Innovating in an Age of Personalization
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Innovating in an Age of Personalization
FountainBlue curates articles and information about the emergence of the Age of Personalization, and how leaders and companies are succeeding with the opportunities ahead.
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Competing in a world of sectors without borders | McKinsey & Company

Competing in a world of sectors without borders | McKinsey & Company | Innovating in an Age of Personalization | Scoop.it
Competing in a world of sectors without bordersBy Venkat Atluri, Miklos Dietz, and Nicolaus Henke
 

Digitization is causing a radical reordering of traditional industry boundaries. What will it take to play offense and defense in tomorrow’s ecosystems?

Rakuten Ichiba is Japan’s single largest online retail marketplace. It also provides loyalty points and e-money usable at hundreds of thousands of stores, virtual and real. It issues credit cards to tens of millions of members. It offers financial products and services that range from mortgages to securities brokerage. And the company runs one of Japan’s largest online travel portals—plus an instant-messaging app, Viber, which has some 800 million users worldwide. Retailer? Financial company? Rakuten Ichiba is all that and more—just as Amazon and China’s Tencent are tough to categorize as the former engages in e-commerce, cloud-computing, logistics, and consumer electronics, while the latter provides services ranging from social media to gaming to finance and beyond.

Organizations such as these—digital natives that are not defined or constrained by any one industry—may seem like outliers. How applicable to traditional industries is the notion of simultaneously competing in multiple sectors, let alone reimagining sector boundaries? We would be the first to acknowledge that opportunities to attack and to win across sectors vary considerably and that industry definitions have always been fluid: technological developments cause sectors to appear, disappear, and merge. Banking, for example, was born from the merger of money exchange, merchant banking, savings banking, and safety-deposit services, among others. Supermarkets unified previously separate retail subsectors into one big “grocery” category. Changes such as these created new competitors, shifted vast amounts of wealth, and reshaped significant parts of the economy. Before the term was in vogue, one could even say the shifts were “disruptive.”

Yet there does appear to be something new happening here. The ongoing digital revolution, which has been reducing frictional, transactional costs for years, has accelerated recently with tremendous increases in electronic data, the ubiquity of mobile interfaces, and the growing power of artificial intelligence. Together, these forces are reshaping customer expectations and creating the potential for virtually every sector with a distribution component to have its borders redrawn or redefined, at a more rapid pace than we have previously experienced.

Consider first how customer expectations are shifting. As Steve Jobs famously observed, “A lot of times, people don’t know what they want until you show it to them.” By creating a customer-centric, unified value proposition that extends beyond what end users could previously obtain (or, at least, could obtain almost instantly from one interface), digital pioneers are bridging the openings along the value chain, reducing customers’ costs, providing them with new experiences, and whetting their appetites for more.

We’ve all experienced businesses that once seemed disconnected fitting together seamlessly and unleashing surprising synergies: look no farther than the phone in your pocket, your music and video in the cloud, the smart watch on your wrist, and the TV in your living room. Or consider the 89 million customers now accessing Ping An Good Doctor, where on a single platform run by the trusted Ping An insurance company they can connect with doctors not only for online bookings but to receive diagnoses and suggested treatments, often by exchanging pictures and videos. What used to take many weeks and multiple providers can now be done in minutes on one app.

Now nondigital natives are starting to think seriously about their cross-sector opportunities and existential threats that may lurk across boundaries. One example: We recently interviewed 300 CEOs worldwide, across 37 sectors, about advanced data analytics. Fully one-third of them had cross-sector dynamics at top of mind. Many worried, for instance, that “companies from other industries have clearer insight into my customers than I do.” We’ve also seen conglomerates that until recently had thought of themselves as little more than holding companies taking the first steps to set up enterprise-wide consumer data lakes, integrate databases, and optimize the products, services, and insights they provide to their customers. Although these companies must of course abide by privacy laws—and even more, meet their users’ expectations of trust—data sets and sources are becoming great unifiers and creating new, cross-sectoral competitive dynamics.

Do these dynamics portend a sea change for every company? Of course not. People will still stroll impromptu into neighborhood stores, heavy industry (with the benefit of technological advances, to be sure) will go on extracting and processing the materials essential to our daily lives, and countless other enterprises beyond the digital space will continue to channel the ingenuity of their founders and employees to serve a world of incredibly varied preferences and needs. It’s obvious that digital will not—and cannot—change everything.

But it’s just as apparent that its effects on the competitive landscape are already profound and that the stakes are getting higher. As boundaries between industry sectors continue to blur, CEOs—many of whose companies have long commanded large revenue pools within traditional industry lines—will face off against companies and industries they never previously viewed as competitors. This new environment will play out by new rules, require different capabilities, and rely to an extraordinary extent upon data. Defending your position will be mission critical, but so too will be attacking and capturing the opportunities across sectors before others get there first. To put it another way: within a decade, companies will define their business models not by how they play against traditional industry peers but by how effective they are in competing within rapidly emerging “ecosystems,” comprising a variety of businesses from dimensionally different sectors.

A world of digital ecosystems

As the approaching contest plays out, we believe an increasing number of industries will converge under newer, broader, and more dynamic alignments: digital ecosystems. A world of ecosystems will be a highly customer-centric model, where users can enjoy an end-to-end experience for a wide range of products and services through a single access gateway, without leaving the ecosystem. Ecosystems will comprise diverse players who provide digitally accessed, multi-industry solutions. The relationship among these participants will be commercial and contractual, and the contracts (whether written, digital, or both) will formally regulate the payments or other considerations trading hands, the services provided, and the rules governing the provision of and access to ecosystem data.

Beyond just defining relationships among ecosystem participants, the digitization of many such arrangements is changing the boundaries of the company by reducing frictional costs associated with activities such as trading, measurement, and maintaining trust. More than 80 years ago, Nobel laureate Ronald Coase argued that companies establish their boundaries on the basis of transaction costs like these: when the cost of transacting for a product or service on the open market exceeds the cost of managing and coordinating the incremental activity needed to create that product or service internally, the company will perform the activity in-house. As digitization reduces transaction costs, it becomes economic for companies to contract out more activities, and a richer set of more specialized ecosystem relationships is facilitated.

Rising expectations

Those ecosystem relationships, in turn, are making it possible to better meet rising customer expectations. The mobile Internet, the data-crunching power of advanced analytics, and the maturation of artificial intelligence (AI) have led consumers to expect fully personalized solutions, delivered in milliseconds. Ecosystem orchestrators use data to connect the dots—by, for example, linking all possible producers with all possible customers, and, increasingly, by predicting the needs of customers before they are articulated. The more a company knows about its customers, the better able it is to offer a truly integrated, end-to-end digital experience and the more services in its ecosystem it can connect to those customers, learning ever more in the process. Amazon, among digital natives, and Centrica, the British utility whose Hive offering seeks to become a digital hub for controlling the home from any device, are early examples of how pivotal players can become embedded in the everyday life of customers.

For all of the speed with which sector boundaries will shift and even disappear, courting deep customer relationships is not a one-step dance. Becoming part of an individual’s day-to-day experience takes time and, because digitization lowers switching costs and heightens price transparency, sustaining trust takes even longer. Over that time frame, significant surplus may shift to consumers—a phenomenon already underway, as digital players are destroying billions to create millions. It’s also a process that will require deploying newer tools and technologies, such as using bots in multidevice environments and exploiting AI to build machine-to-machine capabilities. Paradoxically, sustaining customer relationships will depend as well on factors that defy analytical formulae: the power of a brand, the tone of one’s message, and the emotions your products and services can inspire.

Strategic moves

The growing importance of customer-centricity and the appreciation that consumers will expect a more seamless user experience are reflected in the flurry of recent strategic moves of leading companies across the world. Witness Apple Pay; Tencent’s and Alibaba’s service expansions; Amazon’s decisions to (among other things) launch Amazon Go, acquire Whole Foods, and provide online vehicle searches in Europe; and the wave of announcements from other digital leaders heralding service expansion across emerging ecosystems. Innovative financial players such as CBA (housing and B2B services), mBank (B2C marketplace), and Ping An (for health, housing, and autos) are mobilizing. So are telcos, including Telstra and Telus (each playing in the health ecosystem), and retailers such as Starbucks (with digital content, as well as seamless mobile payments and pre-ordering). Not to be left out are industrial companies such as GE (seeking to make analytics the new “core to the company”) and Ford (which has started to redefine itself as “a mobility company and not just as a car and truck manufacturer”). We’ve also seen ecosystem-minded combinations such as Google’s acquisition of Waze and Microsoft’s purchase of LinkedIn. Many of these initiatives will seem like baby steps when we look back a decade from now, but they reveal the significance placed by corporate strategists on the emergence of a new world.

While it might be tempting to conclude as a governing principle that aggressively buying your way into new sectors is the secret spice for ecosystem success, massive combinations can also be recipes for massive value destruction. To keep your bearings in this new world, focus on what matters most—your core value propositions, your distinct competitive advantages, fundamental human and organizational needs, and the data and technologies available to tie them all together. That calls for thinking strategically about what you can provide your customers within a logically connected network of goods and services: critical building blocks of an ecosystem, as we’ve noted above.

Value at stake

Based on current trends, observable economic trajectories, and existing regulatory frameworks, we expect that within about a decade 12 large ecosystems will emerge in retail and institutional spaces. Their final shape is far from certain, but we suspect they could take something like the form presented in Exhibit 1.

Exhibit 1
Sidebar

China by the numbers

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The actual shape and composition of these ecosystems will vary by country and region, both because of the effects of regulations and as a result of more subtle, cultural customs and tastes. We already see in China, for example, how a large base of young, tech-savvy consumers, a wide amalgam of low-efficiency traditional industries, and, not least, a powerful regulator have converged to give rise to leviathans such as Alibaba and Tencent—ideal for the Chinese market but not (at least, not yet) able to capture significant share in other geographies (see sidebar, “China by the numbers”).

The value at stake is enormous. The World Bank projects the combined revenue of global businesses will be more than $190 trillion within a decade. If digital distribution (combining B2B and B2C commerce) represents about one-half of the nonproduction portion of the global economy by that time, the revenues that could, theoretically, be redistributed across traditional sectoral borders in 2025 would exceed $60 trillion—about 30 percent of world revenue pools that year. Under standard margin assumptions, this would translate to some $11 trillion in global profits, which, once we subtract approximately $10 trillion for cost of equity, amounts to $1 trillion in total economic profit.1

Snapshots of the future

Again, it’s uncertain how much of this value will be reapportioned between businesses and consumers, let alone among industries, sectors, and individual companies, or whether and to what extent governments will take steps to weigh in. To a significant degree, many of the steps that companies are taking and contemplating are defensive in nature—fending off newer entrants, by using data and customer relationships to shore up their core. As incumbents and digital natives alike seek to secure their positions while building new ones, ecosystems are sure to evolve in ways that surprise us. Here is a quick look at developments underway in three of them.

Consumer marketplaces

By now, purchasing and selling on sites such as Alibaba, Amazon, and eBay is almost instinctive; retail has already been changed forever. But we expect that the very concept of a clearly demarcated retail sector will be radically altered within a decade. Three critical, related factors are at work.

First, the frame of reference: what we think of now as one-off purchases will more properly be understood as part of a consumer’s passage through time—the accumulation of purchases made from day to day, month to month, year to year, and ultimately the way those interact over a lifetime. Income and wealth certainly have predictive value for future purchases, but behavior matters even more. Choices to eat more healthily, for example, correlate to a likelihood for higher consumption of physical fitness gear and services, and also to a more attractive profile for health and life insurers, which should result in more affordable coverage.

The second major factor, reinforcing the first, is the growing ability of data and analytics to transform disparate pieces of information about a consumer’s immediate desires and behavior into insight about the consumer’s broader needs. That requires a combination of capturing innumerable data points and turning them, within milliseconds, into predictive, actionable opportunities for both sellers and buyers. Advances in big data analytics, processing power, and AI are already making such connections possible.

This all generates a highly robust “network factor”—the third major force behind emerging consumer marketplaces. In a world of digital networks, consumer lenders, food and beverage providers, and telecom players will simultaneously coexist, actively partner, and aggressively move to capture share from one another. And while digitization may offer the sizzle, traditional industries still have their share of the steak. These businesses not only provide the core goods and services that end users demand, but often also have developed relationships with other businesses along the value chain and, most important, with the end users themselves. Succeeding in digital marketplaces will require these companies to stretch beyond their core capabilities, to be sure, but if they understand the essentials of what’s happening and take the right steps to secure and expand their relationships, nondigital businesses can still hold high ground when the waves of change arrive.

B2B services

The administrative burdens of medium, small, and microsize companies are both cumbersome and costly. In addition to managing their own products and services, these businesses (like their larger peers) must navigate a slew of necessary functions including human resources, tax planning, legal services, accounting, finance, and insurance.

Today, each of these fields exists as an independent sector, but it’s easy to imagine them converging within a decade on shared, cloud-based platforms that will serve as one-stop shops. With so many service providers available at the ease of a click, all with greater transparency on price, performance, and reputation, competition will ramp up and established players can anticipate more challengers from different directions. At the same time, it’s likely that something approaching a genuine community will develop, with businesses being able to create partnerships and tap far more sophisticated services than they can at present—including cash-planning tools, instant credit lines, and tailored insurance.

Already, we can glimpse such innovations starting to flourish in a range of creative solutions. Idea Bank in Poland, for example, offers “idea hubs” and applications such as e-invoicing and online factoring. ING’s commercial platform stretches beyond traditional banking services to include (among other things) a digital loyalty program and crowdfunding. And Lloyds Bank’s Business Toolbox includes legal assistance, online backup, and email hosting. As other businesses join in, we expect the scope and utility of this space to grow dramatically.

Mobility

Finally, consider personal mobility, which encompasses vehicle purchase and maintenance management, ridesharing, carpooling, traffic management, vehicle connectivity, and much more. The individual pieces of the mobility puzzle are starting to become familiar, but it’s their cumulative impact that truly shows the degree to which industry borders are blurring (Exhibit 2).

Exhibit 2

 

 

 

 

 

 

 

 

 

 

Emerging priorities for the borderless economy

These glimpses of the future are rooted in the here and now, and they are emblematic of shifts underway in most sectors of the economy—including, more likely than not, yours. We hope this article is a useful starting point for identifying potential industry shifts that could be coming your way. Recognition is the first step, and then you need a game plan for a world of sectors without borders. The following four priorities are critical:

  • Adopt an ecosystem mind-set. The landscape described in this article differs significantly from the one that still dominates most companies’ business planning and operating approaches. Job one for many companies is to broaden their view of competitors and opportunities so that it is truly multisectoral, defines the ecosystems and industries where change will be fastest, and identifies the critical new sources of value most meaningful for an expanding consumer base. In essence, you must refine your “self vision” by asking yourself, and your top team, questions such as: “What surprising, disruptive boundary shifts can we imagine—and try to get ahead of?” and “How can we turn our physical assets and long-established customer relationships into genuine consumer insights to secure what we have and stake out an advantage over our competitors—including the digital giants?” That shift will necessarily involve an important organizational component, and leaders should expect some measure of internal resistance, particularly when existing business goals, incentives, and performance-management principles do not accord with new strategic priorities. It will also, of course, require competitive targeting beyond the four walls of your company. But resist the impulse to just open up your acquisition checkbook. The combinations that make good sense will be part of a rational answer to perennial strategic questions about where and how your company needs to compete—playing out on an expanding field.
  • Follow the data. In our borderless world, data are the coins of the realm. Competing effectively means both collecting large amounts of data, and developing capabilities for storing, processing, and translating the data into actionable business insights. A critical goal for most companies is data diversity—achieved, in part, through partnerships—which will enable you to pursue ever-finer microsegmentation and create more value in more ecosystems. Information from telecommunications-services players, for example, can help banks to engage their customers and make a variety of commercial decisions more effectively. Deeper data insights are finally beginning to take ideas that had always seemed good but too often fell short of their potential to turn into winning models. Consider loyalty cards: by understanding customers better, card providers such as Nectar, the largest loyalty program in the United Kingdom, and Plenti, a rewards programs introduced by American Express, can connect hundreds of companies of all sizes and across multiple industries to provide significant savings for consumers and new growth opportunities for the businesses that serve them. Meanwhile, the cost of sharing data is falling as cloud-based data stores proliferate and AI makes it easier to link data sets to individual customers or segments. Better data can also support analytically driven scenario planning to inform how ecosystems will evolve, at which points along the value chain your data can create value, and whether or where you can identify potential “Holy Grail” data assets. What data points and sources are critical to your business? How many do you have? What can you do to acquire or gain access to the rest? You should be asking your organization questions like these regularly.
  • Build emotional ties to customers. If blurring sector boundaries are turning data into currency, customer ownership is becoming the ultimate prize. Companies that lack strong customer connections run the risk of disintermediation and perhaps of becoming “white-label back offices” (or production centers), with limited headroom to create or retain economic surplus. Data (to customize offerings), content (to capture the attention of customers), and digital engagement models (to create seamless customer journeys that solve customer pain points) can all help you build emotional connections with customers and occupy attractive roles in critical ecosystems. You should continually be asking your organization, “What’s our plan for using data, content, and digital-engagement tools to connect emotionally with customers?” and “What else can we provide, with simplicity and speed, to strengthen our consumer bond?” After all, Google’s launch of initiatives such as Chrome and Gmail, and Alibaba’s introduction of enterprises such as Alipay and the financial platform Yu’E Bao, weren’t executed merely because they already had a huge customer base and wanted to capture new sources of revenue (although they did succeed in doing so). They took action to help ensure they would keep—and expand—that huge customer base.
  • Change your partnership paradigm. Given the opportunities for specialization created by an ecosystem economy, companies need more and different kinds of partners. In at least a dozen markets worldwide—including Brazil, Turkey, and several countries in Asia, where in many respects data are currently less robust than they are in other regions—we’re seeing a new wave of partnership energy aimed at making the whole greater than the sum of its parts. Regardless of your base geography, core industry, and state of data readiness, start by asking what white spaces you need to fill, what partners can best help with those gaps, and what “gives” and “gets” might be mutually beneficial. You’ll also need to think about how to create an infrastructural and operational framework that invites a steady exchange with outside entities of data, ideas, and services to fuel innovation. Don’t forget about the implications for your information architecture, including the application programming interfaces (APIs) that will enable critical external linkages, and don’t neglect the possibility that you may need to enlist a more natural integrator from across your partnerships, which could include a company more appropriate for the role, such as a telco, or a third-party provider that can more effectively connect nondigital natives. And don’t assume that if you were to acquire a potential partner, you’d necessarily be adding and sustaining their revenues on a dollar-for-dollar basis over the long term.

No one can precisely peg the future. But when we study the details already available to us and think more expansively about how fundamental human needs and powerful technologies are likely to converge going forward, it is difficult to conclude that tomorrow’s industries and sector borders will look like today’s. Massive, multi-industry ecosystems are on the rise, and enormous amounts of value will be on the move. Companies that have long operated with relative insularity in traditional industries may be most open to cross-boundary attack. Yet with the right strategy and approach, leaders can exploit new openings to go on offense, as well. Now is the time to take stock and to start shaping nascent opportunities.

Linda Holroyd's insight:
  • Adopt an ecosystem mind-set
  • Follow the data. 
  • Build emotional ties to customers.
  • Change your partnership paradigm. 
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The Consumer Behaviors Shaping the Next Generation of Mobile Experiences

The Consumer Behaviors Shaping the Next Generation of Mobile Experiences | Innovating in an Age of Personalization | Scoop.it

The digital experiences people expect and marketers can deliver have changed dramatically, and Jason Spero has had a front-row seat. Now, Google’s VP of Global Performance Solutions is keeping an eye on the consumer behaviors shaping the next generation of experiences.

We’re living in the golden age of user experience. Startups are upending entire industries with their focus on simplicity, while traditional companies reinvent themselves on mobile to stay relevant.

But it’s not the technology that gets me most excited. Rather it’s the rich experiences that technology is enabling for consumers and the impact it’s having on marketers like you and me. The speed at which brands are introducing compelling new experiences is only accelerating. We’ve not seen anything like it before.

For us as marketers, that means consumer expectations are higher than ever. We’re no longer competing with the best experience in our respective categories. We’re now competing with the best experience a consumer has ever had.

Every time a company designs a rich, useful, or new experience, it raises the bar for what consumers care about. On the flip side, if an experience is frustrating or annoying, a consumer may not give that company a second chance. Building a great user experience is a challenge, especially as we all grapple with how and when to experiment with new technologies.

But rather than think about the technologies first, I find it helps to imagine the experience you’d want as a consumer, apply it to your brand, and build toward that. Here are three things I hear from consumers when it comes to what they expect from brands:

 “Help me faster”

Technology is becoming assistive in ways we couldn’t have imagined a few years ago. We can pay for coffee with a tap. We can deposit a check by snapping a photo. And we can order laundry detergent with a voice command to a digital assistant.

But as technology enables faster experiences, consumers are growing impatient. Their willingness to wait is declining and, as a result, consumers are shifting their thinking from, “Who does it best?” to “Who does it best now?”

Source: Google Data, Global, n=3,700 aggregated, anonymized Google Analytics data from a sample of mWeb sites opted into sharing benchmark data, Mar. 2016.

 

There’s a price to pay if you don’t consider speed. Fifty-three percent of people will abandon a mobile site if it takes more than three seconds to load.1 Now here’s the reality: We tested 900,000 mobile sites globally and found that the average time it takes to fully load a mobile page is 22 seconds.2

Speed is a developer’s problem, a designer’s problem, and therefore, a marketer’s problem. When marketers prioritize speed it has a ripple effect. Designers must then focus on selecting visual elements, fonts, and a design structure that allow for fast, frictionless mobile experiences. And developers can further optimize, ensuring the best mobile experience possible.

 
“Know me better”

Personalized and relevant experiences are key to connecting with consumers, and they have a positive impact on the bottom line. Eighty-nine percent of U.S. marketers reported that personalization on their websites or apps resulted in an increase in revenue.3

Source: eMarketer/Evergage, "2016 Trends in Personalization," conducted by Researchscape. Data was provided to eMarketer by Evergage; June 14, 2016.

 

But personalization is a strategy, not a feature. We have an opportunity to be smarter with data, using important signals about customers—such as browsing behavior or CRM data—to shape their experiences. 

For example, when Maybelline was preparing to launch new products for contouring—a type of makeup application that is becoming more mainstream—it used Google Insights to craft how-to videos, which are personalized by intent and demographic. As a result, Maybelline’s videos racked up 9M views.

Likewise, 63% of people expect brands to use their purchase history to provide them with personalized experiences.4 In other words, if you know I just purchased a pair of shoes, then offer me socks or a matching belt to go with them.

“Wow me everywhere”

Brands need to consider how all of their experiences—across media, channels, and devices—fit together.

Source: Google/Greenberg, U.S., “Rising Expectations in Consumer Experiences,” n=1,501 consumers aged 18–54, Mar. 2017.

 

Sixty-two percent of people expect brands to deliver a consistent experience every time they interact with a brand. But only 42% believe brands actually do provide a consistent experience.

Walgreens provides a good example of seamless, consistent experiences in action. The brand’s team recognized that mobile could help it remove barriers between online and offline. Its mobile app connects consumers with a doctor or pharmacist online, and consumers can then pick up prescriptions in-store. Likewise, beauty advisors are armed with tablets, so they can quickly pull up past purchases online and make recommendations for offline purchases. 

The approach is paying off. Customers who interact with Walgreens in-store and on mobile are six times more valuable than someone who only visits the brand’s physical stores.

Bringing it all together

As consumer behaviors shift, it will be important to rethink the investments we make in the user experience. Removing friction and bridging the gaps between channels—all while treating each customer as a unique individual—will be key.

Ultimately, creating great digital customer experiences is not solely a product challenge or a marketing challenge. It’s a business opportunity. And those who invest in creating memorable experiences will win users’ hearts, minds, and ultimately, dollars.

Jason Spero

VP of Global Performance Solutions at Google

Linda Holroyd's insight:

Help me faster. Know me better. Wow me everywhere. . .

No pressure!

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How to succeed as a chief digital officer in pharma | McKinsey & Company

How to succeed as a chief digital officer in pharma | McKinsey & Company | Innovating in an Age of Personalization | Scoop.it

The life-sciences industry is embracing digital to unlock innovation. We spoke to ten digital leaders at global pharmaceutical companies to understand how they focus their efforts.

The conviction that competitive differentiation will require effective digital initiatives has led many life-sciences companies to create a new leadership role, chief digital officer (CDO), to guide their digital initiatives.

To understand how these leaders see the digital future and how they are managing for success, we spoke to CDOs and their equivalents at ten pharma companies. These conversations suggest three imperatives for digital efforts: focus on the team applying the tools, not on the tools themselves; make bold, disruptive bets; and optimize the portfolio of initiatives to achieve company priorities, while taking finite resources into account.

Focus on teams and capabilities, not tools

Like most tools, digital technology becomes commoditized, so gains from early adoption tend to fade as technology becomes cheaper and more accessible. Thus, technology itself is unlikely to be a sustainable differentiator.

“It is easy for businesses to jump to technology, to be enamored with the shiny objects and not focus on the problem [they are] trying to solve,” says Amy Landucci, global head of digital medicines at Novartis. Sustainable differentiation requires a focus on generating cutting-edge insights into the business and its possibilities. To that end, companies must build teams of people capable of generating such insights. The team, not the tool, is the vital element in digital success across industries.1

The team must have a suite of digital capabilities, including expertise in data science and multichannel management, experience deriving insights from real-world evidence, and a system of digital tools to complement traditional pharmaceuticals. Generating differentiating insights requires a cross-functional team that’s able to work across markets.

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A team member needs to have “drive, good understanding of customer journeys and ability to identify the relevant innovative digital solutions leading to better healthcare outcomes. He/she needs to inspire the rest of the organization,” according to Betul Susamis Unaran, global head of digital at Ferring Pharmaceuticals. Other digital leaders say they seek individuals who want a job that is not purely technical, who can understand pain points and ways that digital technology can resolve them, and who can work with diverse members of the wider enterprise. These abilities are crucial, since “getting digital embedded in the business is just as difficult as figuring out where to focus,” says Francis Kendall, digital-strategy leader at Roche.

The evolution of digital in the strategy of manufacturers creates this need for cross-functional teams. The next few years will likely see manufacturers’ focus shift from technology to design in order to ensure adoption of digital and analytics solutions inside and outside the enterprise. Several factors will fuel this shift.

First, powerful digital and analytics platforms that enable faster and easier application development are emerging. For example, while deep learning analytics used to be the secret gardens of a few technology companies, open-source platforms like Alphabet’s TensorFlow can enable anyone (with solid mathematical skills) to develop innovative analytics. The impact of the analytical tools will depend on their reach, which will in turn depend on the creation of interfaces that enable lay users to leverage the analytics in their day-to-day work. Creating intuitive interfaces so executives, physicians, or patients can use—and help improve—the tools will be mostly a design and marketing challenge.

Second, just as tech companies such as Apple and Fitbit have made user-centric design a significant source of digital value, life-sciences companies will embed design thinking into their approaches to the market. Many are realizing that differentiating through digital will require translating deep customer insights into solution designs that help patients and providers simplify their journeys or improve their outcomes.

Finally, life-sciences companies are increasingly recognizing the need to overhaul their current approach to application development. Only a handful of the 160,000 healthcare applications available on iOS, for example, are used at scale. Similarly, pharmaceutical manufacturers are starting to realize that creating applications focused solely on their products will limit their impact. Most patients are polymedicated and require interoperable solutions. How many apps will a single patient use?

The adoption challenge is huge and will require sophisticated teams that put digital and analytics at the heart of the business. Attracting such talent remains challenging, as multiple tech companies are venturing into life sciences. Companies in some industries admit paying digital executives more than the CEO, albeit on terms strongly linked to performance.

The organizational structures within which teams operate will depend on their mandate. Philip Ma, vice president of digital health technology and data sciences at Biogen, says that a key question is whether the company’s strategy is “to enable the existing business or to create new businesses.” Most CDOs with whom we spoke are charged with enabling the development of digital solutions within the core of the business, so they have organized their teams to integrate closely with, and have influence on, business functions.

But the rarer strategy of using digital to create novel business lines and revenue streams calls for designing the organization to be as unencumbered as possible by the current enterprise. Kristian Hart-Hansen, CEO of the LEO Innovation Lab, says that he wants to be like a “speed boat going out into open waters.” Otsuka Digital Health, a start-up created to commercialize a digital behavior-health platform, is similarly freestanding.2

Make bold, disruptive bets

Change in today’s digital world is proceeding rapidly. The belief that digital change happens incrementally is dangerous and has contributed to the demise of many companies, including some with a rich technological history—such as Kodak, a technology leader that failed to keep pace with the rapid digitization of photography.

A portfolio of digital initiatives should include bold, disruptive bets. Malika Mir, CDO at Ipsen, says that a key part of her role is “to make sure that the business understands digital is a game changer, that it will revolutionize how we do business.”

Other industries offer valuable lessons for pharma. In some industries, digital has moderately realigned supply and demand in the market by exposing new supply (Airbnb) or by addressing unmet demand (streaming services that unbundle single songs from albums). In other industries, market dynamics have shifted radically, with companies reimagining products and services (as, for example, Amazon and Dropbox transformed storage products into a service) or hyperscaling platforms that blur traditional industry definitions and span multiple market segments (Apple, Google, and Tencent).3In banking, among other industries, traditional barriers to entry, such as regulatory control, have not prevented extreme market shifts—signaling risks for companies that ignore the need to make bold moves.

While many pharma companies are launching game-changing initiatives to transform their core business, another option is to create a separate, self-sustaining entity for these efforts. LEO Pharma created Innovation Lab as an independent unit with multiyear funding to focus on nonpharmacologic digital solutions for patients with skin diseases. As CEO Hart-Hansen suggests, LEO Innovation Lab is shifting “from a pills company to a solutions company,” creating digital platforms and applications not necessarily tied to drugs.

Initiatives fall into two key categories. A disruptive initiative inherently transforms a product or a customer experience (or the monetization of either). Conversely, an optimizing digital initiative improves the efficiency of a business or product more incrementally. The distinction is important.

Disruptive initiatives require substantial change and create tension in the enterprise. Success metrics are rarely fiscal, especially in the early stages. These initiatives require multiyear investments and extensive capability building, and they have a higher risk of failure than optimizing initiatives.

Optimizing initiatives often have a measurable return on investment. These “safer” initiatives are important, but too much attention to them can prove dangerous, as they can create a false sense of security. They consume the digital team’s time and effort but rarely mitigate the external risk of disruption to the enterprise.

Optimize the portfolio

From the many digital initiatives available to them, CDOs must choose those that will best serve the company’s priorities within its finite resources. Making the right choice requires setting the digital strategy, aligning initiatives with strategic goals, creating metrics for and prioritizing initiatives, and developing an operating model.

Setting the digital strategy requires identifying how digital technology can help redefine the business (that is, the use cases). This step ensures focus on addressing the needs of the enterprise, with less focus on the technology itself. “Technology is here to facilitate a business,” says Marcello Damiani, chief digital officer of Moderna Therapeutics. “If you don’t understand your business, you can’t apply your technology.”

Then the CDO needs to inventory initiatives and align them with the use cases. Except for a new or small company that is “planting its initiatives in a green field,” most companies have existing initiatives that have arisen organically within the enterprise. A closer look at these initiatives often finds opportunities to combine some by use case. Philip Ma of Biogen, for instance, has reorganized multiple small analytics and data-science initiatives to take advantage of their interdependencies in helping the company get better at forecasting.

Next, the CDO needs to define metrics for success, as a basis for prioritizing initiatives. The right metrics depend on the type and scope of the initiative. CDOs agree that a financial-output metric such as return on investment is not necessarily well suited to disruptive initiatives in their early stages (or ever, in many cases). In the early stages, measures appropriate to a specific use case, such as increased customer adoption or shorter recruitment time, are generally more appropriate. Most also use a second metric, such as degree of alignment or likelihood of implementation, to reflect the desire and ability to execute an initiative—underscoring the importance of change management in deploying digital.

Combining these metrics with resource requirements is an effective way to prioritize initiatives. Some CDOs discover that their portfolio focuses too heavily on technology like apps or analytics. Others see that they lack the capability4or team for effective execution.

Finally, the CDO must develop an operating model. A common impediment to successful deployment of digital initiatives is the company’s traditional way of working. Established pharmaceutical companies typically make decisions meticulously, and often slowly. As a result, the CDOs we interviewed recognize the need to develop new operating models that enable rapid building, testing, and learning—an agile or lean-start-up model, for example. The goal is to swiftly deepen understanding of the customer or use case and learn from failed experiments.

For instance, one company recently developed a new pricing and contracting tool for medical-device representatives. Instead of modifying the core analytical engine embedded in a complex legacy system, it deployed a new cloud-based solution, initially using simple outputs from the legacy system. Believing that the tool was directionally correct, the company piloted and refined it with field representatives. It gradually developed a full solution to embed in the enterprise system, but it benefited from the impact of the initial solution in the meantime.

How pharma can win in a digital worldRead the article

The status quo is often deeply rooted in large pharma companies, and this can hamper the effort to create a build-test-learn operating model. For example, team members often have difficulty accepting the failures that inevitably happen when testing and iterating a nascent initiative.

Some CDOs tackle such issues by asking senior management to realign employees’ performance metrics. Others recruit individuals from technology firms and start-ups, where the build-test-learn approach is part of the company culture. “It’s OK to fail,” says Michael Russo, executive director of digital strategy and innovation of Acorda Therapeutics, “but fail quickly and learn from the mistakes.” Role modeling by leaders—for example, when an executive describes his or her own failures and the lessons learned—can also help shift the culture.

A crucial part of the new operating model is an approach to knowledge management. Malika Mir of Ipsen, for example, has established processes to record all initiatives in a central database in order to track them and share knowledge from successful and failed initiatives across the global organization. This has the added benefit of providing a means of tracking initiatives.

Deployment of resources is equally important. In the early stages of an initiative, when the potential for failure is high, use of resources needs to be limited without extinguishing innovation. “If tests show the project is good and we see a business case, then we go to beta phase and scale up,” says Hart-Hansen of LEO Innovation Lab. One CDO speaks of putting “guardrails” around the resources devoted to initiatives, while empowering leaders to allocate the resources as they see fit.

CDOs can play a key role in guiding life-sciences companies through the disruption of digital technology and reaping its rewards. Successful CDOs build teams that can generate insights from digital tools and have the courage to make bold, disruptive bets. These leaders also create a portfolio of initiatives that match company priorities and make the organizational changes needed to execute those initiatives successfully.

In an end state where digital is fully embedded in the business, the successful digital leader may be faced with the dilemma of his or her position becoming redundant. At its best, the CDO is thus an agent of transformation, and the epitome of selfless leadership.

About the author(s)

Amy Hung is a senior expert in McKinsey’s New Jersey office, Olivier Leclerc is a senior partner in the Southern California office, and Travis Murdoch is a consultant in the Silicon Valley office.
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The case for digital reinvention | McKinsey & Company

The case for digital reinvention | McKinsey & Company | Innovating in an Age of Personalization | Scoop.it

The case for digital reinvention
By Jacques Bughin, Laura LaBerge, and Anette Mellbye

Digital technology, despite its seeming ubiquity, has only begun to penetrate industries. As it continues its advance, the implications for revenues, profits, and opportunities will be dramatic.

As new markets emerge, profit pools shift, and digital technologies pervade more of everyday life, it’s easy to assume that the economy’s digitization is already far advanced. According to our latest research, however, the forces of digital have yet to become fully mainstream. On average, industries are less than 40 percent digitized, despite the relatively deep penetration of these technologies in media, retail, and high tech.

As digitization penetrates more fully, it will dampen revenue and profit growth for some, particularly the bottom quartile of companies, according to our research, while the top quartile captures disproportionate gains. Bold, tightly integrated digital strategies will be the biggest differentiator between companies that win and companies that don’t, and the biggest payouts will go to those that initiate digital disruptions. Fast-followers with operational excellence and superior organizational health won’t be far behind.

These findings emerged from a research effort to understand the nature, extent, and top-management implications of the progress of digitization. We tailored our efforts to examine its effects along multiple dimensions: products and services, marketing and distribution channels, business processes, supply chains, and new entrants at the ecosystem level (for details, see sidebar “About the research”). We sought to understand how economic performance will change as digitization continues its advance along these different dimensions. What are the best-performing companies doing in the face of rising pressure? Which approach is more important as digitization progresses: a great strategy with average execution or an average strategy with great execution?

The research-survey findings, taken together, amount to a clear mandate to act decisively, whether through the creation of new digital businesses or by reinventing the core of today’s strategic, operational, and organizational approaches.

More digitization—and performance pressure—ahead

According to our research, digitization has only begun to transform many industries (Exhibit 1). Its impact on the economic performance of companies, while already significant, is far from complete.

This finding confirms what many executives may already suspect: by reducing economic friction, digitization enables competition that pressures revenue and profit growth. Current levels of digitization have already taken out, on average, up to six points of annual revenue and 4.5 points of growth in earnings before interest and taxes (EBIT). And there’s more pressure ahead, our research suggests, as digital penetration deepens (Exhibit 2).

While the prospect of declining growth rates is hardly encouraging, executives should bear in mind that these are average declines across all industries. Beyond the averages, we find that performance is distributed unequally, as digital further separates the high performers from the also-rans. This finding is consistent with a separate McKinsey research stream, which also shows that economic performance is extremely unequal. Strongly performing industries, according to that research, are three times more likely than others to generate market-beating economic profit. Poorly performing companies probably won’t thrive no matter which industry they compete in.

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At the current level of digitization, median companies, which secure three additional points of revenue and EBIT growth, do better than average ones, presumably because the long tail of companies hit hard by digitization pulls down the mean. But our survey results suggest that as digital increases economic pressure, all companies, no matter what their position on the performance curve may be, will be affected.

Uneven returns on investment

That economic pressure will make it increasingly critical for executives to pay careful heed to where—and not just how—they compete and to monitor closely the return on their digital investments. So far, the results are uneven. Exhibit 3 shows returns distributed unequally: some players in every industry are earning outsized returns, while many others in the same industries are experiencing returns below the cost of capital.


These findings suggest that some companies are investing in the wrong places or investing too much (or too little) in the right ones—or simply that their returns on digital investments are being competed away or transferred to consumers. On the other hand, the fact that high performers exist in every industry (as we’ll discuss further in a moment) indicates that some companies are getting it right—benefiting, for example, from cross-industry transfers, as when technology companies capture value in the media sector.

Where to make your digital investments

Improving the ROI of digital investments requires precise targeting along the dimensions where digitization is proceeding. Digital has widely expanded the number of available investment options, and simply spreading the same amount of resources across them is a losing proposition. In our research, we measured five separate dimensions of digitization’s advance into industries: products and services, marketing and distribution channels, business processes, supply chains, and new entrants acting in ecosystems.

How fully each of these dimensions has advanced, and the actions companies are taking in response, differ according to the dimension in question. And there appear to be mismatches between opportunities and investments. Those mismatches reflect advancing digitization’s uneven effect on revenue and profit growth, because of differences among dimensions as well as among industries. Exhibit 4 describes the rate of change in revenue and EBIT growth that appears to be occurring as industries progress toward full digitization. This picture, combining the data for all of the industries we studied, reveals that today’s average level of digitization, shown by the dotted vertical line, differs for each dimension. Products and services are more digitized, supply chains less so.

Exhibit 4

To model the potential effects of full digitization on economic performance, we linked the revenue and EBIT growth of companies to a given dimension’s digitization rate, leaving everything else equal. The results confirm that digitization’s effects depend on where you look. Some dimensions take a bigger bite out of revenue and profit growth, while others are digitizing faster. This makes intuitive sense. As platforms transform industry ecosystems, for example, revenues grow—even as platform-based competitors put pressure on profits. As companies digitize business processes, profits increase, even though little momentum in top-line growth accompanies them.

The biggest future impact on revenue and EBIT growth, as Exhibit 4 shows, is set to occur through the digitization of supply chains. In this dimension, full digitization contributes two-thirds (6.8 percentage points of 10.2 percent) of the total projected hit to annual revenue growth and more than 75 percent (9.4 out of 12 percent) to annual EBIT growth.

Despite the supply chain’s potential impact on the growth of revenues and profits, survey respondents say that their companies aren’t yet investing heavily in this dimension. Only 2 percent, in fact, report that supply chains are the focus of their forward-looking digital strategies (Exhibit 5), though headlining examples such as Airbnb and Uber demonstrate the power of tapping previously inaccessible sources of supply (sharing rides or rooms, respectively) and bringing them to market. Similarly, there is little investment in the ecosystems dimension, where hyperscale businesses such as Alibaba, Amazon, Google, and Tencent are pushing digitization most radically, often entering one industry and leveraging platforms to create collateral damage in others.1
Exhibit 5

Instead, the survey indicates that distribution channels and marketing are the primary focus of digital strategies (and thus investments) at 49 percent of companies. That focus is sensible, given the extraordinary impact digitization has already had on customer interactions and the power of digital tools to target marketing investments precisely. By now, in fact, this critical dimension has become “table stakes” for staying in the game. Standing pat is not an option.

The question, it seems, looking at exhibits 4 and 5 in combination, is whether companies are overlooking emerging opportunities, such as those in supply chains, that are likely to have a major influence on future revenues and profits. That may call for resource reallocation. In general, companies that strategically shift resources create more value and deliver higher returns to shareholders. This general finding could be even more true as digitization progresses.

Our survey results also suggest companies are not sufficiently bold in the magnitude and scope of their investments (see sidebar “Structuring your digital reinvention”). Our research (Exhibit 6) suggests that the more aggressively they respond to the digitization of their industries—up to and including initiating digital disruption—the better the effect on their projected revenue and profit growth. The one exception is the ecosystem dimension: an overactive response to new hyperscale competitors actually lowers projected growth, perhaps because many incumbents lack the assets and capabilities necessary for platform strategies.

As executives assess the scope of their investments, they should ask themselves if they have taken only a few steps forward in a given dimension—by digitizing their existing customer touchpoints, say. Others might find that they have acted more significantly by digitizing nearly all of their business processes and introducing new ones, where needed, to connect suppliers and users.

To that end, it may be useful to take a closer look at Exhibit 6, which comprises six smaller charts. The last of them totals up actions companies take in each dimension of digitization. Here we can see that the most assertive players will be able to restore more than 11 percent of the 12 percent loss in projected revenue growth, as well as 7.3 percent of the 10.4 percent reduction in profit growth. Such results will require action across all dimensions, not just one or two—a tall order for any management team, even those at today’s digital leaders.

Looking at the digital winners

To understand what today’s leaders are doing, we identified the companies in our survey that achieved top-quartile rankings in each of three measures: revenue growth, EBIT growth, and return on digital investment.

We found that more than twice as many leading companies closely tie their digital and corporate strategies than don’t. What’s more, winners tend to respond to digitization by changing their corporate strategies significantly. This makes intuitive sense: many digital disruptions require fundamental changes to business models. Further, 49 percent of leading companies are investing in digital more than their counterparts do, compared with only 5 percent of the laggards, 90 percent of which invest less than their counterparts. It’s unclear which way the causation runs, of course, but it does appear that heavy digital investment is a differentiator.

Leading companies not only invested more but also did so across all of the dimensions we studied. In other words, winners exceed laggards in both the magnitude and the scope of their digital investments (Exhibit 7). This is a critical element of success, given the different rates at which these dimensions are digitizing and their varying effect on economic performance.

Exhibit 7

Strengths in organizational culture underpin these bolder actions. Winners were less likely to be hindered by siloed mind-sets and behavior or by a fragmented view of their customers. A strong organizational culture is important for several reasons: it enhances the ability to perceive digital threats and opportunities, bolsters the scope of actions companies can take in response to digitization, and supports the coordinated execution of those actions across functions, departments, and business units.


The economic essentials of digital strategy
The economic essentials of digital strategy
Bold strategies win

So we found a mismatch between today’s digital investments and the dimensions in which digitization is most significantly affecting revenue and profit growth. We also confirmed that winners invest more, and more broadly and boldly, than other companies do. Then we tested two paths to growth as industries reach full digitization.

The first path emphasizes strategies that change a business’s scope, including the kind of pure-play disruptions the hyperscale businesses discussed earlier generate. As Exhibit 8 shows, a great strategy can by itself retrieve all of the revenue growth lost, on average, to full digitization—at least in the aggregate industry view. Combining this kind of superior strategy with median performance in the nonstrategy dimensions of McKinsey’s digital-quotient framework—including agile operations, organization, culture, and talent—yields total projected growth of 4.3 percent in annual revenues. (For more about how we arrived at these conclusions, see sidebar “About the research.”)

Exhibit 8

Most executives would fancy the kind of ecosystem play that Alibaba, Amazon, Google, and Tencent have made on their respective platforms. Yet many recognize that few companies can mount disruptive strategies, at least at the ecosystem level. With that in mind, we tested a second path to revenue growth (Exhibit 9).

Exhibit 9

Companies in this profile lack a disruptive strategic posture but compensate by being in the top 25 percent for all the other elements of digital maturity.2 This fast-follower profile allows more room for strategic error—you don’t have to place your bets quite so precisely. It also increases the premium on how well you execute. The size of the win is just slightly positive at 0.4 percent in annual revenue growth: 5.3 percent from good (but not best-in-class disruptive) strategy and an additional 7.1 percent through top-quartile digital maturity. This is probably good news for incumbents, since many of them are carefully watching tech start-ups (such as those in fintech) to identify the winning plays and then imitating them at their own bigger scale. That approach, to be sure, demands cutting-edge agility to excel on all the operational and organizational aspects of digital maturity.

In the quest for coherent responses to a digitizing world, companies must assess how far digitization has progressed along multiple dimensions in their industries and the impact that this evolution is having—and will have—on economic performance. And they must act on each of these dimensions with bold, tightly integrated strategies. Only then will their investments match the context in which they compete.

About the author(s)

Jacques Bughin is a director of the McKinsey Global Institute and a senior partner in McKinsey’s Brussels office; Laura LaBerge is a senior practice manager of Digital McKinsey and is based in the Stamford office; and Anette Mellbye is an associate partner in the London office.

The authors wish to thank Dan Lovallo, Soyoko Umeno, and Nicolas van Zeebroeck for their contributions to this article.
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Why Robots Will Not Decimate Human Jobs

Why Robots Will Not Decimate Human Jobs | Innovating in an Age of Personalization | Scoop.it

Slow economic growth is the mantra of political campaigns and economic angst. Growth in economic output per hour (“labor productivity”) achieved an annual pace of 3 percent for a full half-century between 1920 and 1970. Since 1970 that rate has slowed to about 1.5 percent, and in the last six years productivity growth has slowed further to a lamentable 0.5 percent annual rate.

My book The Rise and Fall of American Growth attributes this enormous contrast between rapid growth in 1920-70 and slow growth after 1970 to the basic nature of inventions. Growth in the middle of the 20th century was propelled by the invention in the late 19th century of electricity, the internal combustion engine, the telephone, chemicals and plastics, and the diffusion to every urban household of clear running water and waste removal. America made a transition from 50 percent of the working population on farms to a largely urban nation, and the drudgery of household work – carrying water in and out, doing laundry on a scrub board – made a transition to modern bathrooms and kitchens by the 1950s.

The digital revolution associated with computers has since 1960 dominated the sphere of innovation, as office work transitioned from the typewriter and old-fashioned calculator to the new world of personal computers, spreadsheet and word processing software, the internet, and search engines. But the impact of this revolution in boosting productivity growth lasted only one decade (1995-2005), a much shorter impetus than occurred earlier in the century when productivity growth achieved its 3 percent annual pace for five decades from 1920 to 1970. 

Why? The computer revolution altered office work but did not extend into everyday life as had the earlier inventions that brought us electricity, motor vehicles, and the modern kitchen and bathroom. Smart phones were introduced by Blackberry in 2003 and by Apple in 2007, but their uses are primarily to boost consumer enjoyment through social networks and game-playing, not a part of the market economy that creates jobs and pays wages. 

Why has productivity growth been so mediocre, a 0.5 percent annual pace since 2010? In my view this has occurred because most of the benefits of the digital revolution were over by 2005. Everywhere you look, from corporate offices to check-in desks at doctor, dentist, and veterinarian offices, the equipment on the desks is the same as in 2005, as is most of the software. 

This slackening of the pace of economic growth due to the minor impact of new innovations has both a pessimistic and an optimistic aspect. Slow productivity growth dampens the ability of business firms to provide wage increases to their workers. But slow productivity growth also means that steadily growing output continues to provide new jobs, 15.5 million of which have been created in the U.S. since early 2010.

But how can so many jobs be created in a world of technological hype of robots taking over the economy? Aren’t robots about to decimate jobs, throwing half the population out of work as has been predicted to occur over the next decade by the two Oxford economists in 2013, Carl Frey and Michael Osborne?

Robots are nothing new; the first industrial robot was introduced by General Motors in 1961, and by the mid-1990s robots had a major role in automobile factories, welding together body parts and freeing human workers from the noxious fumes of the auto paint shop. But robots have made little impact outside of manufacturing. Even Amazon’s high-tech warehouses use robots just to move shelves to human workers, who hand-select the items to be shipped as well as the packing material, and pack the shipments by hand.

But outside of manufacturing and wholesale warehouses, robots are hard to find. I play a game called “find the robot.” In my daily strolls in and out of supermarkets, restaurants, doctor and dentist offices, my nearby hospital, offices in my own university, and the vast amount of employment involving elementary and secondary teachers, personal trainers, and old age caretakers, I have yet to find a robot. 

In my journeys, the closest thing I have found to the introduction of a robot in the service sector is that in a local casual dining restaurant, there are kiosks on the tables to allow patrons to pay their bills without human intervention. But offsetting that is the fact that my local supermarket recently removed its self-checkout electronic kiosks to be replaced by human express checkout agents, apparently due to excessive fraud as customers slid expensive items by the dumb credulity of the self-checkout kiosks.

The Frey and Osborne pessimism about jobs is total fiction. They predict over the next decade that 55 percent of airline pilot jobs will be eliminated. Sorry, but government regulations require two pilots in a commercial aircraft, and a switch to one pilot per aircraft is nowhere in sight. They predict that 92 percent of retail checkout clerk jobs will be eliminated, but there is no robot-like replacement of retail clerks in sight beyond the 30-year-old invention of bar-code scanning.

Surely multiple-function robots will be developed, but it will be a long and gradual process before robots outside of manufacturing and wholesaling become a significant factor in replacing human jobs in the service, transportation or construction sectors. And it is in those sectors that the slowness of productivity growth is dragging down the economy’s overall performance. 

My book concludes that the rapid economic growth of the mid-20th century cannot be repeated. Those “Great Inventions” were too important and too pervasive to happen again anytime soon.  But let us not forget, the corollary of slow productivity growth is the rapid creation of jobs, as we have witnessed in the last six years and will enjoy for the foreseeable future. 

Robert J. Gordon is professor in social sciences at Northwestern University and the author of The Rise and Fall of American Growth, one of six books on the shortlist for the 2016 Financial Times and McKinsey Business Book of the Year Award, to be announced Nov. 22.

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The 3%+ economic growth between 1920 and 1970 was sparked by inventions and innovations that transitioned us from urban living to modern bathrooms and kitchens by the 1950.

Most of the benefits of the digital revolution started in 1960 were over by 2005, and we have witnessed slower productivity growth of 1.5 and even .5 percent since 1970. However, this does not discount the rapid creation of jobs we've witnessed in the last six years and will enjoy for the foreseeable future. 

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Having Diabetes Is No Longer Going To Be A Life Sentence

Having Diabetes Is No Longer Going To Be A Life Sentence | Innovating in an Age of Personalization | Scoop.it

by Reenita Das , CONTRIBUTOR
I cover healthcare issues related to transformation and convergence

Opinions expressed by Forbes Contributors are their ownSource: Frost & Sullivan
While 415 million people suffer from diabetes today, this number is set to rise to 642 million by 2040. As one of the top five mortality causes of 2030, diabetes is indeed a serious global healthcare issue. While we wait for regenerative medicine to provide us with lab-grown pancreases to replace diseased ones and permanently treat diabetes, patients unfortunately will have to continue searching for better tools to manage their disease. The good news is that several approaches have already been undertaken to develop such tools to help them do so.

Here are the top five ways that Frost & Sullivan’s transformational health program analysts predict diabetes management will change in the future.

Mandatory Screening

Current global statistics on diabetes diagnosis are grim–1 in 2 diabetics remains undiagnosed. A primary challenge to overcome this issue lies in the gold standard for diagnosis–fasting and random blood glucose levels. However, this is set to change with the arrival of non-invasive methods to predict diabetes risks. The Scout DS system by Miraculins is one such device. Using visible light to assess skin diabetes biomarkers (like the Advanced Glycation End-Products) on the forearm, the system throws out a diabetes score in 90 seconds. If the score is high, the patient is referred to a specialist for additional tests and consultation. The non-invasive, quick, no-fasting, no-bloodwork system means you could be getting screened for diabetes during your next annual physical checkup at your general physician’s office.

Nutrigenomic Profiling

Every individual is different when it comes to metabolic rates, exercise capabilities, tendencies to put on weight or stay lean, inclination to eating sweets, predisposition to diabetes and so on, courtesy of DNA. But now, we have the ability to sequence our DNA and have access to what is known as the individual nutrigenomic profile. The modern science of nutrigenomics combines nutrition and genetics, enables individuals to know how food constituents interact with their genes at molecular levels, and contributes to the disease. This knowledge can help diabetes prevention, or assist diabetics in better managing their disease. Don’t be surprised to see a diabetic person armed with a food scanner (like TellSpec or DietSensor) assessing his restaurant dish and dessert against his nutrigenomic profile

Non-Invasive Monitoring

The “holy grail” of diabetes monitoring is non-invasive glucose monitoring that can end pricking fingers for testing several times a day. There are several approaches being developed; broadly, these could be categorized based on where monitoring occurs–eyes (tear drop), fingertip, earlobe and saliva. Apart from big names like Google and Novartis involved in making such monitoring products a reality, there are also smaller players like Medella Health, LighTouch Medical and Quick LLC. Approaches include contact lenses, passing light (visible, infrared or other) through the skin to detect glucose and even salivary assessments. So the next time you are talking to a diabetic person and their contact lens turns a bright color (an indicator for hypoglycemia), get them a chocolate pronto. They will thank you!

Background Therapy

Of course, a potential “cure” for diabetes is replacing pancreatic β cells with stem cell-derived, lab-grown cells. But the current focus of the industry is the artificial pancreas–although we have Medtronic’s MiniMed 670G as the first of this category, we are likely to see many more advances in this area. Competitors like BigFoot Biomedical, Dexcom and Animas Corporation are also developing similar systems. What these essentially mean is freedom from daily monitoring glucose levels, guesstimating appropriate insulin dosages and injecting them. Another advance that will change the field is being developed by Sensulin and other major pharma companies like Eli Lilly–glucose-responsive, once-a-day insulin that could potentially replace basal and prandial insulin. While this insulin still would be taken once a day through the same insulin pens or other delivery devices, the release of insulin in the body would be controlled by blood glucose levels alone, controlling these levels far better than regular insulin delivery. Overall, diabetics would now be able to live worry-free–either injecting insulin only once a day, or simply letting the artificial pancreas system take over completely, improving the overall quality of life. Your diabetic friend might just stop carrying her glucometer, test strips, lancets, insulin pen and chocolates (or maybe not chocolates).

Analytics And Artificial Intelligence

A future diabetic person will have their genomic information incorporated in to their diabetes management regimen. Big Data analytics will play a very important role in informing the patient (not the caregiver!) what they should eat, how much they should exercise and how to manage the disease–in real time. An artificially intelligent interface will “communicate” with the user. For example, the a distant-future system might tell the patient (based on her past history, genetic predisposition and today’s diet and activity levels): “If you have that particular dessert now, it will cause your glucose levels to shoot up, necessitating immediately performing activities like jogging to burn approximately 150 calories or an insulin injection of 0.5 units. Please select your choice–jogging or automatic insulin delivery” (numbers are hypothetical).

Does this mean now is the best time for diabetics? We are definitely along the way to finding a cure for this disease, but until then, advances in technology will surely make the life of a diabetic person much easier.

Are you a diabetes patient advocate or an entrepreneur? We would love to hear your opinions on what you think will be the future of diabetes care.

This article was written with contributions from Siddharth Shah, Research Analyst and Venkat Rajan, Global Director, both from the Visionary Health program of Frost & Sullivan’s Transformation Health practice.

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Do You Live in a Bubble?
5 Lessons from the 2016 Presidential Election

Do You Live in a Bubble? <br/>5 Lessons from the 2016 Presidential Election | Innovating in an Age of Personalization | Scoop.it

Published on November 9, 2016
Russell Walker
Clinical Professor, Kellogg School of Management, Northwestern University

The 2016 Presidential election offers many valuable lessons. It shows that for many Americans, especially those in urban areas, there is a bubble. Living in a bubble is a challenge for sound decision-making and leadership.

The lessons embedded in the surprising results of this election remind me of leadership, decision-making, and even big data analysis.

The majority of polls predicted that Clinton would win. Indeed, even the published probability of Clinton winning was over 90% on the eve of the election. How can so many polls and predictors be so wrong? The triumph of big data failed. Or did it? A careful review of the polls tracked by Real Clear Politics shows that the LA Times and the IBD/TIPP polls consistently showed Trump ahead or tied. Virtually, every other poll predicted a Clinton win.

The lessons are important:

1) Truth is Not Revealed by Committee: Asking many people with the same perspective only amplifies the errors that they have and you have. Clearly, the polls that predicted Clinton, especially the on-line polls, were subject to this error.

Key Take Away: Seek out experts, not averages or committees. Even Michael Moore predicted Trump would win Michigan. Remember the tragic result of the NASA launch team ignoring the input of the experts on the safety of the Challenger launch. The launch commander ignored an expert’s opinion.

2) Seek Out Disconfirming Information: Building analytical models that are influenced by confirmation bias and further do not search for disconfirming information lead to bad results – be it with big data or small data. More attention to the LA Times and IBD/TIPP polls would have made the results less surprising. Similarly, as some people saw the US housing crash coming, there is enormous value in seeking information that disconfirms your perspective and hypothesis.

Key Take Away: Don’t seek why you are right, but rather examine how you might be wrong. It is rigorous and leads to better decision-making, greater open-mindedness, and better insights.

3) Know Your Customer: Trump got closer to his customer and understood their issues and concerns. CEOs and business leaders have similar challenges. Get close to your customer and know what they want, think, and believe (about your product, your firm, and you).

Key Take Away: Rarely does your customer (or employee or constituent) tell you what is wrong. It takes work and deliberate effort to learn from them. Remove the language, “I think” and replace it with “What do you think?” Leaders listen and then react. The least effective executive seminars I have led are those where the CEO or leader tells the team what to do or think. It stymies the flow of information and creativity.

4) Challenge Your Perspective (Always): The best ideas and theories are those developed by defeating the counter-hypothesis. Proving yourself right is not as valuable as examining other theories as alternatives. Surprises, insights, and great discoveries come from challenging prevailing wisdom, ideas, and perspectives. Challenge your own ideas!

Key Take Away: Learning requires asking questions. Asking hard questions requires examining what you believe and why it might be wrong. Humble yourself and re-examine your ideas; it will make you a better decision maker.

5) Get Out of the Bubble: Staying in HQ behind your computer screen is easy. Walking the floor, meeting your workers, getting to know them in person, and getting to know your customers is work. For political and business leaders, it is easy to remain in a safe bubble and to support yourself with people that think just like you. It is a commitment to leadership and discovery to move outside of the bubble. Do it every day! Consider ideas with an open mind and look for insights that reveal surprises and discoveries in data and daily life.

Key Take Way: You only get out of the bubble if you want to do so. Successful leaders get out of the bubble. A simple test can help. Do you know the people that make your food or clean your office? Do you acknowledge them? Do you thank them? If not, there is a first and easy step out of the bubble. Acknowledge them, thank them, and listen to them.

Leaders are identifiable to everyone in their organization. It is hard for leaders to get to know every employee or customer. However, if you do it with effort, you will earn great respect and admiration from those that already look to you for guidance.

There is a whole world outside of your bubble. Go find it!

About Russell Walker, Ph.D.

Professor Russell Walker helps companies develop strategies to manage risk and harness value through analytics and Big Data. He is Clinical Professor of Managerial Economics and Decision Sciences at the Kellogg School of Management of Northwestern University. He has advised the World Bank, the Department of State, SEC, IFC, multiple US Senators, and a host of corporations.

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Interesting perspective on why the election predictions of the majority were wrong

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5 Forecasts For The Future

5 Forecasts For The Future | Innovating in an Age of Personalization | Scoop.it

Every now and then, it’s a fun and healthy challenge to think distantly. Sure, we already expect self-driving cars, wearable hardware, a connected home, and augmented reality. But where does the foreseeable future take us next? I’m talking more Black Mirror than investor thesis. What new problems will we be struggling with? What will kill us? What will connect us? While solutions change, some questions will always remain. If only to stimulate discussion among friends, here are a few ideas on my mind these days:

  1. Social media will become passive.
  2. Our (augmented) reality will be a land grab, and always be under attack from brands.
  3. Interfaces will compete with the technology underneath.
  4. Autonomous vehicles in cities will become a public utility.
  5. We will transcend “tragedy of the commons” with technology that aligns self-interests with community benefits.

Allow me to explain, as well as share some implications for each:

(1) Social media will become passive.

The concept of actively “posting” or “sharing” will be frowned upon and entirely replaced by a passive stream of your life’s experiences, whereabouts, and media consumption. Imagine a 24 hour channel of you that is authentic, aways live (or automatically programmed), and always accessible to your friends (or if you’re born in the age of transparency (post year 2000), accessible to anyone). Any effort to actively post something will be seen as “manual editing” and will be perceived negatively unless it is an artistic statement. Quality will be community and algorithmically-determined, surfacing the highlights of your experience in a way that is automatic and thus deemed more authentic. Implications?

  • So many social products and new forms of advertising will emerge to accommodate the era of passive social. Viral growth of new products and media will happen more naturally based on how many people are tuning into you. Simply, whatever you’re doing or consuming is what other people will discover.
  • Typical forms of paid user acquisition will become obsolete, replaced by product placement and “experience placement.” The prices you pay for products and services in your life will be offset by the exposure you bring. The bigger your network (and the better your “CFV” (Conversion From Viewers, a measure of how actionable your content is for those that follow you), the less your life will cost!
  • I am struck by the idea of trusting automation over what someone does manually. It’s the evolution of how we are drawn to inferior photos on Snapchat in a more primal way than carefully posed and edited photos on Instagram. The objectivity of algorithms over the subjectivity of human tendencies may cause us to “trust” algorithms more. We value an unedited photo and “collective intelligence” for the same reasons — they make us less paranoid that we’re being lied to (and thus help us believe and relate). With the loss of “manual editing,” social media will become a more effective form of empathy and truth.
  • Given the passivity of social networks, their relevance will rely on context. Social networks will pop into and out of our life depending on where we are, what we’re doing, and what we want. Visiting Spain for Christmas? Expect to have “contextual ephemeral social networks” (sorry) that enable you to navigate, connect and plan activities with other friends in Spain during the week you are there. When the trip ends, the network will dissapear.
(2) Our (augmented) reality will be a land grab, and always be under attack from brands.

Personally, I’m more bullish about augmented reality than virtual reality. The augmented layer opens up a ton of exciting (and horrifying) ways for brands, friends, governments, and artists to get in your line of sight based on where you are and when you’re there. Quite quickly, I see it getting out of hand. While the physical world has practical limitations that keep billboards at bay, the augmented world won’t. To get a feel for how bad this could be, check out this video. Implications?

  • Perhaps “ad blockers” will be the most important apps in the era of augmented (and virtual) reality? Whatever platform and device you use to augment your reality, advertising is the most likely business model. If the increasing number of paid search results in a typical Google search today is any indication, your augmented reality will constantly be under siege. To fight it, you’ll install intelligent or crowd-sourced filtering software that will override unwelcome parts of your augmented reality experience.
  • Perhaps the major platforms for augmented reality will designate certain zones as commercial or non-commercial? Zoning has worked well enough for governments. I can see your home — and all other private property — being designated as “non-commerical,” and thus off-limits to advertising. If Snapchat’s filter submission and approval system is any indication, augmented reality will be an unprecedented land grab akin to the domain-name craze in the nineties.
(3) Interfaces will compete with the technology underneath.

A few years ago I shared my excitement for the “interface layer: where design commoditizes tech,” and how superior interfaces will aggregate multiple services underneath. In the future, we will want fewer interfaces in our lives — and these interfaces will integrate all sorts of utilities into a simple flow. Examples?

  • Modern interfaces will revolutionize how we plan our day by aggregating the disparate services we wish to schedule, from rides and food to babysitters, into a single interface. The underlying providers of such services will compete for presence in the interface, based on price and revenue share with the interface itself.
  • The interfaces we use at work will become customizable. People will be able to choose and customize the “skin” for the tools they use in the enterprise. Consumerization of enterprise technology will bring us to a place where productivity and employee morale is meaningfully higher when interfaces are user-friendly and custom.
  • Interfaces will change the way we get customer service from companies and governments, negating the need to interact directly with cable companies, utilities, or government websites. The interface companies will monetize by proactively suggesting optimizations to your plans (saving you money) — or offering premium ways of saving time. These modern interfaces will empower customers and citizens by stripping away the benefits of friction enjoyed by providers (companies and governments rely on how damn difficult it is for us to do certain things!).
  • And for the left-field prediction, an entirely new mobile operating system will emerge that is location-centric rather than app-centric. In a modern world where we want fewer interfaces with interconnected functionality, it is time to rethink mobile. Functionality should be visible and then hidden based on where and when we are, rather than what apps we installed. In fact, apps shouldn’t exist. Whatever we need (whether we know it or not) should be at our fingertips, and (no surprise) our voice command should summon anything we want.

The biggest implication of the emerging interface layer is ruthless competition to be the default. The utility-based providers underneath these interfaces will be pressed on margins and will compete to be the default provider in the interfaces we use on a daily basis. To survive, the providers will focus more on optimizing the cost-efficiency of their services rather than spending money building their brand and relationships with customers.

(4) Autonomous vehicles in cities will become a public utility.

When (not if) all transportation within a city’s limits becomes automated and increasingly regulated, cities will rethink infrastructure and public transportation. Some cities already see Uber as a solution to “last mile” transportation quandaries. Perhaps planning and scheduling software for public transportation becomes more important than the commoditized technology in the vehicles themselves. Perhaps transportation will join the ranks of water and electricity? Implications?

  • A whole series of questions emerge: Will on-demand and autonomous transportation data become a public asset? At what point will mass transit adopt autonomous vehicles and become completely automated? Will the future of mass transit be operated by governments or private companies? Will companies that create technology to plan and schedule mass transit for government (like Remix Software) commoditize the tech that performs the transportation? As an Uber investor, i’m mixed about this, but I believe Uber’s dataset alongside its advances in autonomous technology will be its moat.
  • On the topic of autonomous vehicles, I was thinking the other day about the consequences of preset routes and what would happen when vehicles “disobey.” Call it a CGW — “car gone wild” — when a vehicle, with or without passengers onboard, begins to roam either out of bounds or off the set schedule or route (attention Black Mirror writers!). Perhaps the vehicle was hacked? Or perhaps conflicting instructions around traffic conditions or passenger destinations, coupled with artificial intelligence, take the vehicle on an unexpected course. Ultimately, government safety officers must be equipped to control anything that runs automatically.
(5) We will transcend “tragedy of the commons” with technology that aligns self-interests with community benefits.

The “tragedy of the commons” is the unfortunate human tendency to take advantage of shared-resources out of self-interest, thus depleting the benefits everyone could enjoy through collective action. Back in the day, farmers would take their livestock and selfishly deplete the town commons before returning to their own lands (which they would sustain thoughtfully). If everyone just agreed to graze the commons sparingly, it would last and benefit everyone. But self-interests obstruct the common good. People who abuse insurance spike prices for the rest of us. People who cheat taxes cause the rest of us to pay more. Through increased transparency, networks, and artificial intelligence, technology will enable us to collectively regulate and align our interests. Implications?

  • Any product or service that bakes in a cost for “bad actors” can be transformed. The way we buy insurance, get mortgages, and pay taxes may change once we can unbundle the costs and align our interests with larger groups of likeminded people. Would you pledge to eat healthier to lower your health insurance premiums? Would you pledge to drive safely and disclose the speed of your driving for cheaper insurance? As technology permeates our everyday actions, you’ll have the option of surrendering a degree of self-interest for lower prices.
  • Social networks will reduce the frequency of abuse and trolling through new tools powered by human curation and artificial intelligence that diminish the reach of bad actors. If you troll or fail to participate in the collective efforts to protect the platform, your voice will be heard less. To be anonymous and still be a steward of the medium is the future of freedom of speech.
  • Your reputation will become portable, recognized and rewarded beyond the brands and governments from whom you earned it. If you have a history of over-using customer service or being an outlier on the cost curve, you may not be eligible for better pricing.
  • Collective bargaining networks will become the default source for certain insurance and financial products. Bartering and “favor based” economies will become more mainstream as equality can be tracked.
What to do with forecasts?

Forecasts for the future are not an investment thesis. The future won’t happen until the present is ready for it. One of the things I’ve learned from the partners at Benchmark is just how important it is to invest with a tremendous insight into the present. But for a seed investor, product leader, or entrepreneur, forecasts for the future add a new lens to pattern recognition. Aside from what I look for in a founder, team, and product, I try to determine whether the future is a headwind or a tailwind for a company. Is the team attempting to defy a likely outcome or make it happen in a better way?

If nothing more, considering the future exercises our imagination and sparks conversation and debate with people you can learn from. Bring it.

Linda Holroyd's insight:

5 Forecasts: Social media, augmented reality, UIs, autonomous vehicles a 'tragedy of commons'

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From Babies to Billions: The Honest Company Trajectory

From Babies to Billions: The Honest Company Trajectory | Innovating in an Age of Personalization | Scoop.it
When I read the other day that the Honest Company, founded in 2011, was likely to be acquired by a large, established consumer packaged goods (CPG) company for nearly $2 billion, I initially was surprised. As a fan of the brand and its creator, Jessica Alba, my wife was not. After all, she pointed out, Alba started the company based on what she herself had experienced as a new mother: the need for a trusted supplier of safe, eco-friendly products for babies.

The more I thought about it, the more I realized that it made perfect sense for a large CPG company to make such an investment. Consider that Amazon is encroaching further and further into territory traditionally controlled by the CPG-retail ecosystem. According to Yahoo Finance, “Amazon now has a warehouse or delivery station within 20 miles of 44% of the U.S. population.” Amazon is also expanding its private-label business, now offering everything from food to diapers.

Yes, diapers. Which brings us back to Honest Company – a consumer-driven business built on an e-commerce-first model. As Alba describes the epiphany that led her to start the company, “[brick-and-mortar] stores should be for perishables, not products.” As traditional CPG-retail ecosystem players seek to keep pace with the rapidly changing marketplace, many will seek to acquire built-on-Web companies. Think of Walmart buying Jet for $3 billion, or Unilever picking up Dollar Shave Club for $1 billion.

It’s not only about acquiring a growing and trusted brand with a large base of repeat customers. It’s also a way of fending off niche players – Dollar Shave Club is a good example – that win customers based on an innovative service model and are then positioned to expand into other products and audiences. Even more important, legacy CPG companies seek to absorb e-commerce-first businesses in hopes that their success can be replicated throughout the enterprise.

Whoever acquires Honest Company will need to ensure, on the one hand, that they don’t disrupt a business model that is clearly working. On the other, they need to think holistically about their overall enterprise and how to bring the rest of their brands more directly to consumers. CPG companies that embrace this challenge will be well positioned in the years to come.
Linda Holroyd's insight:

It's about service and excellence. It's about brand. WTG Honest Company!

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Transforming operations management for a digital world | McKinsey & Company

Transforming operations management for a digital world | McKinsey & Company | Innovating in an Age of Personalization | Scoop.it

McKinsey

Transforming operations management for a digital world

October 2016,

By Albert Bollard, Alex Singla, Rohit Sood, and Jasper van Ouwerkerk

 

When combined, digital innovation and operations-management discipline boost organizations’ performance higher, faster, and to greater scale than has previously been possible.In every industry, customers’ digital expectations are rising, both directly for digital products and services and indirectly for the speed, accuracy, productivity, and convenience that digital makes possible. But the promise of digital raises new questions for the role of operations management—questions that are particularly important given the significant time, resources, and leadership attention that organizations have already devoted to improving how they manage their operations.At the extremes, it can sound as if digitization is such a break from prior experience that little of this history will help. Some executives have asked us point blank: “If so much of what we do today is going to be automated—if straight-through processing takes over our operations, for example—what will be left to manage?” The answer, we believe, is “quite a lot."

More digital, more human

Digital capabilities are indeed quite new. But even as organizations balance lower investment in traditional operations against greater investment in digital, the need for operations management will hardly disappear. In fact, we believe the need will be more profound than ever, but for a type of operations management that offers not only stability—which 20th-century management culture provided in spades—but also the agility and responsiveness that digital demands.

The reasons we believe this are simple. First, at least for the next few years, to fully exploit digital capabilities most organizations will continue to depend on people. Early data suggest that human skills are actually becoming more critical in the digital world, not less. As tasks are automated, they tend to become commoditized; a “cutting edge” technology such as smartphone submission of insurance claims quickly becomes almost ubiquitous. In many contexts, therefore, competitive advantage is likely to depend even more on human capacity: on providing thoughtful advice to an investor saving for retirement or calm guidance to an insurance customer after an accident.

That leads us to our second reason for focusing on this type of operations management: building people’s capabilities. Once limited to repetitive tasks, machines are increasingly capable of complex activities, such as allocating work or even developing algorithms for mathematical modeling. As technologies such as machine learning provide ever more personalization, the role of the human will change, requiring new skills. A claims adjuster may start by using software to supplement her judgments, then help add new features to the software, and eventually may find ways to make that software more predictive and easier to use.

Acquiring new talents such as these is hard enough at the individual level. Multiplied across an organization it becomes exponentially more difficult, requiring constant cycles of experimentation, testing, and learning anew—a commitment that only the most resilient operations-management systems can support.Seizing the digital momentAnd if digital needs operations management, we believe it’s equally true that operations management needs digital. Digital advances are already making the management of operations more effective. Continually updated dashboards let leaders adjust people’s workloads instantly, while automated data analysis frees managers to spend more time with their teams.

The biggest breakthroughs, however, come from the biggest commitment: to embrace digital innovation and operations-management discipline at the same time. That’s how a few early leaders are becoming better performers faster than they ever thought possible. At a large North American property-and-casualty insurer, for example, a revamped digital channel has reduced call-center demand by 30 percent in less than a year, while improved management of the call-center teams has reduced workloads an additional 25 percent.

Achieving these outcomes requires organizations to tackle four major shifts.

Digital and analog, reinforcing each other

Digitization can be dangerous if it eliminates opportunities for productive human (or “analog”) intervention. The goal instead should be to find out where digital and analog can each contribute most.That was the challenge for a B2B data-services provider, whose customized reports were an essential part of its white-glove business model. Rather than simply abandon digitization, however, the company enlisted both customers and frontline employees to determine which reports could be turned into automated products that customers could generate at will.Working quickly via agile “sprints,” developers tested products with the front line, which was charged with teaching customers how to use the automated versions and gathering feedback on how they worked. The ongoing dialogue among customers, frontline employees, and the developer team now means the company can quickly develop and test almost any automated report, and successfully roll it out in record time.

Driving digital, enterprise-wide

Developing new digital products is only the beginning, as a global bank found when it launched an online portal. Most customers kept to their branch-banking habits—even for simple transactions and purchases that the portal could handle much more quickly and cheaply.

Building the portal wasn’t enough, nor was training branch associates to show customers how to use it. The whole bank needed to reorient its activities to showcase and sustain digital. That meant modifying roles for everyone from tellers to investment advisers, with new communications to anticipate people’s concerns during the transition and explain how customer service was evolving. New feedback mechanisms now ensure that developers hear when customers tell branch staff that the app doesn’t read their checks properly.Within the first few months, use of the new portal increased 70 percent, while reductions in costly manual processing means bringing new customers on board is now 60 percent faster. And throughout the changes, employee engagement has actually improved.

Realigning from the customer back

The next shift redesigns internal roles so that they support the way customers work with the organization. That was the lesson a major European asset manager learned as it set out on a digital redesign of its complex, manual processes for accepting payments and for payouts on maturity. The entire organization consisted of small silos based on individual steps in each process, such as document review or payment processing—with no real correlation to what customers wanted to accomplish. The resulting mismatch wasted time and effort for customers, associates, and managers alike.

The company saw that to digitize successfully, it would have to rethink its structure so that customers could easily move through each phase of fulfilling a basic need: for instance, “I’ve retired and want my annuity to start paying out.” The critical change was to assign a single person to redesign each “customer journey,” with responsibility not only for overseeing its digital elements but also for working hand in glove with operations managers to ensure the entire journey worked seamlessly. The resulting reconfiguration of the organization and operations-management systems reduced handoffs by more than 90 percent and cycle times by more than half, effectively doubling total capacity.

Making better leaders through digital

The final shift is the furthest reaching: digital’s speed requires leaders and managers to develop much stronger day-to-day skills in working with their teams. Too often, even substantial behavior changes don’t last. That’s when digital actually becomes part of the solution.About two years after a top-to-bottom transformation, cracks began to show at a large North American property-and-casualty insurer. Competitors began to catch up as associate performance slipped. Managers and leaders reported high levels of stress and turnover.

Speed and scale: Unlocking digital value in customer journeys

A detailed assessment found that the new practices leaders had adopted—the cycle of daily huddles, problem-solving sessions, and check-ins to confirm processes were working—were losing their punch. Leaders were paying too little attention to the quality of these interactions, which were becoming ritualized. Their people responded by investing less as well.

Digital provided a way for leaders to recommit.

An online portal now provides a central view of the leadership activities of managers at all levels. Master calendars let leaders prioritize their on-the-ground work with their teams over other interruptions. Redefined targets for each management tier are now measured on a daily basis. The resulting transparency has already increased engagement among managers, while raising retention rates for frontline associates.

Organizations investing in human and digital capabilities can start by asking themselves several critical questions:

  • Do we really understand how customers interact with us now, and how they want to in the future?
  • How can we give customers the experience they want, no matter which digital and human channels they use?
  • How can we speed our metabolism so we can uncover new opportunities for better performance?
  • Can our culture become flexible enough for us to collaborate effectively with our customers through constant change?

Capturing the digital opportunity will require even greater operations-management discipline. But digital also makes this discipline easier to sustain. Adding the two together creates a powerful combination.

 

About the author(s)
Albert Bollardis an associate partner in McKinsey’s New York office,Alex Singlais a senior partner in the Chicago office,Rohit Soodis a partner in the Toronto office, andJasper van Ouwerkerkis a senior partner in the Amsterdam office.

The authors wish to thank Chandana Asif, Joao Dias, Kingsley Gifford, David Hamilton, David Jacquemont, Somesh Khanna, David Taylor, and Alex Yeo for their contributions to this article.

Linda Holroyd
CEO, FountainBlue
Linda.Holroyd@FountainBlue.biz
650-395-8177 voice
650-646-1117 text and cell
650-209-7677 Skype, linda.holroyd-fountainblue
Availability: http://fountainblue.youcanbook.me 

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Combine digital innovation and operations management

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3 timeless ingredients to successful modern marketing strategy

3 timeless ingredients to successful modern marketing strategy | Innovating in an Age of Personalization | Scoop.it
 

Recently, while vacationing in Tuscany, we hired a driver and we went wine tasting. Our first stop was the most famous winemaker Antinori Family. Gorgeous, newly designed winery, but from the moment we walked in, the vibe was unwelcoming. The receptionist did not greet us, the wine pourers in the tasting room had total attitude and were not interested in either engaging with us nor describing the wines we were tasting. Besides that, each small tasting was expensive! Disappointed, we departed with no wine in hand and hurried on to visit a few other good wineries in the picturesque area.

Our most memorable stop by far was at the Tenuta Tociano winery in San Gimignano. To our pleasant surprise, the owner Pierluigi greeted us at the gate with an umbrella while wearing an apron and boots (it was raining heavily). He introduced himself, made sure he knew our names, where we were from and then proceeded to escort us to a small table which was loaded with empty wine glasses and cheese/salami plate for the tasting. ( I later found out that he makes sure he greets or speaks with everyone that visits his winery.) Pierluigi gave us the background on his wine and all the awards they won from Wine Spectator. More importantly, however, he was also charming enough to tell us all that awards don't matter because wine preference is a matter of taste and he did not want us to feel compelled in any way to prefer one wine more than the other due to its "high" ratings.

He then introduced his nephew, who spent the next few minutes entertaining and educating us with some tasting techniques. He had us all swishing the wine around and practically gargling on it. Interesting enough, everyone in the room was laughing and smiling and feeling awkward together. On the table, they had a paper placemat and a pen to identify which wines you preferred and cleverly, on the back of the placemat, a handy order form to purchase the wines we had just tasted, as well as a spot to put your contact info to join their exclusive online community and hear about their stateside wine tasting events.

As a veteran marketer and sales person, I totally appreciated the marketing and true salesmanship of this small winery. These were my takeaways that apply to any business, whether you are a 700-year-old winery, or any company doing business today.

1- Greetings Matter (first impressions)! You can have the slickest website or coolest office ever, but you must find a way to also make people feel welcome, whether it's in your place of business or your website. Do not be indifferent!

2- Be Generous. Educate and give people information that pertains your industry for free. Much like the winemakers' nephew who spent time teaching us how to properly taste wine from awkwardly sticking your nose in the glass to swirling in our mouths, he taught us about the differences in Chianti grapes and educated us on the difference between a Chianti, Reserva or a super Tuscan. What is your place of business doing to educate or give information or content for free? this builds loyalty immediately. They were extremely generous in their pouring, which built instant loyalty and yes a wine buzz.

3-Create a Community: Figure out a way to make your prospect be a part of your community. During our visit, we were encouraged to sign up and be part of a Tuscan wine lovers community with wine articles, videos and discounted wine with free shipping to the US. There are thousands of wineries in the Chianti region but this winery figured out a way to get us to be an advocate, a member and potentially a long time shopper. One of my favorite go-to resources for great tips on building and nurturing a successful community to grow your business (www.jeffbullas.com) .

People interactions matter. Honestly, I bought Chianti wine on our trip based on how sellers engaged with me during the wine tasting (yeah this proves I am not a wine connoisseur.) It's similar to any business, the product itself must be good, but the sales interactions and the customer service portion of the business are vitally important. It isn't sufficient to have just slick packaging or a gorgeous website, your people interactions and how your company makes prospects and customers feel matter more that you realize. Scott McKain's book Collapse of Distinction: has some great practical advice and some entertaining examples of how much customer service matters.

We now live in an attention-based economy. When we are lucky enough to have our customers/prospects attention that's when need to be authentic and engaged. So pour that glass of chianti and ask yourself what am I doing to make my customers feel appreciated and feel satisfied that they are getting good value from your products and services.

Linda Holroyd's insight:

Greetings Matter, Be Generous, Build Community

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New insights for new growth: What it takes to understand your customers today | McKinsey & Company

New insights for new growth: What it takes to understand your customers today | McKinsey & Company | Innovating in an Age of Personalization | Scoop.it

New insights for new growth: What it takes to understand your customers today
By Jonathan Gordon, Volker Grüntges, Vicki Smith, and Yvonne Staack

Companies that know how and when to use the wide array of research tools available today have a big competitive advantage in generating insights that lead to new organic growth.

What do Unilever, Philips, Amazon, and Netflix have in common? At first sight, nothing much. They compete in very different industries, and while Unilever and Philips are firmly rooted in the 19th century, Amazon and Netflix are unthinkable without the Internet.

What they have in common, though, is that they drive growth by meeting consumer needs better than their competitors do. Core to this consumer focus is a strong belief in insights, and in the active use of a diverse mix of insight tools—new and old, qualitative and quantitative, digital and analog—to get better answers.

Unilever, for example, has successfully engaged in consumer cocreation to launch TRESemmé, a fast-growing dry-shampoo brand that is now one of the best-selling mass hair-care products in the US. Philips has achieved major market-share gains in highly contested home-appliance categories through city-level growth analysis. Thanks to its data-driven recommendation engine, Amazon attributes more than one third of its revenue to cross-selling,1 and Netflix saw its subscribers triple between 2011 and 2015, largely because of its ability to develop hit shows such as House of Cards, based on advanced analysis of subscribers’ past viewing behavior.2
Developing a better understanding of customers is increasingly a strategic necessity, because fast-moving markets, new technologies, and new business models are changing what customers want and how they shop. Yet many companies still spend the bulk of their research budget on traditional techniques (e.g., focus groups, interviews, and surveys), or treat insights as an afterthought, which leaves them with a limited and often incorrect view of what customers want. That is a recipe for obsolescence in today’s economy.

While there is a vast array of marketing analytics and insights capabilities, this article focuses on those tools, techniques, and approaches that specifically lead to new commercial growth, i.e., new products, services, or markets. (An insight is defined as the discovery of a fundamental consumer need that companies can use to create value for the customer and the business.)

A new approach to insights

Getting to a level of understanding about what customers really want requires the ability to understand what motivates consumers, as well as how they shop and make decisions. Based on our work with leading companies and innovative insights vendors, as well as proprietary research, we have identified five research approaches that are best suited for generating the kinds of insights that lead to new growth opportunities.

1. Observe consumers ‘in the field’

Observing consumers as they shop or use a product is often deeply revealing about their behaviors and motivations. This kind of research is closely tied to behavioral economics, a school of thought that seeks to understand the way consumers actually make decisions. It’s also a pillar of design thinking, which puts the customer at the center of a system of interactions with the brand.
John Kearon, the founder of UK-based agency BrainJuicer, a two-time winner of Esomar’s Best Methodology award and a leading provider of observational and ethnographic research, believes that “anything based on observation of what people really do is massively more accurate than what people say they do—or the reasons they give for saying it.”3
One international food company, for example, was seeking to introduce European markets to a new product: a dip that could also be spread on bread. The CEO believed that countries like France or Italy would be ideal pilot markets, given the countries’ obsession with good food. To test this hypothesis, a team of ethnographic researchers conducted “dine-alongs,” where they joined subjects in five countries both in restaurants and in private homes.
Through observation and casual conversation, the team found that consumers in two other countries were actually more open than those in France and Italy to international cuisines and new flavors, and would be more receptive to the company’s product. Based on this research, the company changed their market-entry priorities and increased their launch targets to more than a 10 percent share in the category, which unlocked additional sales of more than $10 million annually.

2. Digitize the daily diary
While consumer diaries—literally a written record someone creates to track their daily decisions and purchases—have been around for some time, digital advances and mobile devices have made this kind of research much more versatile, accurate, and accessible. Typical applications include video recording, photographs, and blog posting of food or beverage consumption, media usage, patient journeys, or compliance with medical prescriptions and therapies. What’s more, the results are available within days, if not in real time, rather than after weeks or months.
In a pioneering case, a maker of pharmaceuticals and medical devices used digital diaries to better understand how arthritis patients self-administered injections several times a day. Participating patients used mobile devices to film themselves performing these tasks. Additionally, researchers observed patients at home. The research revealed that some patients skip injections because of the discomfort and pain they cause or the anxiety patients feel. Not all patients, however, admit such qualms to their physicians, who then will frequently prescribe higher dosages of pain medication. A member of the observation team said, “Until now, we have never seen how patients live in their day-to-day lives.”
To address this issue and increase patients’ compliance with the prescription regimen, the company is working on a needle-free drug delivery system as well as other ideas for new products and services that would make the life of arthritis patients a lot easier. The total opportunity has been valued at almost $100 million in incremental revenue.

3. Use advanced analytics to get much more granular insights
Today, the mass of data about consumer behavior allows marketers to get past broad and often deceptive averages to dive into much more granular levels of insight that can unlock new opportunities. Those who invest in big data and advanced analytics often achieve up to 10 percent sales growth, up to 5 percent higher return on sales, and a margin uplift of 1 to 2 percent.4
A next-generation car-rental company with ambitious growth plans, for example, used advanced data-mining techniques to target new customers more effectively. It started by analyzing its database of driver profiles and trips to identify distinct groups of customer archetypes. The team then pulled in external data from a variety of sources to build a scoring model to identify drivers in a given city or neighborhood who fit one of the ten archetypes the business had developed. They then tailored offers and communications to each of those segments. Within one year, the company grew its customer base by more than 10 percent and increased its revenues by almost 20 percent.
Philips US applied advanced analytics to simulate the market potential for various combinations of price tiers, channels, and product portfolios—not at a country or even regional level, but city by city in dynamic markets.
With that information in hand, the marketing team created offers that targeted the most promising segments in each city. The market share in relevant product categories increased from 15 percent to 19 percent, and the EBIT for the company’s consumer lifestyle division jumped from 8 percent to 14 percent. Says Pieter Nota, CEO for Philips Consumer Lifestyle: “Based on the global growth analysis, we devised a plan to double revenues over the course of less than a decade without compromising profit margins, partly driven by product innovation in two highly dynamic categories.”


4. Better listening and learning with social media
Social media allows companies to listen in on unfiltered conversations consumers are having about their preferences, experiences, and habits. Many services exist, such as Hyve, Winkle, BrandWatch, Synthesio, or Google Analytics, to unlock insights from analysis of online discussions, consumer reviews, topical blogs, and keyword-driven trend analysis. Active listening enables companies to detect relevant buzz early on (be it positive, neutral, or negative), react swiftly, and unearth clues that can lead to innovations.
Beiersdorf, the personal-care company and owner of the Nivea brand, tapped into an ongoing social-media conversation to develop a completely new product line. Using Hyve’s Netnography Insights software, the company found that consumers were complaining in multiple online forums such as beautyjunkies.de that deodorant leaves stains on textiles.5 Further analysis revealed that the issue was widely discussed and that users shared advice on how to remove various types of stains.
In response, the company developed a new type of deodorant that prevented yellow stains on white clothes. To test the concept, Beiersdorf turned to almost 2,000 dedicated followers of the Nivea brand. It turned out that consumers were not only concerned about yellow stains on white clothes but also about white stains on dark-colored clothes. Beiersdorf refined the concept and marketed it as “Nivea invisible for black & white,” stressing that “white stays white and black stays black.”
Ansgar Hölscher, in charge of consumer insights for the Nivea brand, says, “Thanks to social listening and online consumer cocreation, Nivea Black & White became the most successful product launch for Beiersdorf in ten years.”

5. Cocreate with consumers on digital platforms
Manufacturers of consumer products are inviting their customers to generate new ideas to advance their product development and gather feedback on new products, even before launch. This goes beyond just listening to customer preferences and bringing them into the creative and development process. When done well, cocreation can reduce market-research costs, increase customer loyalty, and develop the products and services that customers want. Leading vendors in this field include CrowdWorx, Innocentive, Synthetron, noo F/X, and Lunar, the award-winning design firm recently acquired by McKinsey.7
Procter & Gamble became a high-profile proponent of this approach when it launched its Connect+Develop program, which aimed to leverage external idea generation for future product development. One of the innovations that originated from this program was the Swiffer range of cleaning products that collectively contribute about a billion dollars in annual sales.8
More recently, Unilever made headlines when it created a new hair-care range, TRESemmé Fresh Start Dry Shampoo, with the help of consumers. It learned that half of US women do not wash their hair every day, even though many of them feel insecure on the days when they don’t.
To learn more, Unilever engaged with women in My Beauty Café, an online community dedicated to hair care and beauty regimens. Community members contributed to every step of product development, from initial ideation and concept refinement to sample testing, packaging, and advertising. Launched in 2010, the new range generated first-year sales of almost $8 million. Subsequently, Unilever’s share of the US mass hair-care market jumped from 9 to almost 16 percent. Today, Fresh Start Dry Shampoo is one of the ten best-selling products in the overall styling category in the US mass market.9
Generating insights is a vital, iterative process. Testing and learning, adding innovative methodologies to your tool kit, and discarding techniques that no longer add value have become core insights disciplines. While reengineering how companies generate insights is crucial to finding new growth, how effective it is relies on an approach that is as dynamic as the market itself.

About the author(s)

Jonathan Gordon is a partner in McKinsey’s New York office, Volker Grüntges is a senior partner in the Munich office, Vicki Smith is a senior expert in the Chicago office, and Yvonne Staack is a senior expert in the Hamburg office.

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Age of the Customer

Age of the Customer | Innovating in an Age of Personalization | Scoop.it

FountainBlue’s September 2 VIP roundtable was on the topic of Embracing the Age of Personalization. Please join us in thanking our gracious hosts at Hitachi. The executives in attendance at this month’s roundtable represented a wide range of industries, roles, functions and company sizes. Therefore, their perspectives on who the customer is, what the customers’ needs are, and how best to address them varied widely. Below is a compilation of their collective thoughts regarding serving the needs of the customer.

  • Companies can’t be everything for everyone. They must have a clear idea of which customers they serve and know how to serve them well, to the point of even anticipating their needs.
  • Serving the customer means also that the business must morph, depending on the needs of the customer. This in general means offering more customized professional services, offering platforms for customizations, offering integrated products and services, etc.,
  • Companies from all industries are better leveraging technology to deliver to the needs of the customer.
  • Companies must adhere to the policies and requirements of the company where their headquarters are located, as well as all the countries where their customers reside. Interactions and services may become quite complex and complicated.
  • Gone are the days when people await the formal glossy newsletter. Real-time, social communications and interactive mobile applications are the best ways to connect with your customers, partners and other stakeholders.
  • The attention span of the customer has gotten really short. Think about offering a 20 second sound bite as a teaser so that they will see a 14 minute video show.

Here are some predictions from our group of execs:

  • Pay-as-you-go software-as-a-service offerings will become an essential requirement for vendors.
  • Customer expectations will continue to rise exponentially and companies will be continuing to scramble to get customers the level of instantaneous, detailed information and analysis they seek.
  • The Intelligence of Things will be focused on solving real-world problems.
  • The role of the channel will become much more important and channel leaders will be chartered with translating the needs of the customer and simplifying and mapping these to solutions which are scalable, leveraging technology.
  • Immersion experiences will become more integral to better understanding the needs of the customer.
  • Ease of use and intuitiveness of flow will be so much more important as customers will have low tolerance for things that are too complex, confusing or complicated to be usable. It’s an Age of Convenience!
  • Configuration platforms will help customers customize to their own needs, following an architecture and structure designed by companies.
  • Companies which offer integrated services from soup to nuts will earn a large and loyal customer base.
  • Companies who can best understand and sell to niche international markets will see better returns. An example is Coke, who has a separate formula for different locations. In fact, most companies already do this, with the BMW3 series being an exception.
  • The same can be said for companies who can successfully connect with specific industry verticals.
  • There will be more money available in general, but it would be offered to fewer companies who truly understand the needs of the customer and seamlessly deliver to those needs.

Resources:

    • 5 Tech Trends Redefining the Customer Experience, Information Week, August 2016 
      • Create Multi-modal instant content, integrating words, images, sounds and video.
      • Think of IoT as devices that provide the next major channel of communication.
      • Leverage data science to deliver differentiated and personalized experiences. 
      • Automate business processes with bots, agents and supervisors.

      • Invest in a modern microservice cloud architecture, where applications are divided into hundreds of independent microservices. 

    • The Age of Personalization: Why Curated Content Is Good For Business, Magnify Team, July 21, 2016
      • Personalization has transformed from a marketing objective to a larger value system that guides how we produce and consume content
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Is Doctorless Care the Future of Healthcare?

Is Doctorless Care the Future of Healthcare? | Innovating in an Age of Personalization | Scoop.it
Reenita Das Contributor

 Is Doctorless Care the Future of Healthcare?

 

Is Healthcare becoming a Data-driven Science led by Clinicians?

The current model of sick care is undeniably unsustainable due to a number of compelling reasons. The aging population burden tops the list. The United Nations’ World Population Aging Report paints a grim picture for the future (see Figure 1) – from 2025 and beyond, the proportion of the elderly population (aged 60 and above) is set to rise, while the share of the working adult population to support this elderly population is expected to remain constant, and even to drop after 2030.

 

Disconnect Between Healthcare Spending and Patient Outcomes

At the same time, the world will continue to grapple with a significant disconnect between health spending and actual patient outcomes. Consider the parameter of life expectancy (see Figure 2, sourced from Our World in Data). As expected, the U.S. is an outlier, but even in other developed nations such as Switzerland and Norway, where health expenditure is higher than the other countries it still does not result in a proportionate increase in life expectancy – some nations actually spend less and yet achieve similar life expectancies.

Figure 2: Life Expectancy vs. Health Expenditure, 1970-2013

Clearly, the present healthcare situation is economically unsustainable. But more importantly, this situation is set to get worse with an increasing aging population that demands more care services and hence higher healthcare expenditure. The importance of wellness and prevention becomes even more critical in this current situation.

Less than 50 percent of Medicine is Evidence Based and Lacks Accuracy and Continuity

Another startling phenomenon is that less than 50% of medicine is evidence based. Studies conducted in oncology have shown that 44% of cancer treatments are later altered during the subsequent course of treatment, highlighting the issue of treatment accuracy gaps. Additionally 20% of diagnostic tests often have to be repeated because of misdiagnosis or false diagnosis which has resulted in inaccurate treatment. Of course the whole paradigm of healthcare is episodic and not continuous which is problematic today especially for the management of chronic diseases.
Explosion of Health Information Availability
An overwhelming amount of medical information is available – more than 25 million published scientific papers are available on Pubmed alone. Obviously, keeping up with developments is practically impossible for any physician.  Not just the healthcare industry, but the very practice of medicine itself is also rapidly changing. Consider the statistics in the diagram below (see Figure 3). With the increasing adoption of digital health technologies such as wearables and smart phone apps, the amount of health information available today (150+ Exabyte’s, with 1 Exabyte being 1,000,000 terabytes of information) is set to grow exponentially.  While the Internet of Things approach to healthcare is bound to generate mounds of data that may seem to exacerbate the situation for doctors. Technologies such as big data analytics and artificial intelligence (AI) are much more powerful and able than the human brain to not just process the large volumes of data, but also to deduce actionable insights for doctors to process and leverage.

Defining the Nexus of Disease Prevention and Treatment with Health Analytics

In a heightened era of population health analytics and continuous and interoperable digital health information, the practice of medicine is becoming more and more of an art form and less of a scientific process. A doctor’s education, clinical experience and intellectual instinct may never be entirely replaced by machine learning or AI software. But, recent health information technological and life sciences advances are making it more and more possible to overcome several current challenges. Physiological function sensors are becoming commoditized, and along with wireless communication technologies, the Internet of medical things approach to care is poised to take hold in the delivery of healthcare in the U.S.

Figure 3: Medical Practice transformation, Select

Providers, who have historically been at the epicenter of all things medicinal, are being asked to engage with an ever growing onslaught of sophisticated and highly functional digital assets. Today’s physicians are being presented with unprecedented real-time access to medical databases in  a cloud environment that hold, literally, the entire history of clinical care, symptomatology, 3D images of tumors, diagnosis and prognosis for every conceivable rash or physical malady known. What modern medicine is to do with this information is not yet clear. Presently, a redefining of the processes and practices of medicine are being explored with amazing innovations driven by an over-arching quest for improved quality outcomes.

Frost & Sullivan

Make no mistake — the paradigm of the traditional doctor patient relationship is shifting from one of 100% reliability on the physician to drive practically every aspect of care to one of virtual and digital collaboration along the continuum of health analytics across the entirety of the care ecosystem. Additionally, millennials prefer to see doctors virtually rather than face to face which will accelerate this trend.

This Darwinian step of medical practice evolution has led to the discovery of a unique opportunity to shift even further the paradigm of medicine to one of understanding the underlying precursors to all forms of disease by statistically performing a multi-variate regression analysis for every dependent variable in our environment. The results of which, when arrayed in rank order by coefficient of correlation (r²) reveals in conjunction with genomic data which specific chronic and degenerative disease threats pose the greatest health dangers for each particular individual. Similarly they also show what the precursors to these diseases will be, where and how to monitor them, and how to prevent the onset of these very same debilitating diagnoses.
Doctorless Care of the Future
The caregiver now becomes more of a lifestyle health tour guide, monitoring one’s journey from birth to death, carefully ensuring one’s metabolic and physiologic road map does not make a dangerous turn resulting in an oncoming genomic triggered fatality. By doing so, we now place patients at the epicenter of the healthcare delivery model and physicians using life science technology will work to prescribe not a cure, but rather a pathway to true whole health by preventing disease. As automation increases the future of healthcare will move towards full autonomy (Figure 4), assisting doctors in their quest for preventing disease.

Figure 4: Maturity levels for automation in healthcare


With a scientific paradigm shift of this magnitude, modern medicine will then fulfill the man-made Triple Aim of healthcare with physicians and patients sharing responsibility for improving the overall health of the population, improving each clinical outcome, and by doing so, reduce the per capita cost of healthcare.
Conclusion
Science, specifically the practice of medicine using the scientific process as a foundation for diagnosing and curing disease is changing within its own intellectual applications. With the recent robust embodiment of health analytics aligning with the life sciences, the practice of medicine is evolving not as a result from an environmental threat or for survival of the fittest species, but rather for the preservation of life for a particular genus species, Homo sapiens.

Health historically has been defined as a living organ with the absence of disease. With a better understanding of the organic and environmental causes of disease through applications of health analytics, physicians can now take calculated actionable steps to prevent disease. With this, society will recognize a need for cultural change to transform the practice and economic model of healthcare delivery. Physicians will be called upon to prescribe a set of lifestyle guidelines unique to each patient to aid them in achieving true health, particular to their individual environment and human genome.

So, while we do not anticipate an ecosystem where we do not need doctors, we do suggest embracing a new era of working with physicians so that we can achieve true health. Because we now recognize the many causes of disease through health analytics and digital health information, health can be now defined as achieving a disease free lifestyle by embracing a culture of optimum health, thus preventing disease.

If you would like more insights on doctorless care, please connect with us! Email rdas@frost.com  and speak to a thought leader in this field.

This article was written with contributions from Patrick Riley, Principal Analyst, Advanced Medical Technologies, and Siddharth Shah, Industry Analyst, Visionary Health program, both part of Frost & Sullivan’s Transformational Health practice.

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Does Blockchain Have A Place In Healthcare?

Does Blockchain Have A Place In Healthcare? | Innovating in an Age of Personalization | Scoop.it

The blockchain concept is still widely misunderstood

Blockchain technology is making headlines everywhere. If you have recently attended any tech events it is highly likely that you came out of them having heard just that bit more about it. Everybody is talking about blockchain--from the President of the United States to the Nigerian government. Despite all the hype, for many people (across different industries) the blockchain concept still seems difficult to grasp, which makes it one of the most misunderstood technologies of 2017. This confusion around blockchain can be attributed both to its contentious origin (Satoshi Nakamoto, the “unknown” who designed Bitcoin and its original reference implementation) and equally to the absence of any standard definition of blockchain technology. Nevertheless, the perceived (if not yet fully understood) disruptive nature of blockchain and its possible impact on businesses across industries makes it crucial first to understand blockchain and then to distinguish the hype from the reality. Today we are going to try to unpack blockchain at a basic level and understand its implications for the healthcare industry.

What is blockchain technology, and how can we separate the hype from reality?

So what is blockchain? If we filter out all the hype and technological jargon, blockchain technology is, at its simplest, a distributed and immutable (write once and read only) record of digital events that is shared peer to peer between different parties (networked database systems). In essence, the fundamental strengths of a blockchain system lie in its data integrity and networked immutability. Having said this, there is always scope to build application layers on top of a blockchain system and enable additional functionalities such as public or private keys, or self-executing mechanics (e.g. smart contracts), but this isn't the core functionality of blockchain technology.

To put it even more simply, let’s flash back to the 1990s, when “internet” was the buzzword. People misunderstood the internet with a tunnel vision around its early use cases (e.g. internet = email, or internet = Web). Similarly, today’s confusion around blockchain technology is not because of its fundamental properties at the protocol layer, but rather because of hype around as-yet-unproven use cases at the application level, which are often mistaken for the integral part of core blockchain technology. For example, today many people commonly identify blockchain with Bitcoin, by far the most commonly known implementation of blockchain technology. But in fact Bitcoin is only the tip of the iceberg of several hundred applications using the blockchain system today.

Translating this analogy for the healthcare industry, the concept of blockchain technology and systems is undoubtedly disruptive, but it will not act as a magic bullet to solve emerging business problems in the fast-changing and highly interconnected digital health ecosystem. Rather, it will be an evolutionary journey for blockchain-based healthcare systems or applications, where trust and governance within a blockchain network or consortium will be the critical success factors for implementation.

Credit: www.healthit.gov; Frost & Sullivan

Blockchain technology

 

What are the most promising blockchain-based use cases for the healthcare industry?

Beyond blockchain technology’s utopian moment in the fintech industry, in the healthcare industry it has just started to inspire both relatively easily achievable and more speculative potential applications. Healthcare authorities, governments and the provider community globally are equally excited about the new possibilities presented by blockchain. Nevertheless, the industry needs to focus on establishing blockchain consortia to foster ecosystem partnerships and create standards or frameworks for future implementation on a large scale across healthcare use cases. The Hyperledger Foundation, an open-source global collaborative effort created to advance cross-industry blockchain technologies, is one great example among many developing small blockchain consortia models in the healthcare space.

Despite the current euphoria, we need to understand and decode the hype cycle for blockchain technology and its realistic healthcare applications. By doing so, we believe that, among several hundred use cases, the five blockchain-based healthcare use cases mentioned below demonstrate more convincing opportunities, albeit at varying degrees of adoption across countries and health systems.

  • Clinical Health Data Exchange and Interoperability: When we talk about blockchain and healthcare, data exchange is typically the first topic to come up. Blockchain-enabled health IT systems that can provide technological solutions to many challenges, including health data interoperability, integrity and security, portable user-owned data and other areas. Most fundamentally, blockchain could enable data exchange systems that are cryptographically secured and irrevocable. This would enable seamless access to historic and real-time patient data, while eliminating the burden and cost of data reconciliation. The recent collaboration between Guardtime, the data-centric security company, and the Estonian eHealth Foundation to secure the health records of one million Estonian citizens using its proprietary Keyless Signature Infrastructure (KSI) is a classic example of blockchain technology. However, considering the complexities around data ownership and governance structure for health data exchange between public and private entities, it would be difficult to replicate the Estonian blockchain-secured health records model globally.
  • Claims Adjudication and Billing Management: An estimated 5-10% of healthcare costs are fraudulent, resulting from excessive billing or billing for non-performed services. For example, in the United States alone, Medicare fraud caused around $30 million in losses in 2016. Blockchain-based systems can provide realistic solutions for minimizing these medical billing-related frauds. By automating the majority of claim adjudication and payment processing activities, blockchain systems could help to eliminate the need for intermediaries and reduce the administrative costs and time for providers and payers. Blockchain could also have significant ramifications for improving some of the huge logistical information tracking hurdles of reliability-centered maintenance (RCM) functions. Recently, Gem Health, a provider of blockchain application platforms for enterprises, has collaborated with Capital One to develop blockchain-based healthcare claims management solutions.
  • Drug Supply Chain Integrity and Provenance: Based on industry estimates, pharmaceutical companies incur an estimated annual loss of $200 billion due to counterfeit drugs globally. About 30% of drugs sold in developing countries are considered to be counterfeits. A blockchain-based system could ensure a chain-of-custody log, tracking each step of the supply chain at the individual drug/product level. Furthermore, add-on functionalities such as private keys and smart contracts could help build in proof of ownership of the drug source at any point in the supply chain and manage the contracts between different parties. For example, a company called iSolve LCC is currently working with multiple pharma/biopharma companies to implement its Advanced Digital Ledger Technology (ADLT) blockchain solutions to help manage drug supply chain integrity.
  • Pharma Clinical Trails and Population Health Research: It is estimated that 50% of clinical trials go unreported, and investigators often fail to share their study results (e.g. nearly 90% of trials on ClinicalTrials.gov lack results). This creates crucial safety issues for patients and knowledge gaps for healthcare stakeholders and health policymakers. Blockchain-enabled, time-stamped immutable records of clinical trials, protocols and results could potentially address the issues of outcome switching, data snooping and selective reporting, thereby reducing the incidence of fraud and error in clinical trial records. Further, blockchain-based systems could help drive unprecedented collaboration between participants and researchers around innovation in medical research in fields like precision medicine and population health management.
  • Cyber Security and Healthcare IoT: According to the Protenus Breach Barometer report, there were a total of 450 health data breaches in 2016, affecting over 27 million patients. About 43% of these breaches were insider-caused and 27% due to hacking and ransomware. With the current growth of connected health devices, it will be very challenging for existing Health IT infrastructure and architecture to support the evolving IoMT (Internet of Medical Things) ecosystems. By 2020, an estimated 20-30 billion healthcare IoT connected devices will be used globally. Blockchain-enabled solutions have the potential to bridge the gaps of device data interoperability while ensuring security, privacy and reliability around IoMT use cases. Companies such as Telstra (user biometrics and smart homes), IBM (cognitive Internet of Things) and Tierion (industrial medical device preventive maintenance) are actively working around these use cases.
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8 Principles for Leaders to Make the Most of the Exponential Age (Part 2)

8 Principles for Leaders to Make the Most of the Exponential Age (Part 2) | Innovating in an Age of Personalization | Scoop.it
Sue Siegel on Exponential Leadership

1. Always be an ambassador for your team, innovation happens everywhere: As a leader, you must always be an ambassador for your team. Not only is it important for you to always reflect your company’s values, but it’s also important that you constantly search for opportunities, tools, people, and ideas that would be valuable to your team. In other words, if you go to an event or conference, always be on the lookout for great opportunities for your team.

2. Issues within the team should be resolved within the team: Given the pace of change and complexity of leading a high-performance team, there is often a lot of stress and confusion with implementing team decisions. This can lead to gossiping or complaining outside of the group. Sue notes that your colleagues outside the team don’t want to sit there and actually help you; instead, they just want to hear the gossip and spread it. This can be detrimental to productivity and team morale. Instead, don't start rumors, don’t spread them, and if you have an issue, take it up immediately within the team and solve it there.

3. Once a decision is made, it is supported. Period. This is really important. Once a decision is made in a meeting, there must be no second-guessing of that decision after the fact. Sue explains, “When we walk out of that room, and you've had all the chance to actually defend your position to make the decision, it’s time to start executing. That's it.” If you need to change a strategy, use data from implementation to support your argument and bring it up in the next decision-making meeting.

4. Proactive problem management – go directly to the source: As complexity increases, so too does the potential for conflict or confusion. As an exponential leader, you must be proactive in managing this. Sue’s strategy is simple and clear: “Go to the source, directly to the source. Don’t complain to managers or others before you’ve gone to the person first to resolve the conflict.”

5. Assume noble intent: I love this one. It’s important as a leader to trust your team and assume that they have the team’s best interests in mind. It’s remarkable what you are able to achieve when you assume noble intent. Ultimately, this goes back to hiring as well. You must ensure that you are hiring team players who are inspired by the company’s mission and purpose.

6. Ambidextrous leadership (investor + operator thinking): Sue believes there is enormous value in pairing venture capital investor-type thinking with operator-type thinking. Being able to step back and analyze opportunities from an investor’s perspective can be a valuable tool in helping entrepreneurs and managers alike make better decisions. And for investors, thinking like an operator is so important to understand the businesses they are investing in and, more than that, to best leverage your resources to help the companies.

7. You can’t delegate culture: This is absolutely critical for exponential leaders. Culture can make or break a company, and therefore it a) must be very high on a leader’s list of priorities and b) must come from the top. Leaders can’t delegate culture. Sue goes on, “Leaders are the culture bearers, the torchkeepers of culture in our companies. They might have change agents, or those that actually help them amplify their culture, but the leader cannot delegate culture. This is a truth that a lot of us forget because we're so busy. Employees and teams really want to see it from their leaders. They want to hear the talk, they want to watch them walk the talk, all the time.” Interestingly, while leaders cannot delegate culture creation, they can delegate culture keeping.

8. Purpose and passion: Purpose and passion drive people to do what they do. Sue explains, “Our people are very motivated by a purpose. And you have to go recruit for that kind of person. Purpose fuels passion. Passion creates energy to deliver. It empowers people to believe they can. Purpose and passion actually help people unlock the potential they never knew they had. It is up to leaders to define the purpose and build a team around it.”

In conclusion…

Change is coming. Exponential leaders must prepare for it and embrace it.

You’ve got to resolve conflict proactively, expect the best from your team, and fuel their energy to solve problems and create extraordinary results.
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12 KPIs you must know before pitching your startup

12 KPIs you must know before pitching your startup | Innovating in an Age of Personalization | Scoop.it

It is critically important for the founders of a company to intimately understand the company’s key performance indicators (KPIs). Founders cannot hope to grow a company in any meaningful way without an almost obsessive focus on its KPIs.

Why? Because KPIs, if constructed correctly, give management and potential investors a cold, analytical snapshot of the state of the company, untainted by emotion or rhetoric. This focus must not be limited to the KPIs themselves, for they are merely measurements of outcomes. We look for founders to have an understanding of what levers can be pulled and what tweaks can be made to improve the business, which will then be reflected in its KPIs.

The focus should not be on the KPIs themselves, but the meaning behind them and knowing what impacts each one.

Let’s review some of the KPIs that are important for founders to thoroughly understand and for which they should have a strategy, or set of strategies, for optimizing. Please note that some KPIs are not relevant to some types of businesses. Finally, I am not going to go into very much detail on each metric and how to calculate it as (a) that is beyond the scope of this article, and (b) that information is readily available from other sources.

Customer acquisition cost (CAC). CAC is the amount of money you need to spend on sales, marketing and related expenses, on average, to acquire a new customer. This tells us about the efficiency of your marketing efforts, although it’s much more meaningful when combined with some of the other metrics below, and when compared to competitors’ CAC.

Acquiring new customers is one thing, but retaining them is even more important. Your customer retention rate indicates the percentage of paying customers who remain paying customers during a given period of time. The converse to retention rate is churn (or attrition), the percentage of customers you lose in a given period of time. When we see high retention rates over an indicative time period, we know the company has a sticky product and that it is keeping its customers happy. This is also an indicator of capital efficiency.

Lifetime value (LTV) is the measurement of the net value of an average customer to your business over the estimated life of the relationship with your company. Understanding this number, especially in its relation to CAC, is critical to building a sustainable company.

We consider the ratio of CAC to LTV to be the golden metric. This is a true indicator of the sustainability of a company. If a company can predictably and repeatedly turn x into 10x (note: 10x is just an illustration and not meant to imply any sort of minimum or standard), then it’s sustainable.

The most successful founders tend to be those who have an obsessive focus on their KPIs and the drive to constantly experiment and optimize them.

CAC recovery time (or months to recover CAC). This KPI measures how long it takes for a customer to generate enough net revenue to cover the CAC. CAC recovery time has a direct impact on cash flow and, consequentially, runway.

 

Whereas CAC measures the variable expenses attributable to acquiring customers, overhead measures the company’s fixed expenses incurred irrespective of the number of customers acquired. Overhead relative to revenue is a reflection of the capital efficiency of a company (i.e. all things being equal, a company that generates $1 million in revenue on $200,000 in overhead is twice as efficient as one that generates $1 million in revenue on $400,000 in overhead).

Understanding your revenue and monthly expenses (fixed and variable) enables you to calculate the company’s monthly burn. This is simply the net amount of cash flow for a month when net cash flow is negative. If the company starts the month with $100,000 in cash and ends the month with $90,000 in cash, its burn rate is $10,000. If a company’s monthly net cash flow is positive, it is not burning cash.

A keen focus on runway is critical to the survival of any startup. Runway is the measure of the amount of time until the company runs out of cash, expressed in terms of months. Runway is computed by dividing remaining cash by monthly burn. We prefer to view a conservative estimate of runway that calculates the monthly burn utilizing current revenue and projected expenses (after accounting for the increased expenses to be incurred post-investment). We require an absolute minimum of 12 months of runway, but have a strong preference for 18 months or more. Short runways cause entrepreneurs to by myopic and not to have the liberty to tweak and iterate when necessary. It also forces them to almost immediately focus on the next fundraising round instead of growing the company.

Expressed as a percentage, profit margin tells us how much your product sells for above the actual cost of the product itself. Put another way, it reveals how much of the selling price is “mark-up.” This invaluable metric allows us to consider the return on investment on the cost of the product and is significant in understanding the scalability and sustainability of the company.

We consider conversion rate to be a very telling KPI in that it reveals a combination of the company’s ability to sell its products to its customers and customers’ desire for the product. It is particularly instructive to track and review conversion rate over time and regularly run experiments to improve it.

Certain businesses find that revenue may not be the most informative indicator of their financial performance. This is especially true for marketplaces for which revenue (i.e. their take rate) represents a small portion of overall transactions. Gross merchandise volume (GMV) can be a useful KPI in these cases. GMV is the overall dollar value of sales of goods or services purchased through a marketplace.

For companies that have apps, online games or social networking sites, monthly active users (MAU) is an important KPI. MAU is the number of unique users who engage with the site or app in a 30-day period. Understanding MAU is helpful in determining the revenue potential of a company or how well it is currently monetizing.

When we speak to founders to learn more about their companies, we ask them for these KPIs, along with their narrative and other information. It is a quick way for us to understand the current state of the business and we have serious concerns about founders who do not know their KPIs.  We find that the most successful founders tend to be those who have an obsessive focus on their KPIs and the drive to constantly experiment and optimize them.

Linda Holroyd's insight:

Great acronyms, great measurements

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How the convergence of automotive and tech will create a new ecosystem | McKinsey & Company

How the convergence of automotive and tech will create a new ecosystem | McKinsey & Company | Innovating in an Age of Personalization | Scoop.it

As the high-tech and automotive worlds merge—with four disruptive technology trends driving change—a complex ecosystem is creating new rules for success.

As four technology trends reshape the global automotive sector, customer preferences are moving away from its traditional strongholds, such as chassis and engine development. This shift in customer preferences and the sheer size of the automotive sector have attracted new players: a potent mix of large high-tech companies and start-ups. Both differ from the automotive incumbents on virtually every level.

 

These new entrants and the disruptive trends they bring—electrification, autonomous driving, diverse mobility, and connectivity—will transform typically vertically integrated automotive value chains into a complex, horizontally structured ecosystem. The newcomers are well positioned (and expected) to make moves in novel areas such as autonomous driving. Consequently, today’s OEMs and tier-one suppliers must abandon strategies aiming at total control of vehicles and instead pick and choose where and how to play by shedding assets, streamlining operations, and embracing digital acquisitions.

Four trends that favor software-driven innovation

The fortunes of players in the automotive sector have always depended on what customers see as valuable. Most of this value has resided in the hardware of vehicles and in the automakers’ brands. However, future innovations will probably focus on disruptive technology trends, so the customers’ perceptions of value will shift, increasingly putting incumbents in danger. The four trends that will favor the newcomers are these:

  • Electrification. Drivetrains will shift toward hybrid-electric, electric, and fuel-cell technologies as they mature and become cheaper.
  • Autonomous driving. The operation of automated cars will move from advanced driver-assistance systems to fully autonomous driving as the technology matures.
  • Diverse mobility. As the sharing economy expands and consumer preferences change, the standard model will continue to evolve from outright purchase or lease to rentals and car sharing.
  • Connectivity. The possibilities for “infotainment” innovations, novel traffic services, and new business models and services will increase as cars get connected to each other, to the wider infrastructure, and to people.

Attracted by the shift in customer preferences, the importance of the new trends, and the global automotive market’s massive size and value-creation potential, technology players are making their way into the sector. As they develop new software options, cars are evolving into computers on wheels, a change similar to events in the computer industry 20 years ago and the cellphone industry 10 years ago. As a result, we anticipate that a complex ecosystem will emerge in the automotive sector.

Although the sector adheres to a vertically integrated business model, with OEMs in full control of their supplier networks, the new tech players are more focused on horizontal moves:

  • A number of high-tech players are developing autonomous-driving systems that are quite likely to merge into what the computer industry calls an operating system (the central system that makes a unit run).
  • Disruptors from the taxi and ride-sharing industries are developing innovative new business models.
  • Two leading online and technology companies are focusing on in-car entertainment platforms, which they hope will become the standard for applications.

No single player is likely to dominate any part of such a horizontally organized, complex value chain by itself. But many of the new tech entrants are well positioned to take the lead in the software-focused parts. For each part of the ecosystem, there might be room for only a few winners, since few players will be able to invest the resources necessary to reach scale (Exhibit 2).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The automakers have invested billions in car hardware, from engine plants to stamping facilities and beyond, so they have the best position to dominate the hardware-focused areas. In software, the tech players enjoy significant advantages, including leading-edge capabilities, agile operating models, and the financial muscle required to pursue exploratory investments aggressively. For the automakers and tech players, success in tomorrow’s mobility sectorwill depend on how well they build on these natural advantages.

Linda Holroyd's insight:

Electrification, Autonomous driving, Diverse mobility, Connectivity - will tech or auto have the edge?

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The U.S. Just Got Hit by a (Values-Based) Tsunami

The U.S. Just Got Hit by a (Values-Based) Tsunami | Innovating in an Age of Personalization | Scoop.it

The U.S. Just Got Hit by a (Values-Based) Tsunami

Published on November 14, 2016

Bruce Kasanoff

 

Fair warning: today I'm going to share a research-backed perspective on the values at work that may have impacted last week's U.S. presidential election. These values have impacts far beyond politics, as they could impact how we work and live for decades to come.

 

There's a lot to unpack here, so I apologize for the longer than usual post. Here goes...

Last week, I used Maslow's Hierarchy of Needs to make the case that we need more empathy to help us better understand the perspectives of others. Some readers commented that the flaw with Maslow is that people cite him without supporting their conclusions with actual research. This led me to the UK, where Pat Dade's firm has spent many years connecting Maslow's work with research.

His firm, Cultural Dynamics, bases its work on quantitative research that has been conducted since 1973, measuring the values, beliefs, and motivations of (primarily) the UK population. They have used this research to split the population into three different values-based groups.

In both the United States and UK, the long-term trend in recent decades has been a decline in the number of Settlers in favor of the other two groups. Here are some of Pat's fascinating observations. The subheads are mine, but all observations in quotes are his:

The need for change: "When Settlers are no longer the dominant group a political system will need to evolve, or break, if it is to satisfy the group replacing the Settlers - the Prospectors."

Our institutions must change: "As needs are met and new needs emerge... the institutional structures that satisfied the Settlers become less relevant as the Prospector needs increase and the systems fail to change at the same rate."

The role of young male Prospectors: Pat uses the term "Golden Dreamers" to describe young, primarily male Prospectors who are both vocal and so outspoken as to often be labeled as "trolls" online. He says, "Golden Dreamer voices become amplified when political institutions become unfit for purpose. The amplification occurs when the voices of those representing the Prospectors with 'shattered dreams' leads the ‘confirming voices’ of Settlers who believe their dreams have turned to nightmares and there is nothing to do about it."

How the media magnifies fear-based voices: "The Settlers and Prospectors who hold these values (smoldering resentment fueled by fear)... exhibit behaviors (that) make great copy and drama for the media - and a feedback loop creates even more extreme views and behaviors."

The great divide emerges: "The emergence of the Pioneers with a vastly different set of needs has added drama to the scenario. This conflict between the ethical liberal values and the moralistic and pragmatic values of ill-liberal values lies at the heart of the battle for the soul of democracy... liberal institutions and organizations (are failing) to satisfy the needs of the Settlers and Golden Dreamers."

We need a new vision that satisfies all: "The fact that (Golden Dreamer/Settler values) are winning very close elections is a wake-up call for liberal values to stop compromising with inhumane values and behaviors. A new version of a liberal democracy is yet to be created. Now is the time... the US contains almost 50% Pioneers and the UK almost 40% - but (these groups) have to be attracted to people and policies who are less political and more ethical as representatives in social and electoral processes."

The majority will always want change: "Most people are Prospector or Pioneer and will be looking for change, not battling against it."

Warning - danger ahead: "Prospector and Pioneer values are driving (entrepreneurial activities and innovation) within organizations, and initially these groups will see the bright side of the technology – but they will also be the first to see the dark side. This hasn't happened yet – the narrative is still about the bright future – but we expect a backlash before 2020 and the next elections in the UK and the US."

Summing it up...

One could easily make the case that both major political parties and our largest companies have been far too slow to react to these shifts in our population. If Pat is right, nearly every group is unhappy now:

Pat says that the mood of Settlers and the Golden Dreamers portion of Prospectors may be best captured by Bob Dylan's line, “If you ain’t got nothing, you got nothing to lose”.

The rest of Prospectors and all Pioneers are watching as seemingly everything shifts away from their values. To make matters worse, "their" institutions aren't successfully formulating or communicating a positive formula for change.

Why did I share this?

In the U.S., confronted with very different choices, voters were split virtually 50/50. The only thing that united the population was that almost no one liked the choices.

Elections are a highly visible way to judge the sentiment of the population, and this election - like Brexit in the UK - revealed a tremendous clash in values. These values don't just separate us politically; they separate us in terms of how people perceive nearly everything.

This is an issue for all: companies, employees, leaders, non-profits, student, freelancers, retired folks... everyone. If we dismiss it as "our politics are broken" then we are doomed to suffer endlessly.

I'm an optimist, so suffering endlessly is not an acceptable solution. Instead, we need to be realistic. The same old answers are long past their breaking points. We need fresh faces and fresh ideas.

In fact, optimism may be the right way to test any potential solution. The right answer should spark optimism in all three groups: Settlers, Prospectors, and Pioneers. That has been the magic of the American Dream: it sparked optimism in all. We need to rekindle that sense of optimism, not just in the U.S., but all around the world.

Bruce Kasanoff writes and edits content for a wide range of entrepreneurs and executives.

 

 
Linda Holroyd's insight:

Bring the Settlers, Prospectors and Pioneers together

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Why investors are throwing heaps of money at machine learning

Why investors are throwing heaps of money at machine learning | Innovating in an Age of Personalization | Scoop.it

If you’re a whip-smart investor with big bucks to spend, chances are you’ve got your fingers in the AI pie.

It’s a market where $50 million is chump change, so if you really want to play with the high rollers you’ll need more room on the check.

Sentient’s up to $144 million in an AI platform play, while Vicarious Systems has thrown $67 million at AI algorithms.

So it’s pretty fair to say that if you’re a bot, you’re going to enjoy a top-notch private education.

But why now? What’s made machine learning and AI the hot stuff du jour?

It’s a game changer, that’s what.

AI and machine learning are about process optimization, but taken to the extreme.

The more they learn, the smarter they get and the more they’re going to utterly disrupt the economics of the world as we know it.

But first they’re going to disrupt the economics of software development.

It won’t be long until a project that currently takes a full year of work and a team of 6-10 devs can be compressed to a couple of months.

And that’s just to start. Because while humans are pretty well optimized, machines are just getting started.

Skeptical? Sure. But we’ve seen it before with the first industrial revolution. And that was when machines weren’t so bright.

Now they’re smart enough to put whole teams of devs – and all the teams supporting them — out to pasture.

Take the stock exchange ticker symbols that epitomize Wall Street. Thomson Reuters and Bloomberg used to spend a small fortune maintaining their databases of AAPLs, MSFTs, and AMZNs – collating their information, tracking prices, and preparing reports.

No longer. Machine learning can automate all of this. Those databases can now run on AI power alone thanks to models primed to identify ticker patterns or news relating to a publicly traded company.

The fact is, if it’s repetitive, process based, and involves large amounts of data, it’s a prime target for machine learning.

And let’s face it – those are the kinds of problems developers are targeted with solving.

After all, good developers are the ones who are lazy at heart. They want to solve a problem once, not multiple times.

And machines are crafted for efficiency. They’re born pattern recognizers and problem solvers.

And given enough time and enough maturity, we’ll be seeing systems that possess near-human intelligence in narrow domains.

That’s a lot of smarts for a lot less money than it would take to hire a team of crack developers. Which is why investors are throwing money at machine learning like there’s no tomorrow.

Because they see the tomorrow – and it’s one that involves a ROI that humans just can’t offer.

Sure, there’ll be road bumps.

Machines are as left-brained as they come, and some problems are fuzzier, messier, and broader than machines can currently handle. Finding a way to solve those right-brain problems – the ones that require logical leaps and creativity – is where the real opportunity lies.

Because when we’ve done that? We’ve cracked the secret to our own humanity. We’re still figuring our how own brains work, so recreating them is going to be a challenge we might not yet be up for. But the lure of that is pretty spectacular.

There’ll be massive failures. There’ll be efforts to solve the unsolvable. We’re betting that companies that build out toolkits to improve the accessibility and usability of AI will be some of the first winners in this field. Helping data scientists all over the world make use of AI to solve individual problems in specific domains will be one of the first places the economic value becomes apparent.

This, of course, is only the beginning. Data exchange between these models will further accelerate the usefulness and cost effectiveness of this AI. When it all comes together, there’ll be successes that will change the very fabric of our economy – and how we see and do things. Smart investors see it. They’re willing to gamble on the failures because they see the game changing potential of the successes.

Simplifying and compressing data science is the first place we’ll see the economics of machine learning start to pay off. It’ll mean smaller teams and condensed projects.

But let’s face it – putting ourselves out of a job is utterly worth it for the future that could be.

With a tireless, dedicated genius working with us on solving problems, we can turn our attention to the more rewarding, inalienably human bit: defining them.

Jeff Catlin is CEO of Lexalytics.

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Secrets of the Next Wave

Secrets of the Next Wave | Innovating in an Age of Personalization | Scoop.it

Dear 21-year-old me.
Have you ever considered just how you might start such a letter to your younger self? The question is a trick, of course. It’s a way to ask: What has the experience of career and life so far really taught you? What single secret might you wish to slip, like a fortune cookie paper, into the pocket of your younger self? Or, more practically: What do you want to tell your 21-year-old child heading to a first job? The baby-faced executive working in your office? The one running your company? Or even, perhaps more usefully, this: What can I do differently in the future?
If you had to make a fast and intense study of the secret to success now, you could do worse than scanning the names and lives that follow on LinkedIn’s 2016 Next Wave list. The list itself is kind of a miracle of technology. Ages ago I was an editor at TIME Magazine and we always crabbed together those fancy-sounding annual Time 100 lists with far less than the level of intellectual rigor you might have hoped: “Hey, let’s add that Peruvian ceviche master after the Prime Minister of Australia?!” And, sure enough, an artisan of fluke, lime and chilies would make it on the list. Ahead of Bill Gates. Buzz sold. 
The Next Wave is different. It’s an attempt to use data to fillet out of the world around us a sense of what’s working now. And, by implication, what’s not. Our world runs on networks after all—for medicine, finance, transportation, just about everything. These networks can be studied and measured and understood. So why not use them to tell us something about work?
As you read through the Next Wave list (or if you’re on it!) you’ll discover one thing pretty quickly. Animating all the brilliant ideas, the moving personal stories, and the historic-scale ambitions of each Next Waver is this single insight into what makes a powerful career now: We are what we are connected to. I don’t just mean connections to people. I mean the ideas you and I are tied to, good or bad. The experiences. The hopes. The puzzles we work on as we drive or run or consume our morning coffee. This list is a stark lesson that if you’re making an inventory of your life now the right place to start isn’t with a measure of what you have in the bank. Or the market cap of your firm. Or even your resume. No. Try this much simpler and more powerful puzzle: What am I connected to? The people on the list here: They have 25 times more connections than the average member on LinkedIn. 
I have spent a good part of the last few years trying to sort out why some people and companies and movements succeed now, while others fizzle out or implode. It’s something I think about a great deal, not merely in my day job as CEO of Kissinger Associates or as a board member at Starbucks and FedEx, but also in considering politics and history and economics. Why do some nations fail? What’s happening in our country now? I have found that success today in any endeavor is marked by a kind of intuition about connection. You and I look at a car and think: “Car”. The Uber guys look at it and see a revolution. The White House looked at ISIS and said, at first, “amateurs”, because they couldn’t quite make out the webs of power really at work. In my own career, if I’m honest, the biggest wins have come from connection—not inspiration or genius or drive. So if I were speaking to 21-year old me? The message would be fast: You are what you are connected to. 

What the Next Wave list celebrates is, in a sense, a new kind of corporate athlete. Not merely the team player, but the connected one—the figure who has that skill, whether working in a traditional law firm or some bleeding edge startup, to tie together unique groups of people or concepts into something new. You’ll find on this list a data scientist working at a fire department, a Google executive flipping ISIS wannabes back, and the media entrepreneur who turns her tools loose on the problems of race, diversity and society. In the past, there was always an eagerness to celebrate the great CEO or general or politician who battled ahead on their own, smashing obstacles with the unbreakable club of their egos. Those are the folks who used to make up lists of this sort. We know better now, I think. The great executives or innovators we celebrate here, the ones whose breakthroughs we study and consider in that “Hey, what does this mean for me?” kind of way, all drew on connection to make their success possible. 

If you look at any collection of powerful careers now, no matter how you sort it—venture capitalists in China, aid workers in Ghana, biologists in Amsterdam—real success is marked by an honest and useful mania for connection. And this tells us something about the age we live in. A hunger for new links often emerges during periods of really radical change. During the Industrial Revolution, for instance, the very first scientific journals and technical congresses came into being as figures from around Europe gathered to share ideas and challenge old thinking. Or think of the disappearance of Latin as the dominant language of scholarship. When, 400 years ago, scholars began using ordinary French or English, it was because they wanted to connect to an ever larger audience. “How fast can our ideas spread?” figures of that age asked. Little wonder the great Enlightenment philosopher Immanuel Kant said the motto of his age could be simply recorded as: "Dare to know!" Our age? "Dare to connect!" is not a bad motto for success.
What a list like this one reminds us is that there is a certain power that inheres in making links. It’s the power of discovering something new, of exercising our empathy, of being open to surprise. When I was younger, a boss once gave me this advice: Just do one big thing every year and you’ll have a successful career. Write a book. Launch a new project. Change jobs. His point was that in order to crack through the white noise of our daily work, we need to be sure each year to strive for one big leap.
I’ve tried to follow this advice pretty carefully and found it’s been a useful guide. But it’s clear to me it’s not enough. Do one big thing every year, sure, but this too: Make a list of all the new connections you want and then ruthlessly jack them into your life, one after another.
In my recent book The Seventh Sense, I’ve called this instinct to connect a whole new skill—really a sensibility that marks success now. I mean an ability to look at the world, see connection, and use it. It’s a skill that can be learned. And it is what will mark the winners and losers of our age when we look back several decades from now. What the data tells us about the Next Wave leaders is something I think we all know by instinct now anyhow: Success and connection are really the same thing now.
So let’s go back to the start. Tell us: What would you tell your 21-year-old self? Or your 51-year-old self? Something about sales? Friendships? Connection? What didn’t you know then that would be of help now to all of us as we try to figure out this strange and exciting new business world around us? Go ahead: Connect us to your ideas! (It’s the only way we may make it to the Next Wave in our own careers.)

Joshua Cooper Ramo is co-CEO of Kissinger Associates and a board member of Starbucks and FedEx. He’s also the author of the New York Times best selling book “The Seventh Sense,” which was #1 on McKinsey's latest CEO reading list.

Linda Holroyd's insight:

Here's to those who are building that seventh sense

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Why "Relationship Workers" will replace "Knowledge Workers"

Why "Relationship Workers" will replace "Knowledge Workers" | Innovating in an Age of Personalization | Scoop.it

There are two factors today that are dramatically shaping the future of work. Technology is reshaping what can be done by machines. Every day, there are stories of jobs being taken over by Artificial Intelligence. From reading X-Rays to writing financial reports for publications and advising clients on how to manage their portfolios, several jobs that were formerly within the domain of humans are increasingly getting done by machines.
Robots do not get temperamental or take vacations. And the costs of having a robot are also dropping. Several of the jobs that are considered indispensable today will not exist in the future. A host of digital technologies, from chatbots to virtual reality, is taking over jobs that humans have done until now.
The second factor is the increasing complexity in our world. Problems are getting too complex to be done by one individual. The days of the lone genius working alone in a lab are over. Problems have to be seen through a multidisciplinary lens. No longer can someone from one discipline solve problems all alone.
Traditional economics was based on the assumption of the rational human being, who would weigh all options and incentives before making a choice. However, economics failed to explain the biases and blind spots inherent in the human psyche. That led to the birth of Behavioural Economics, which was born out of the fusion of economics and psychology.
But when the Nobel Prize was given to Daniel Kahneman, the father of Behavioural Economics, it was given for his work in the field of economics. Maybe it is time to rethink the categories of the Nobel Prize in a world that is increasingly transdisciplinary.
When the nature of work changes, the skills portfolio needed to do that work also changes. Google’s fonts are designed in cross functional teams where coders work with psychologists to design fonts that will be more attractive to users. Google needs anthropologists who will help understand how a user behaves and thinks. Their insights become useful inputs for designing and continuously tweaking the company’s products and services.
Working in trans-disciplinary teams will mean that knowing how to manage people and coordinate with others will be skills that will be valuable in the job market. Routine problems will get solved by algorithms. Human beings who can solve complex problems will be valuable. Being able to leverage data, form a hypothesis, present the idea to others and convince them will be important. Creative people who are skilled in working with others to solve complex problems will be flooded with opportunities.
If accomplishing the task becomes more and more dependent on others, we will need to work more closely with others. None of these skills can be learned by taking a class. They have to be built through interactions and feedback. We will need others to be able to succeed.
Computers and automation saw the rise of the “knowledge worker”. A knowledge worker was a person whose job involved handling or using information. With computers increasingly taking over such jobs, those who are skilled in working with people will become more prized. The future belongs to people who are more emotionally intelligent. This may be the era of the “relationship worker” – someone who can handle complex human relationships.
Those who can navigate complex human relationships with empathy will be the most valuable workers in future. Do you agree? Have you seen the early signs of that already? I would love to know what you think.

Linda Holroyd's insight:

Transcend the need the knowledge and the need for tech - Become a Relationship Worker

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Why the Future of TV Isn’t TV

Why the Future of TV Isn’t TV | Innovating in an Age of Personalization | Scoop.it
Why the Future of TV Isn’t TV
Published on October 2, 2016

Tom Goodwin
EVP, Head of Innovation at Zenith


I wrote this piece for the Wrap, it's featured here.

You can think TV is in terminal decline or that it’s watched by more people, more often, for longer than ever before and you can both be right. Such a dichotomy is representative of the powerful forces for change in an industry where digitization is changing behaviors, business models, consumer expectations and well, everything. Digital disruption is existentially powerful, we can be scared by what Napster did for music, or what Amazon did to retailers, or we can embrace the new opportunities that having a proliferation of screens and pervasive, fast connectivity provides.

Like many things, it used to be simple. Our media channels correlated perfectly to the single specialized device we consumed that media on. Radio programs via radio stations listened to on radios via radio waves. TV shows on TV channels via TV masts. News via newspapers on newsprint, movies and movie theaters, all clearly separated verticals with no possibility for confusion.

Digitization has destroyed that, as all media becomes bits and bytes, the Internet becomes the pipe to all content and devices become converged, the boundaries between music streaming and radio, between digital art and short films and, most importantly, between video and TV have all blurred. What becomes the defining feature of TV vs. Video? Is it the device it’s watched on? The length of the content? The production quality? Or is it the pipe for the data?

I think in an age where Apple commissions TV content to run on Apple music, where Burberry shows premium footage via Smart TV app, where we stream the NFL via Twitter on a phone, or watch news from Hulu in VR, it seems that the delivery mechanism, the device and the content length offer poor guidance in what TV is and isn’t. It seems more likely that TV in the post-digital age is best defined by the content quality. For years the difficulties in production, the cost of distribution meant that professional commissioners would decide what should be created and distributed. They were the arbiters of what was TV.

Now it’s everyone. Content and creativity is democratized, 4K cameras are cheaper than ever, Kickstarter can fuel every dream, Facebook live or SnapChat give everyone a platform. From YouTube celebrities to viral sensations becoming musical stars, it’s no longer 1,000 TV channels, it’s 1.5 billion connected video cameras in pockets, 400 hours of content uploaded to YouTube each second and billions of views per day through social media.

What we have in 2016 is abundance in all directions. We have more screens, in more places, than ever. We have devices like mobiles creating ever more incremental media moments in life, the mindless swiping in the elevator, the illegal snatched glance at a red light, the subway commute. More screens, more moments, it’s a pie that’s growing and this best describes the vast opportunity for everyone in TV. The challenge is how we can make better content, how we can aid the discovery and sharing of the content and how we will make more money and in better ways.

We’re in a status quo before a paradigm shift. We’re at peak complexity, we have a legacy system of set-top boxes with small incremental changes built around the edges. I now need to select my remote before I decide what show to watch. I need to remember the 13 perfect button presses to watch Jon Oliver on demand. We have SVOD, AVOD, streaming, stored content, broadcast — it’s messy. Terrified of the value destruction first seen in music, retailing and aggregation portals, it’s easy to see why the TV industry is slow to change. Why would they? Yet, we have huge mounting tensions building, we have skinny bundles, OTT, Twitter on the Apple TV, rising levels of privacy — all chipping away — but none delivering the final blow to consumers who are increasingly frustrated being spoiled by the simplicity of a Google search bar or access to everything in one place via Spotify.

TV will one day all be digital. In a world of 5G, set top boxes could fade to the smartphone as a hub. VR content can be made and streamed in real time. Micropayments could take off. Geography will become meaningless. The notion of broadcast vs. streaming will be a false choice. We need to embrace that reality now. All these changes allow more money to be made from more people, more often and in new ways. Everything from rights negotiations, to content format, to payment systems and business models need to be assessed with a future focused lens.

Technology is not a threat, new media doesn’t replace the old, it just gives a new framework to pull it through and creates more places for it to appear. First, it replicates old models in new ways but then it transforms them.

And it is this transformation that makes TV the best place to be right now. Everyone should be thinking about how TV content can mean new things: No longer beholden to ad breaks, shows can be of any length, shows can be interactive, shows can cross screens, shows can be rich immersive storytelling in VR. We need more games-design thinking and less moving image. TV content can be shared in new ways, socially discovered. But how do we replicate the water-cooler moments of the TV of the past? How do we embrace social networks as the distribution network of the future and not be scared of the attention they steal?

This is TV’s moment, it’s time to embrace the change. Quality content has never been more in demand, we have never had more moments to watch it, there has never been a bigger audience. It’s time to look forward to a future where TV content is unleashed from the box that is TV.

Linda Holroyd's insight:

More interactive, more immersive, more content - customers win!

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Why Innovation Fails

Why Innovation Fails | Innovating in an Age of Personalization | Scoop.it

Why Innovation Fails
Published on September 28, 2016
Stefan Lindegaard
Chief Transformer at Transform - or Die!
Why innovation fails? That is a question that has many answers and one that should always be put in the context of the specific organization and situation. Yet, I have seen enough failures on (corporate) innovation so that I can share my perspectives on what goes wrong.

I have been asked to do this in just 12 minutes at an upcoming conference. Here you get some of the messages I intend to share. My focus is on corporate innovation efforts. Your feedback is appreciated.

Executives do not understand innovation. Yes, this is often said and yes, executives are an easy target. But you know, there is also lot of truth to this and when I speak with corporate innovation teams around the world, how to get their executives better onboard for innovation efforts, is one of the key topics.

Middle managers do their job. Strange, how can this be a bad thing? Well, if middle managers do their jobs as they have been told by their executives they will almost always favor the day-to-day business over the innovation activities. Imagine this as a battle between day-to-day and innovation, you play 10 times and you have the day-to-day team win 9-1. That is my experience over the last 10 years.

Why? Because of the objectives and incentives put forth in general for the middle managers and in particular because of the executive decisions made in conflict situations. Their actions speak louder than their nice words on innovation. When you have conflicts, executives tend to get short-sighted, avoid experimentation (and the inevitable failures that comes with innovation) and hang on tight on control (which can drain many innovation efforts).

We are back to my first point on executives that do not understand innovation. What happens with the middle managers is because of the executives and their actions – or rather lack of actions. Point made.

You try too hard to build a culture of innovation. Very few companies have a definition of innovation. They don’t even have a common language and understanding around innovation. Granted, this can be very difficult in large organizations with several business units and many different functions. Maybe you should just admit that this is difficult. Talk less about innovation and get back to basics.

You need to build an adaptive and agile corporate culture. It does not have to a culture of innovation because if you can’t even define what innovation means for your organization, how can you then dare to think that you can create a culture around this? I just don’t get why so many organizations still try this, but it really helps me understand why so many fails at trying to build a strong innovation culture.

You don’t open up your organization. I have witnessed many attempts at opening up corporate innovation efforts over the years. What I have learned is that the companies that succeed are those that are comfortable with experimentation, loss of control and willing to share as much information and insights as possible (because they believe that fast execution is what really matters for success). This comes with open innovation. Too many executives – and their organizations – are just not ready for this.

People first, processes next, then ideas. If you equate innovation with ideas, you have already lost. The front end of innovation (where you get ideas and work with them in the early stages) is now the easier part of innovation management. Why? Ideas are everywhere today and if you struggle to find ideas (even the good ones), you are just not doing your job well enough.

The real challenge is the back end of innovation – the execution part – and here you need the right people at the right time for the right projects and in the right context and with sound processes for this match to happen.

The thing is that all companies have some kind of a project pool where they log their innovation efforts into different categories. But I have not yet met a company that had a people pool to match this project pool. In short, a people pool helps you identify, train and place the people who could contribute the most during the three phases of innovation known as discovery, incubation, acceleration. You need to know the people and you need to have the processes in place to use them in the right way.

The lack of a strong networking element in the corporate culture. One of the most prevailing set of thoughts in any organization is based on a simple question: “What’s in it for me?”.

Most people ask themselves this question when they are asked to contribute to activities that are beyond their well-defined day-to-day tasks. Innovation falls into this category for most employees. So you need to know the reasons why people want to help, but most organizations fail to get this insight and use it for building a strong networking element in their corporate culture.

The networking element also requires that you look into strategic reasons for networking, builds a roadmap for networking according to your objectives and train people to become better networkers.

A note on corporate innovation teams: They need to know their key partners and resources for innovation - internally as well as externally - but innovation teams rarely do a stakeholder analysis. They don’t know their backers, blockers and those who are neutral – and they don’t know why they have the stand they have. Big mistake.    

You die because of the corporate antibodies. Too often, an organization is plagued by silo issues that hinders the ability to bring out the best combinations needed to execute faster and better than the competitors. Too often they also tap into the usual suspects to get the job done and too often, the employees favor the status quo over change. Corporate antibodies in this form will kill your efforts and this is not just for innovation.

I only have 12 minutes to get my points across. It would be great if you could let me know the top three messages that you like the most as this can help me sharpening my focus.

The good thing is that I also have a longer session later at the conference where I can share my insights on what companies and organizations should do to get a better impact with their innovation efforts. I will share a post on this later. 

Linda Holroyd's insight:

Thought-provoking article on why innovations fail

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The four pillars of distinctive customer journeys | McKinsey & Company

The four pillars of distinctive customer journeys | McKinsey & Company | Innovating in an Age of Personalization | Scoop.it

The four pillars of distinctive customer journeys
By Joao Dias, Oana Ionutiu, Xavier Lhuer, and Jasper van Ouwerkerk

New research reveals that focus, simplicity, “digital first,” and perceptions matter most.

In recent years, customer experience (CX) has emerged as a major differentiator for large companies, including financial-services providers. In a McKinsey survey of senior executives, 90 percent of respondents confirmed that CX is one of the CEO’s top three priorities.

It’s a priority because the stakes are so high. For financial institutions, for example, rising customer expectations are pressing organizations to come up with more functional improvements even as alternatives to traditional financial services are emerging. In this dynamic environment, financial institutions face a stiff challenge to differentiate their offerings while reducing cost and complexity for customers—and to do it at a profit.

Overcoming these challenges is critical not just to meet rising customer expectations and to compete with new digital attackers but also to generate significant business impact. Our research indicates that for every 10-percentage-point uptick in customer satisfaction, a company can increase revenues 2 percent to 3 percent.

At a time when the customer-satisfaction scores of top-quartile institutions can exceed those of bottom-quartile players by as much as 30 to 40 percentage points, the financial payoff from best-in-class CX can be significant indeed. These gains come from a variety of sources, including additional product purchases generated by cross-selling and upselling, such as when a borrower increases the value of a loan.

Would you like to learn more about our Digital McKinsey Practice?
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To understand what constitutes distinctive CX in financial services, we performed benchmarking research on five key customer journeys—the series of interactions a customer has with a brand to complete a task—in banking and insurance.1 The survey findings in this article relate specifically to retail customer onboarding but apply generally to the other journeys we studied.

Reaching the top quartile of CX performers is no easy task. Cost, design, and value are emerging as key differentiators for customers, yet companies often lack guiding principles to shape those efforts. By analyzing and ranking correlations between customer satisfaction and operational factors (such as the reasons a customer chooses one company over others, cycle times, features offered, and the use of digital channels) in our survey, four pillars of great customer-experience performance stood out:

1. Focus on the few factors that move the needle for customers

We asked customers to assess different characteristics of the end-to-end experience, including the first interaction with the institution, the ease of identifying the right products, and the knowledge and professionalism of staff. We found that only a small number of characteristics (typically three to five out of 15) had a material impact and accounted for the bulk of overall satisfaction (Exhibit 1).

For example, when analyzing the characteristics of the customer onboarding journey, we found that transparency of price and fees, ease of communication with the bank, and the ability to track the status of the onboarding process accounted for 42 percent of overall satisfaction. The next three highest-ranking characteristics—assessment of broader customer needs; products and services received immediately after account opening, such as debit cards and mobile and online banking access; and ease of identifying the needed product—account for an additional 34 percent. Conversely, characteristics such as the courtesy of staff, the timeliness of callbacks, and the clarity of documentation had limited impact on satisfaction. This finding strongly suggests that banks should concentrate mainly on those things that make the most difference to customer satisfaction.

2. Ease and simplicity: The payoff trade-off

Today’s harried customer values convenience. Cutting down the time it takes to complete an individual journey, such as applying for an account, by making it easier and simpler has a deep effect on customer satisfaction.

For example, in France, customer satisfaction drops by up to 30 percentage points when the time to open an account exceeds 45 minutes. That 45-minute point marks the “satisfaction cliff.” But what’s really important to note is that there is a diminishing payoff in reducing the time it takes a customer to complete a journey. In France, again, the impact on customer satisfaction when taking between 15 and 45 minutes to open an account is relatively minor (the “satisfaction plateau”). Cut that process to below 15 minutes and satisfaction increases by up to ten percentage points. Companies need to work out the trade-off, then, between the investment in improving the ease and simplicity of a process and the resulting improvement in customer satisfaction and new value created.

As more processes are digitized, journey times will be cut back. But low cycle times alone don’t equate to superior CX. Rather, our research indicates that customers respond most positively to the ease of a transaction or process.

3. Master the digital-first journey, but don’t stop there

We analyzed different types of customer journeys: those that are completely online, those that start online and finish in a branch, those that start in a branch and finish online, and those that take place fully in a branch. We found that digital-first journeys led to higher customer-satisfaction scores (Exhibit 2) and generated 10 to 20 percentage points more satisfaction than traditional journeys.

For all the advantages of digital-first journeys, those journeys that are the most digitized across all the interactions lead to the greatest customer satisfaction. Nevertheless, many financial services do not provide fully digital services even when they exist, such as digital identification and verification. This finding indicates that financial-services providers can still significantly improve CX by digitizing complete journeys.

4. Brands and perceptions matter

It may not be surprising that companies whose advertising inspires their customers with the power and appeal of their brand or generates word of mouth deliver 30 to 40 percentage points more satisfaction than their peers. But how advertising or word of mouth affects perceptions is crucial. Two banks in the US, for example, performed nearly identically across a set of customer journeys. However, customers viewed one bank as delivering a much better overall experience than its rival, because the higher-ranked institution’s advertising promoted its user-friendliness.

That perception had an important effect on identifying promotions that were effective for attracting new customers but, on average, had a nearly neutral impact on satisfaction. The average, however, is misleading. Promotions are slightly negative for traditional banks but positive for purely online players. In the same vein, physical proximity to a financial-services provider tends to have, on average, little discernible influence on customer satisfaction. Again, though, the value to customers of physical proximity can vary widely from institution to institution and from country to country, pointing to a need for financial institutions to understand their customers at a more granular level.

Why the customer experience matters
Despite the impact of word of mouth in shaping perceptions, our survey revealed that few customers recommend a financial-services provider on the strength of their existing relationship with it. An existing relationship alone does not turn a customer into an advocate. Institutions that do more to please their existing customers and help them tell their story to their peers might be able to mobilize a new group of influential advocates for their products and services.

It pays to customize
While the four hallmarks for outstanding customer experiences tend to be universal, experience designers should focus on a range of customer preferences based on country, product, and age group. For example, we observed that the ease of navigating through the account-opening process had a larger impact on satisfaction in Italy than in France. Conversely, the assessment of broader customer needs is more important in France than Italy.
When looking across products, we also found detailed differences, such as the satisfaction factors for current accounts and mortgages. When working with current accounts, customers derive the greatest satisfaction from transparency on prices and fees; when they’re applying for a mortgage, by contrast, they most value the ease of filling in the application form.
Finally, there are also differences among customer groups. The ease of communicating with the bank is more important to customers 55 years and older than to 18-to-24-year-olds. Conversely, the ability to identify the right products is more important to 18-to-24-year-olds than to those 55 and older. This suggests that processes and value offerings need to be modular with their emphasis varying with what matters most to each customer segment.
Knowing what to do is the right place to start. But a company’s success in building out great customer journeys requires agile capabilities that excel at rapid iteration and testing and learning.2 Reacting to live feedback from real customers is often the difference between a good and a great customer experience.

About the author(s)
Joao Dias is a partner in the Cologne office, Oana Ionutiu is a specialist in the Bucharest office, Xavier Lhuer is an associate partner in the London office, and Jasper van Ouwerkerk is a senior partner in the Amsterdam office.

Linda Holroyd's insight:

Move the needle forward, keep it simple, manage the digital journey, as well as your brand and perception

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