Innovating in an Age of Personalization

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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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.

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.

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:

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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. 

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.

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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.