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How to Make Data Experiments Powerful

How to Make Data Experiments Powerful | Analytics Project Management | Scoop.it

This article provides two clear examples of how managers can move their projects and organizations to become data-savvy organizations. The fun of this Analytics article is that an example is from an industry that you wouldn't think of being open to IOT and Big Data!

 

Experimentation is powerful when it deepens managerial intuition. The first example asks teams to runs lots of tests and to ask how each one impacts the organizations key performance indicators (KPI's.)  So the team has to look at all the "touchpoints, the task completion, metrics, more deeply than have they had in the past. Managers can quickly test their insights, either validating their thinking or sending them back to think more, then swiftly bring changes to scale.This really changes the team culture and how they look at analytics. 

 

Experimentation is powerful when the organization has unique data. The next example looks at a laundry operations that has a unique set of data and opportunities for introduction of IOT to collect data. "This organization has made it easy, both technically and culturally, for managers to test ideas and learn from them."

 

This is an easy read and a big win for project managers looking for examples of how to implement Analytics Projects. 

Hossenlopp's insight:

This article provides two clear examples of how managers can move their projects and organizations to become data-savvy organizations. The fun of this Analytics article is that an example is from an industry that you wouldn't think of being open to IOT and Big Data!

 

Experimentation is powerful when it deepens managerial intuition. The first example asks teams to runs lots of tests and to ask how each one impacts the organizations key performance indicators (KPI's.)  So the team has to look at all the "touchpoints, the task completion, metrics, more deeply than have they had in the past. Managers can quickly test their insights, either validating their thinking or sending them back to think more, then swiftly bring changes to scale.This really changes the team culture and how they look at analytics. 

 

Experimentation is powerful when the organization has unique data. The next example looks at a laundry operations that has a unique set of data and opportunities for introduction of IOT to collect data. "This organization has made it easy, both technically and culturally, for managers to test ideas and learn from them."

 

This is an easy read and a big win for project managers looking for examples of how to implement Analytics Projects. 

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Solving the data conundrum: How to leverage tech and 'big data' for impact

Solving the data conundrum: How to leverage tech and 'big data' for impact | Analytics Project Management | Scoop.it

The big problem of #BigData: incomplete, fragmented data sets and knowledge at NGO's yet start right by asking the right questions on how to improve organizational performance.  https://t.co/ctyP0XzufO

Hossenlopp's insight:

Inspiring NGO Big Data Examples:  The big problem of Big Data is incomplete, fragmented data sets & knowledge. Yet start an analytics project right by asking the right questions on how to improve organizational performance.  

 

Example:  Drill down from high-level "what do you need on a Monday morning" to “How am I performing?” which would then be refined to, “In which areas of health am I failing the most, as of one month ago, and which specific clinics are contributing the most to my nonperformance?” 

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6 Ways To Make Your Company Data-Driven - InformationWeek

6 Ways To Make Your Company Data-Driven - InformationWeek | Analytics Project Management | Scoop.it
Rich Wagner, president and CEO of Prevedere, shares six guidelines he's developed based on his own experiences seeing good data left to waste at major enterprises, including the Fortune 500 chemical company where he once worked.
Hossenlopp's insight:

Leaders are launching Analytics and Big Data projects to help organizational performance. Why? The Economist Intelligence Unit found data-driven companies rate themselves substantially higher in terms of financial success than others do
http://boulderinsight.com/fostering-data-driven-culture/

 

Rich Wagner, President and CEO of Prevedere provides insight how do to take early moves:
Look forward, not backward: Go solve a business problem as "Executives needed to know what was going to happen, not what had already occurred."
Determine the question: Be clear on what questions are needed to understand or solve the Business Problem "Before searching for answers, it's critical to know what key questions your data should answer."
Rethink your data sources: Many familiar initiatives are internal data yet "I have found nearly 85% of a company's performance is dependent upon external factors" so how do you acquire this info?
Don't go it alone: Partner with vendors who have solutions.
Automate: If the experiment was a success, optimize to make it available as a real-time system.
Mind your presentation: Make answers "part of an existing process" rather than a new awkward bolt-on.

 

Project Teams can work to manage business disruption by following these guidelines and help their organizations transition into data-driven enterprises.

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How the Big Data Explosion Has Changed Decision Making

The Big Data Era balancing act between being open to stakeholder input on Data Governance  and being fast to innovation.

Hossenlopp's insight:

Intriguing Insights On How the Big Data Has Changed Decision Making 

 

I agree with Michael Schrage's HBR article that "Organizations I work with increasingly struggle to straddle two painfully polarizing operating principles. On the one hand, they desperately seek greater agility; on the other, they genuinely want to include all the right stakeholders in their processes."


How does that data get shared (inclusiveness)? And how does the organization effectively take advantage of that data (agility)?"

 

Also he applies this question to "digitalization, data, and analytics. Who has the right to access, process, and share data has become the greatest source of opportunity and contention in the enterprise.

 

This article provides a mobile app case study where product management strategy moved from Innovation to Customer Experience and used Decision Rights to dramatically improve organizational agility.

 

What are Decision Rights?
Schrage work refers to Jensens' work on the subtle and brilliant insight was that the right to make decisions — not just the ability to perform or be responsible for tasks — is essential to organizational efficiency and effectiveness. Consequently, assigning and allocating decision rights is every bit as organizationally important as defining jobs, roles, and tasks. In that light, decision rights can and should be seen as a managerial mechanism for empowerment. The greater your or your team’s decision rights, the more empowered and accountable you are.  Source: http://hbswk.hbs.edu/item/decision-rights-who-gives-the-green-light

 

"The RACI framework offers an excellent real-world instantiation of Jensen’s decision rights approach:

- Responsible. Who is completing the task?
- Accountable. Who is making decisions and taking actions on the task?
- Consulted. Who will be communicated with regarding decisions and tasks?
- Informed. Who will be updated on decisions and actions during the project/process?"

 

This article is a quick read and breaths new application life into the valuable RACI model.

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Use Big Data to Create Value for Customers, Not Just Target Them

Use Big Data to Create Value for Customers, Not Just Target Them | Analytics Project Management | Scoop.it

Excellent Read & Call to Action on need to manage to short term marketing project priorities yet to also ensure that the marketing portfolio includes experiments to ensure longer term competitive advantage. This article states "To build lasting advantage, marketing programs that leverage big data need to turn to more strategic questions about longer term customer stickiness, loyalty, and relationships."

Hossenlopp's insight:

Excellent Read & Call to Action on need to manage to short term marketing project priorities yet to also ensure that the marketing portfolio includes experiments to ensure longer term competitive advantage. This article states "To build lasting advantage, marketing programs that leverage big data need to turn to more strategic questions about longer term customer stickiness, loyalty, and relationships."

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Visualizations That Really Work

Visualizations That Really Work | Analytics Project Management | Scoop.it
Know what message you’re trying to communicate before you get down in the weeds.
Hossenlopp's insight:

As a project manager, have you ever stared at your screen and asked yourself "how do I present this data?"  Yeah - we have all been there. 

 

Focusing on data presentation is the wrong way to talk to yourself or your team. The important data visualization mindset is not about data wrangling, graphics or powerpoint, it is about the business message you want to share and what is the impact. 

 

This article has great insight on 4 types of messages, and suggests which visualization tools or models work best. Great insight when you need to either motivate team members or defend choices for presentations! 

 

Idea Illustration. We might call this quadrant the “consultants’ corner.” and these "illustrations clarify complex ideas by drawing on our ability to understand metaphors (trees, bridges) and simple design conventions (circles, hierarchies). Org charts and decision trees are classic examples of idea illustration."

 

Idea Generation. "Managers may not think of visualization as a tool to support idea generation, but they use it to brainstorm all the time—on whiteboards, on butcher paper, or, classically, on the back of a napkin. Like idea illustration, idea generation relies on conceptual metaphors, but it takes place in more-informal settings, such as off-sites, strategy sessions, and early-phase innovation projects."

 

Visual Discovery.  "This is the most complicated quadrant, because in truth it holds two categories.....This article divides exploratory purposes into two kinds: testing a hypothesis and mining for patterns, trends, and anomalies. The former is focused, whereas the latter is more flexible. The bigger and more complex the data, and the less you know going in, the more open-ended the work."

 

Everyday Dataviz.  "Whereas data scientists do most of the work on visual exploration, managers do most of the work on everyday visualizations. This quadrant comprises the basic charts and graphs you normally paste from a spreadsheet into a presentation. They are usually simple—line charts, bar charts, pies, and scatter plots."  

 

Very good food for thought as you are leading project teams in communicating with your stakeholders and leadership. 

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Big Data, Cloud Demand Drive IT Job Growth - InformationWeek

Big Data, Cloud Demand Drive IT Job Growth - InformationWeek | Analytics Project Management | Scoop.it
IT job numbers grew in July, but not as fast as they did during the rest of 2016. Yet big data and cloud trends will continue to drive job growth going forward, according to CompTIA researchers.
Hossenlopp's insight:

IT Project Manager is still one of the top 5 IT Job Posting Titles. Whoo Hoo. My perspective is that leadership views project management as adding value to project outcomes. Why? Because of our leadership in driving to project frameworks that provide agility and therefore the organizations' competitive advantage.  

My perspective is that leadership views project management as adding value to project outcomes. Why? Because of our leadership in driving to project frameworks that provide agility and therefore the organizations' competitive advantage.  

The market is seeing a hiring shift away from technology  to XaaS e.g., Everything as a Service and is looking to pick up talent with those skills.

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People.ai is using machine learning to rewrite the sales ops playbook

People.ai is using machine learning to rewrite the sales ops playbook | Analytics Project Management | Scoop.it
People.ai, a company bringing machine learning algorithms to sales operations, is emerging from stealth. The platform uses machine learning tech to give..
Hossenlopp's insight:

Remarkable start-up provides an example of combining multiple sources of information about the sales process to provide a dashboard of sales success.    

 

The details:

- Love that Y Combinator which is in my hometown is a startup accelerator based in Mountain View, CA. invests a small amount of money in a large number of startups (most recently 68). People.AI is part of their summer run.

- People.AI is working with 50 organizations to gain access to  email, calendar, phone, WebEx, conference tools and other data sources to automate what is a traditionally manual and error prone sales tracking process. Solution provides insight into  what deems to be the average best way to close a deal. So not only is the tech able to see what a salesperson did correctly, but also where they deviated from the playbook.

- The solution provides insight into what deems to be the average best way to close a deal. So not only are you able to see what a salesperson did correctly, but also where they deviated from the playbook.  

- This insight is providing a hugh amount of transparency and insight that hasn't been available before. This is a powerful value proposition. 

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Growth Hacking Simplified in 4 Steps

Growth Hacking Simplified in 4 Steps | Analytics Project Management | Scoop.it
There is a method to creating explosive momentum capable of taking your business off the ground quickly.
Hossenlopp's insight:

Growth Hacking Principals are critical Project Principals. Project Managers: Include in your charter and modify the iteration cycles to be Growth Hacking Friendly.

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Google Discovered These 3 Factors Make a 38 Percent Difference in Team Performance

Google Discovered These 3 Factors Make a 38 Percent Difference in Team Performance | Analytics Project Management | Scoop.it
Why the best team players beat all-stars.
Hossenlopp's insight:

Project Managers!  Google has data-driven advice for managing teams.

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Why Marketers Can’t Afford to Chase a Silver Bullet Strategy

Why Marketers Can’t Afford to Chase a Silver Bullet Strategy | Analytics Project Management | Scoop.it
Too many marketers chase a "silver bullet" strategy, in which a single tactic will address all their challenges. Here's what to do instead,
Hossenlopp's insight:

Project Managers can drive the creation of a customer journey map. Then they can work with stakeholders to understand key measurements (and data available) at each key touch point. This drives an analytics approach for Marketing Organizations.

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The 15 Best Free Project Management Apps

The 15 Best Free Project Management Apps | Analytics Project Management | Scoop.it
A blog about productivity, workflow automation, company building and how to get things done with less work.
Hossenlopp's insight:

First of All - Zapier is cool. Second - I need to try out more of these tips. 

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Microsoft Launches Online Data Science Degree Program - InformationWeek

Microsoft Launches Online Data Science Degree Program - InformationWeek | Analytics Project Management | Scoop.it
Microsoft is addressing the shortage of workers with data science skills with a new professional degree program offered online. The company said the data science degree will serve as a pilot for future offerings.
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How To Hire Analytical Workers: 10 Traits To Seek - InformationWeek

How To Hire Analytical Workers: 10 Traits To Seek - InformationWeek | Analytics Project Management | Scoop.it
Companies competing on data need the right skill sets and mindsets in place to succeed over the long term. While more individuals are analyzing data as part of their jobs, their ability to do so varies greatly, even among peers. We've identified 10 key traits of an analytical mind, and explain what to look for in your next hire and what skills to cultivate in your own career.
Hossenlopp's insight:

Good Focus on Mindset & not just CV toolkit of both project manager & technical analytics talent.

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Extracting Insights from Vast Stores of Data

Here’s how Amazon Prime, Heineken, and BuzzFeed do Analytics.

Hossenlopp's insight:

Do you ever see an article you wish you wrote? Well HBR article is it for me as I believe in chasing the business problem vs only looking at only the data & anticipating that it may provide insight. HBR agrees & counters the common wisdom of looking at data first to "find" insights and instead states that "Companies that have been successful in harnessing the power of data start with a specific business problem and then seek data to help in their decision making."  It then provides 3 examples; Amazon Prime, Heineken and Buzz Feed. A short yet powerful read!  https://hbr.org/2016/08/extracting-insights-from-vast-stores-of-data?

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Intelligent humans in Silicon Valley are keeping a wary eye on artificial intelligence - Silicon Valley Business Journal

Intelligent humans in Silicon Valley are keeping a wary eye on artificial intelligence - Silicon Valley Business Journal | Analytics Project Management | Scoop.it

Five tech titans — Alphabet, Facebook, Amazon, IBM and Microsoft — are forming a group to create a standard of ethics concerning artificial intelligence (AI). They aren't alone.

Hossenlopp's insight:

Today is Labor Day in the USA. We celebrate it by "not working."  Worried the robot overlords are coming for your job?  Five tech titans — Alphabet, Facebook, Amazon, IBM and Microsoft — are forming a group to create a standard of ethics concerning artificial intelligence (AI.) When us PMs are back to work, we should keep track of these trends and appropriately manage in our Risk Plans. Happy Farewell to Summer!

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How to Make Data Experiments Powerful

How to Make Data Experiments Powerful | Analytics Project Management | Scoop.it

This article provides two clear examples of how managers can move their projects and organizations to become data-savvy organizations. The fun of this Analytics article is that an example is from an industry that you wouldn't think of being open to IOT and Big Data!

 

Experimentation is powerful when it deepens managerial intuition. The first example asks teams to runs lots of tests and to ask how each one impacts the organizations key performance indicators (KPI's.)  So the team has to look at all the "touchpoints, the task completion, metrics, more deeply than have they had in the past. Managers can quickly test their insights, either validating their thinking or sending them back to think more, then swiftly bring changes to scale.This really changes the team culture and how they look at analytics. 

 

Experimentation is powerful when the organization has unique data. The next example looks at a laundry operations that has a unique set of data and opportunities for introduction of IOT to collect data. "This organization has made it easy, both technically and culturally, for managers to test ideas and learn from them."

 

This is an easy read and a big win for project managers looking for examples of how to implement Analytics Projects. 

Hossenlopp's insight:

This article provides two clear examples of how managers can move their projects and organizations to become data-savvy organizations. The fun of this Analytics article is that an example is from an industry that you wouldn't think of being open to IOT and Big Data!

 

Experimentation is powerful when it deepens managerial intuition. The first example asks teams to runs lots of tests and to ask how each one impacts the organizations key performance indicators (KPI's.)  So the team has to look at all the "touchpoints, the task completion, metrics, more deeply than have they had in the past. Managers can quickly test their insights, either validating their thinking or sending them back to think more, then swiftly bring changes to scale.This really changes the team culture and how they look at analytics. 

 

Experimentation is powerful when the organization has unique data. The next example looks at a laundry operations that has a unique set of data and opportunities for introduction of IOT to collect data. "This organization has made it easy, both technically and culturally, for managers to test ideas and learn from them."

 

This is an easy read and a big win for project managers looking for examples of how to implement Analytics Projects. 

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The New IT: Driving Business Innovation With Tech - InformationWeek

The New IT: Driving Business Innovation With Tech  - InformationWeek | Analytics Project Management | Scoop.it
Andi Mann, chief technology advocate at Splunk, sees major changes afoot in how IT and business are aligning.
Hossenlopp's insight:

I believe that Business Leaders don’t want Organizational Project Management (OPM,) they want the benefits which OPM can provide. Andi Mann, chief technology advocate at Splunk, provides a 4 minute blog which through our project management lens provides validation of the value of OPM without using our language. Big Takeaway - Talk the language of business & innovation and don't force executives to translate our project management language.

First Andi Mann https://twitter.com/andimann indirectly defines OPM: “Connecting IT delivery directly with business goals is enabling the company to make data-driven technology decisions, creating measurably better business outcomes.”

Second Andi combines both technology and business approaches. He states “To stay competitive:
- organizations need to drive innovation, not only with their products and services, (for example Cloud and common Data Fabric) but
- also in business approaches and finding new strategies to exceed business goals.” (for example Dev Ops)

He also indirectly summarizes OPM benefits. “Aligning IT with business goals from the get-go gives companies a competitive edge and sets the standard for success.”

Great short read for any project management professional.

http://www.informationweek.com/devops/the-new-it-driving-business-innovation-with-tech-/a/d-id/1326123?

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Data Generation Gap: Younger IT Workers Believe The Hype - InformationWeek

Data Generation Gap: Younger IT Workers Believe The Hype - InformationWeek | Analytics Project Management | Scoop.it

There's a growing generation gap when it comes the promise of revenues from data-driven projects. Where younger workers see the future, older workers may only see another cycle of tech hype.

Hossenlopp's insight:

Project Managers can help bridge the communication gap when new Big Data and Analytics initiatives are launched.  According to an IDG Enterprise  study younger staff generally believe the transformational project benefits while seasoned employees have been through many hype cycles & may have more questions about project value.

 

Why is this discussion important?   There are a lot of data-driven transformation projects in the works! IDG Enterprise states that 53% of companies surveyed are currently implementing, or planning to implement, data-driven projects within the next 12 months. Data-driven projects as those launched with the goal of generating greater value from existing data.

 

My thoughts are that Project Managers can work with key Team Members to ensure that projects are:

- linked to strategic objectives

- the value chain of activities or the customer touch points are identified

- understanding of how project features will help these challenges are clearly identified in the roadmap

- user education and socialization of the technologies used is part of the project plan

 

All these actions drive understanding of the project value & transparency of benefits. This ensures non-hype communication to all stakeholders, regardless of age, geography, and role.

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4 intelligent elements of successful digital transformation | Information Age

4 intelligent elements of successful digital transformation | Information Age | Analytics Project Management | Scoop.it
Don’t flirt with digital – give it the respect it deserves. Those who don’t act will fall behind quickly
Hossenlopp's insight:

Digital transformation is a whole-scale change to the foundational aspects of a business – from the business operating models to infrastructure – through the application of digital technology.

In Sopra Steria’s recent survey of 120 FTSE 500 companies, the majority (64%) said they implemented digital projects to update their existing legacy infrastructure, streamline processes and reduce costs.

 

However, many (60%) also said they are seeking to increase customer engagement by improving the experience they offer their customers.

 

But according to research by Sopra Steria, it is not necessarily a determinant of success – 84% of organisations confess they could be better exploiting digital.


There are four intelligent elements that form the basis of a rewarding relationship with digital.

 

1. ‘Deep thinking’ about the business context
Always make sure you have a clear understanding of the business goals you are pursuing.

2. Commitment to ‘sustained value’
Deliver results – however minimally viable – early and keep focusing on building outcomes forever. There is no steady state.

3. Rely on ‘networked knowledge’
Build a platform of partners that will enable you to get the best help when you need it.

4. See your relationship with digital in terms of building a ‘fluid enterprise’
A successful digital venture is agile, lean and able to adapt to the future demands of business change.

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Big data vs. the Internet of Things: how the projects differ | Information Age

Big data vs. the Internet of Things: how the projects differ | Information Age | Analytics Project Management | Scoop.it
What do you call big data on steroids? The Internet of Things
Hossenlopp's insight:

Buzz words abound in Big Data. Excellent & Quick 2-minute article describing how Big Data and IOT are different.  

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Why Centers of Excellence are No Longer Optional in the Digital Era – CMO Nation

Why Centers of Excellence are No Longer Optional in the Digital Era – CMO Nation | Analytics Project Management | Scoop.it

Analytics is driving changes in project governance in marketing teams.  #pmot #analytics

Hossenlopp's insight:

Analytics is driving changes in project governance in marketing teams. 

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The Hidden Side Effects of Using Big Data to Better Understand Your Customers

The Hidden Side Effects of Using Big Data to Better Understand Your Customers | Analytics Project Management | Scoop.it
Learn what common pitfalls to avoid when using big data to improve customer service and grow customer relationships
Hossenlopp's insight:

Analytics Project managers! Outstanding overview of use cases and challenges of working with Big Data.  And an amusing definition of Big Data -> hint - its messy:-)

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The New York Times is trying to narrow the distance between reporters and analytics data

The New York Times is trying to narrow the distance between reporters and analytics data | Analytics Project Management | Scoop.it
It's building on its in-house analytics dashboard, Stela, with the goal of making audience engagement data easy to find, simple to understand, and even fun to use.
Hossenlopp's insight:

Compelling Analytics Use Case and walk-through of how and why they built out a tool. Outstanding story!

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8 Smart Ways To Use Prescriptive Analytics - InformationWeek

8 Smart Ways To Use Prescriptive Analytics - InformationWeek | Analytics Project Management | Scoop.it
Somewhere between blind faith and skepticism is the world of prescriptive analytics. Here, machine-generated action items and potential outcomes meet human decision-making.
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Majority of IT firms unprepared to tap digital disruptions: Gartner

Majority of IT firms unprepared to tap digital disruptions: Gartner | Analytics Project Management | Scoop.it

Read more about Majority of IT firms unprepared to tap digital disruptions: Gartner on Business Standard.

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