For over 3 decades, my passion has been to assist organizations leverage the business potential of data and analytics and help them envision where and how data and analytics can generate new sources of customer, product and operational value. Maybe my fascination with data and analytics started in my youth with “Strat-o-Matic Baseball” but it certainly caught fire at Metaphor Computers in the 1980’s where I built some of the early Business Intelligence and data warehouse systems. In the 1990’s I joined Sequent Computers where I developed the “Business Benefit Analysis” methodology – a precursor to the “Thinking Like a Data Scientist” methodology. Then at Business Objects, Yahoo, EMC, University of San Francisco, National University of Ireland – Galway and now at Hitachi Vantara, I’ve had the good fortune to work with customers and students to continuously test, tweak and refine the methodology. All of my learnings are captured in my new book “The Art of Thinking Like a Data Scientist.”

Thanks for your joining me on this journey.


A prioritization matrix is a business process analysis tool, often used alongside other bpm software or Six Sigma techniques for comparing choices using specific criteria, and figuring out what to prioritize. It can be applied to anything, from simple tasks to complex projects, by anyone, from single individuals to large organizations. The Big Idea prioritization matrix is probably the most frequently used prioritization chart, plotting User Value against Feasibility. Xindeling Pan is a Product Designer & Design Thinking. Mind Maps are a great technique to organize information, connect related ideas,. The 2 x 2 Prioritization Matrix template will help visualize your ideas so you can make clearer decisions. If you are still working with your group to decide what problems you need to solve (and therefore which need to be prioritized accordingly), you might want to start your meeting with the Problem Statements exercise before you get to the 2 x 2 prioritization matrix. Tool: Eisenhower Matrix (prioritization) by gosia Jul 20, 2020 President Dwight D. Eisenhower was a General in the US Army, then Allied Forces Supreme Commander during World War II, and later the 34th President of the United States (1953–61, serving two consecutive terms), is the namesake of the priority matrix.

To survive in today’s digital economy, it’s imperative for organizations to convert their key business stakeholders into “Citizens of Data Science.” Meaning, they should not only understandwhereand howto apply data science to power the business, but champion adata-first approach toward decision-making across the entire organization.

That’s the subject my new workbook, “The Art of Thinking Like A Data Scientist”, seeks to accomplish. It’s designed to be a pragmatic tool that can help your organization leverage data and analytics to power its business and operational models. The content is jammed with templates, worksheets, examples, and hands-on exercises — all composed to help reinforce and deploy the fundamental concepts of “Thinking Like A Data Scientist.”

The workbook is comprised of six chapters. Chapters 1, 2 and 3 set the business, data science and design thinking foundation. Chapter 4 covers the “Thinking Like a Data Scientist” methodology in detail, including an example. Chapters 5 (Hypothesis Development Canvas) and 6 (Prioritization Matrix) cover two critically-important components of the methodology. A more detailed delineation of the content in each chapter is listed below.

Chapter 1: Big Data Business Model Maturity Index

Chapter 1 sets the stage for the entire book and addresses the question “How effective is your organization at leveraging data and analytics to power your business models?” while providing a benchmark for an organization to measure itself. The chapter concludes with a series of exercises to help determine not only where your organization sits vis-à-vis this benchmark but provides a roadmap to become more effective at leveraging the business potential of data science.

Chapter 2: Understanding the Basics of Data Science

To become more effective at leveraging data and analytics to power your organization’s business models, business stakeholders need a solid understanding of what data science can accomplish. This chapter explains the realm of what’s possible with data science, a layman’s definition of data science (identifying those variables and metrics that might be better predictors of performance), the data science development process, and how business stakeholders – “citizens of data science” – can contribute to an organization’s data science effectiveness.

Chapter 3: Design Thinking Humanizes Data Science

Design Thinking and Data Science share many similarities in delivering meaningful, relevant and actionable outcomes within non-linear work environments. Design Thinking exploits the power of might in fueling data science and business stakeholders’ (and subject matter experts) collaboration to identify variables and metrics that might be better predictors of performance. Design Thinking helps drive organizational alignment and adoption around the analytic results. Design Thinking truly does humanize data science.

Chapter 4: The 'Thinking Like a Data Scientist' Methodology

Ah, the heart of the workbook, the actual methodology itself. This chapter details the 8-step “Thinking Like a Data Scientist” methodology, provides templates, and walks through a detailed example for the reader to readily apply this methodology to help their organizations identify where and how data science can be the source of differentiated customer, product and operational value.

Chapter 5: Hypothesis Development Canvas

Chapter 5 focuses on the most critical output or deliverable from the “Thinking Like A Data Scientist” methodology – the Hypothesis Development Canvas. The Hypothesis Development Canvas codifies the collaboration between the data science team and the business stakeholders to ensure that the data science team has the necessary details to deliver meaningful business impact and relevance. This topic includes details about the targeted use case including use case business or operational objectives, the metrics and KPI’s against which progress and success will be measured, the key stakeholders who have a vested interest in the targeted use case, the entities around which analytics will need to be built, the supporting decisions and predictions, and finally, the costs associated with use case False Positives and False Negatives.

Chapter 6: The Prioritization Matrix Process

The workbook concludes with the single most important tool that I’ve found in driving organizational alignment and adoption of the resulting analytics – the Prioritization Matrix. The Prioritization Matrix process leverages several Design Thinking techniques not only to align the key business stakeholders around which use case(s) the data science team should focus but seeks to tease out the passive-aggressive behaviors that doom so many well-intended data science projects. At the end of the day, you can build the world’s most effective predictions, but if no one puts them to use, nothing is gained.

I hope you enjoy the workbook. It’s one of my steps on the path in teaching business stakeholders to “Think Like a Data Scientist,” a culmination of lessons-learned working with clients for many years.

You can pick up your copy of “The Art of Thinking Like a Data Scientist” workbook here.

I look forward to hearing from you with your observations and learnings.

Thanks!

As an entrepreneur, one of the hardest things to figure out is “What should I work on?” This is also true while working for someone else, but for those of us on our own, it can seem even more daunting.

Here’s a quick strategy I use when trying to figure out what to work on; I call it the Prioritization Matrix.

Step 1: Create a list.

Prioritization matrix worksheet

You should already have a task-list of things you want to / could do floating around in Evernote, Trello, or any of the thousands of To-Do list apps. That’s great, but for this exercise, start a new list.

Off the top of your head, name 10 things you could be working on. I recommend listing off the top of your head versus reviewing your existing lists because these are the things that are top of mind, and, at least for me, tend to be the things that are most important because I’ve been thinking about them recently.

For me, while writing this article, my list looks like:

Wow, that’s a lot that I could be doing. All of which (save #10), could contribute to my business in some way. It’s at this point you might start to feel overwhelmed, but worry-not, just move to step 2.

Step 2: Assign value to each task.

Now, with the list in front of you, assign value from 1-10 (10 being the highest) to each of the tasks you’ve come up with.

You have to determine what drives value for you; is it exposure, credibility, money? Hint: as an entrepreneur, money is a good one.

As you can see, this isn’t a ranking of the list, so it’s OK if two or more entries have the same value ranking. Now if they all have the same value, you have to be more honest with yourself as to which are truly the most valuable.

Step 3: Assign difficulty to each task.

The next step is to think about how hard each task is going to be to complete and assign it a number from 1-10 (10 being the hardest).

Note that the difficulty assignment should be based on your ability (and motivation) to do it. It doesn’t matter if entering numbers in a spreadsheet is technically easy, if you despise it and find it a challenge for you to complete, then give it a hard ranking.

Step 4: Calculate the priority score.

Once you have both a Value and Difficulty score for each task, calculate their priority score by dividing the Value by the Difficulty.

So, for example, if a task has a Value of 8 and a Difficulty of 4, the Priority score is 2.0.

Step 5: Re-order the tasks according to score.

Design Thinking Prioritization Matrix Example

The final step is to re-order your list of 10 things to do by Priority Score, with the largest value going up top. Congratulations, that’s the task you should be working on.

A Few Notes About the Process

Project Prioritization Criteria Matrix

The whole point of the Prioritization Matrix is to make the process of prioritizing tasks a lot easier. That being said, there are a few things to consider:

  • The value of the Matrix is that it takes a look at both Value and Difficulty. Just because a task is valuable, doesn’t mean it’s the right thing to work on at that time (or for you to do it at all, see below). Just because a task is easy (such as watching Rick and Morty) doesn’t mean it’s where you should focus your efforts. Productivity lies in finding the tasks that are valuable and easy enough to do that you actually do them.
  • Just because something has a score < 1.0 doesn’t mean it’s not worth doing, it just means that it’s harder for you to do than the value you can get out if it. If it’s not a task you’re willing to delete (aka not do at all), it means it’s a perfect task to consider outsourcing or delegating to someone else. For example, determining my Perfct Day app strategy is very valuable, but it’s hard for me to decide. So I’m going to request assistance from some smart friends to help me figure it out.
  • This is just one way to think about the work you need to do. If through this exercise you realize you really want to work on Task #2 instead of #1, great, do that. That you do something is better than what you do.

I hope that helps you with the prioritization process. You can find an example copy of the spreadsheet I used here: Prioritization Matrix Example. Share any feedback or questions in the comments.

Example Prioritization Matrix For Accounting

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