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[Book Proposal] Win The Data War: How normal people can survive and thrive in the data abundance era

Book publishers, please contact: Jeff Hulett, or 703.269.8811


There is a gap between how most people use data and the practice of data science.  The tech world has an unsavory drug culture-inspired name for their customers --- you are known as a "user."   Then, to complete the analogy, a tech company could devolve into being a "dealer" or a "pusher."  A tech company focuses on the "user interface" when operating a smartphone and the "user experience" driving the app’s "user engagement.”  Of course, tobacco companies use the same language.  However, instead of smartphones and apps delivering data, tobacco companies use cigarettes to deliver nicotine.

The challenge is that data, unlike nicotine, cannot be avoided.  Data is at the core of how our brain functions.  Data is necessary for life.  The statistics taught in school are not as useful as they could be to guide individual "users" to make the most of data in the real world.  This book provides the bridge.  After walking the bridge, you will receive decision confidence via a practical and intuitive statistical understanding.  Your decision confidence is fortified by tools from data science and business practitioners.  Many resources are furnished to help you dig deeper and make the language of data your Information Age superpower! 

Yes, I have been on the dealer side.  But now it is time to help the users fight back with data and decision-making confidence.

We will explore gaining knowledge from data by harnessing the power of statistics.  Statistics is the language of data.   A statistical language starting point is provided by building upon the time-tested statistical moments framework.  It shows why learning the world through the data lens is helpful and increasingly necessary.

Just like grammar rules for language, statistical moments are essential for understanding our data-informed past as a guide for navigating the future.  As those statistical grammar rules become routine, you will effectively understand the data defining our world. This understanding grows to be a permanent feature guiding your success.  Data, as representing our past reality, contains nuance, exceptions, and uncertainties adding context to that historical understanding.  The statistical moments framework helps unlock the power of our data.

We begin by making the case for data and why learning the language of data is important.  Tools, called 'personal algorithms,' are introduced to help you transform your data.  Then, we will jump into the major statistical moments' building blocks.  Intuitively understanding these moments provides the data grammar and a path to understanding your past reality.  The path includes an approach to identify and manage inevitable uncertainties and potential ignorance.   Context-strengthening examples and historical figures are provided from science, personal finance, business, and politics. 

With the help of two science giants, Thomas Bayes and Vilfredo Pareto, several examples are provided to supercharge personal algorithms in your life. We wrap up with a practical example, strategies to overcome A.I. and achieve long-term health and wealth.

Table of Contents:  The Data Explorer's Journey Map

Part I - The case for data and winning the data war

  1. Data and algorithms are different

  2. Choice architecture and personal algorithms

  3. Data is the foundation

  4. From data scarcity to data abundance

  5. Our past reality is diverse

  6. Tricky samples and cognitive bias

  7. Being Bayesian and the statistical moments' map

Part II – The data foundation and the statistical moments

  1. Don't be a blockhead → 0th moment: unity

  2. Our central tendency attraction → 1st moment: the expected value

  3. Diversity by degree → 2nd moment:  the variance

  4. Momentum's measure → 3rd moment: the skewness

  5. The tale of tails → 4th moment: the kurtosis

  6. Fooling ourselves, a moment of ignorance

Part III - Challenging Our Beliefs: How to be Bayesian in our day-to-day life

  1. How to think like a Bayesian

  2. Uncertainty, free will, and belief updating

  3. The belief bucket

  4. Bayesian inference – the general approach

  5. Bayesian inference example – Should Mia seek a new job?

  6. Beyond Bayes - using the app to implement the best decision process

  7. The next performance review

Part IV - Our Trade-off Life: How Pareto’s 80/20 rule leads to a healthier, wealthier life

  1. Today, we are not naturally good decision-makers

  2. A Healthy Trade-off: Use Pareto’s 80/20 rule to set achievable "just do it" objectives

  3. Pareto and personal finance

  4. Pareto and personal health

  5. Pareto and an injured loved one

  6. Pareto and marriage

Part V - Overcoming The AI: Making the best decisions in our data-abundant world

  1. Create statistical habits without being a statistician

  2. Strategies to overcome the AI - A pet perspective

  3. The connection to personal finance

  4. Resources and personal algorithm best practices

Conclusion – The Effort Yields Its Own Reward

Appendix – A deeper dive into the statistical mathematics


Draft materials: 


Part I and Part II

Available upon request


Part III

Available upon request


Part IV

Available upon request


Part V

Available upon request


Please note:  Additional content citations and links are found within these primary draft articles.

Author Bios:


Jeff Hulett is a career banker, data scientist, behavioral economist, and choice architect. Jeff has held banking and consulting leadership roles at Wells Fargo, Citibank, KPMG, and IBM. Today, Jeff is an executive with the Definitive Companies. He teaches personal finance at James Madison University and leads Personal Finance Reimagined - a personal finance and decision-making organization. Check out his latest book -- Making Choices, Making Money: Your Guide to Making Confident Financial Decisions -- at


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