The Fallacy of Laying Flat: The Fuzzy, Hairy Truth About Data Decisions Making

The Fallacy of Laying Flat

The Fallacy of Laying Flat

The Fuzzy, Hairy Truth About Data Decision Making

Colette Grail

New Degree Press

Copyright © 2022 Colette Grail

All rights reserved.

The Fallacy of Laying Flat

The Fuzzy, Hairy Truth About Data Decision Making

ISBN

979-8-88504-330-4 Paperback

979-8-88504-407-3 Kindle Ebook

979-8-88504-408-0 Ebook

To my mom and dad.

For all that data out there wanting to be valued.

Contents

Foreword

Any idiot can write a book.

Introduction.

(Why) Your Organization Needs Big Data Strategy

Part 1.

What Are We Talking About? 

Chapter 1.

WHAT IS THE BIG (DATA) DEAL?

Chapter 2.

The Fab Five

Chapter 3.

It’s Not the Same

Part 2.

How the Data Got Here 

Chapter 4.

Data Input (Forms > Spreadsheets > Databases > Apps)

Chapter 5.

User Interface

Chapter 6.

Data Output (Reports > Dashboards > Models > Apps)

Part 3.

What Is Out There 

Chapter 7.

Big Data & Your Vote

Chapter 8.

Big Data & Your Bank Account

Chapter 9.

Now You’re Talking—Chatbots

Part 4.

What is Possible

Chapter 10.

Rubber Meets the Road—Creating Big Data Systems

Chapter 11.

Fire the Admin Group 

Chapter 12.

Is This Mission Control?

Chapter 13.

The Corner Office 

Chapter 14.

You Are Who You Say You Are

Chapter 15.

What Does Your Medical Record Say About You? (And Who Is Reading It?)

Part 5.

Stepping Back to the Problem Space

Chapter 16.

ONE—A Point in Time

Chapter 17.

TWO—The Plan

Chapter 18.

THREE—Out of the Plane and into the Fire

Chapter 19.

FOUR—A Stitch in Time

Chapter 20.

No, Really: (Why) Your Organization Needs Big Data Strategy

Afterword

Acknowledgments

Appendix

Foreword

It gives me immense pleasure to pen the foreword for this amazing new book by Colette Grail which, from the very first page, exudes her enthusiasm, excitement and vision for Big Data.

This book is fundamentally about connection. Connecting readers around the globe with this exciting subject with so many possibilities. And through its pages, connecting those who ‘get it’ about Big Data.

I was privileged to connect with Colette more than a decade ago, and I have over the years observed first hand her passion for Big Data, culminating in her researching and writing this exciting and thought provoking book. From an initial introduction to Big Data over a glass of red wine in Cape Town at the southern tip of Africa, to detailed discussions delving into the opportunities and prospects for Big Data over dinner on the other side of the Atlantic in Norfolk, Virginia, Colette has always exuded her passion and excitement for her subject and the many and varied possibilities that Big Data offers.

A Navy veteran with broad experience at home in the US and abroad, Colette has always impressed me with her amazing ability to read, observe and absorb. The results of this talent, her experience in studying and reporting on emerging technology, together with her passionate belief in Big Data and all that it has to offer, comes out strong and true in the pages of this book.

As the world gets more complex, and we leave small data thinking behind, the power, capability and possibilities of Big Data to solve many of the world’s problems is immense and limitless. I unreservedly commend this thought provoking book to you, and hope that you will be enriched, challenged and energised by Colette’s passion for her subject, and that you too will ‘get it’ about Big Data.

Dr Allan du Toit, AM

Rear Admiral, Royal Australian Navy (Rtd) University of New South Wales, Canberra Australia

August 2022

Any idiot can write a book.

Europe is famous for street-side cafés, and Italy by extrapolation is further known for its romantic vine-covered alleys laden with almost doll-like tables and chairs. Awkwardly placed too close together by American standards, they’re nonetheless perfect by design for meeting new people. Naples has its own archetype for this phenomenon, and in the social and fashion epicenter of Naples is an awkward but romantic section known as Chiaia. Pop-up wannabe designer stores nestle with posh clothiers within the alleys and intersections of the thousand-plus-year-old streets. I’d see women in heels walk cobblestone streets that were hazardous even for my running shoes. I couldn’t help but think they’d at least twist an ankle, let alone the worse fall potential. But they did look good. That was the point. Va bene.

That’s where I met Michael, a Swedish doctor who specializes in sports and preventive medicine. His noteworthy passion for preventive health also included the potential of big data. Enjoying happy hour drinks and tapas for which Naples is famous, we spoke at length about the opportunities for better data decision-making, but as for writing a book, he contemptuously quipped, Any idiot can write a book. (By the way, he coedited a book himself.)

I’m not an expert. So, I thank Michael for the conversations and glasses of wine and his cynical view on being an author, because nonetheless it inspired the idiot in me to write this book.

The far greater Michael who inspired me, though, was Michael Faraday. I regret we couldn’t share a glass of wine, but he lived to seventy-five years old before his death in 1867. Every electric motor, generator, or transformer owes its invention to the work of Michael Faraday. He was the founder of electromagnetic theory and inventor of the electric motor, which is used in everything from cars (gas and electric) to airplanes and industrial power plants. Although I’m sure someone would have figured out how magnets have opposite poles and how the magic of attraction and repulsion could create components that make the motors that are the base of so much of industry, it was Faraday who was obsessed and now those electric parts fill our world. He even has a unit of electricity named after him: The International System of Units capacitance is measured in farads. 

And he couldn’t do the math.

Michael Faraday was a Marvel hero in his own right. An underdog who could not afford formal education, he had no network of collegiate or industry support, nor any fortunes to invest. Nonetheless, he had an idea, and he wouldn’t let it go. Those ideas first came to life in charcoal drawings, not classrooms or laboratories. In his youth, he spent seven years apprenticing at a bookbinder and book sales shop, where he fortunately was able to read a great deal. He spent a year attending lectures of acclaimed chemist Humphry Davy. Michael took careful notes and presented those as a 300-page book to the lecturer. When one of Davy’s assistants was fired, Michael got his shot, and eventually those ideas made it to the laboratory (Encyclopedia Britannica, 1911).

His work and his genius became famous, and he would go on to become the first academic chair for the Fullerian Professor of Chemistry at the Royal Institution in London, a lifetime position. But through all those accomplishments, the math was too much; his studies barely broke into trigonometry. As his work evolved, though, the rigor of calculations would only slow down the inventions, so another soon-to-be-famous inventor James Clerk Maxwell stepped up to do the math for him (Nivin 2010).

As for me, I don’t have a PhD. I’m not a CEO or CIO or in any other C-suite position. I’ve done long-distance learning for certificates and an MBA, and I’ve almost completed several Coursera topics. Mostly, though, I read. And I observe.

In the bleachers and on the bench

My laboratory for thirty years was the US Navy. I served on five major staffs covering five continents. I’ve stood the watch in various parts of the world, including back home in the United States during the onset of pandemic. I’ve developed plans, policies, and strategies as well as the briefs and spreadsheets that describe the effect, the opportunities, and the risks. I served in the Pentagon doing capability assessments—working issues at the top level that must account for all levels, from those occurring at the moment to reaching out in the Future Years Defense Plan. The FYDP covers prior year, current year, budget year, and the following four years (i.e., the outyears) (Defense Acquisition University, 2022).

I’ve seen enough to know that no one person is an expert as much as they think they are. Conversely, if you dig in deep enough to your expertise, you lose perspective. Like a Roman historian once observed (that has survived to be reread), you can’t write history while you are living it. Immerse yourself in any subject too far, and you are likely to get lost with your head down. But that expertise is still needed. I truly mean for this book to be so outrageous at times as to border on fiction. I hope that will make enough sense to move mountains. And I believe Herculean efforts are needed.

Part of this book is pointing out the divot into which organizations have fallen regarding data utilization. In studying and reporting on emerging technology, I think understanding big data is the plight of many if not most organizations, corporations, and individuals.

This isn’t an exposé of any sorts. This book is delving into the future of possibilities.

Laying flat

Laying flat is jargon used in my Navy staff days to describe getting a situation under control or understood. Before tasking a mission or operation to another entity, we would want everything laying flat. If I’m describing a new capability that you can use, everything should be laying flat so you understand the whole product at the end of the discussion and what your participation requires.  

Picture an old, sizeable map stretched out on a table. It describes a terrain and any accompanying features or bodies of water. It’s used to get from here to there, and possibly, it shows the way to buried treasure. A map is a representation of how you can get to what you want. It could be an annual operating plan, a marketing schema, a budget, a cyber sprint, or any number of business products. Laying flat is building and using those products to reach a desired effect.

The Fallacy of Laying Flat is the dependence on those documents, that fall short of capturing those dimensions of business, life, war, and famine which we fail to perceive and prepare. The complexity and divergence of the real world isn’t captured in a map, although we often act as if it does. The good news is much more data is available to make better products, and the ability to utilize the data is growing. The crutch is using the same Microsoft Office products with which everyone is more comfortable. It’s a self-driven limitation, but the risk from not understanding big data and all data usage in a more comprehensive and complex context, though, leads to catastrophe, such as how to respond to a pandemic or assuage the rising effects of extreme weather.

The map itself is the way, but it is also a classic planning conundrum. Strategists and tacticians are warned to not confuse the map with the territory. The map is merely a representation of real life. It isn’t reality. 

Introduction: 

(Why) Your Organization Needs Big Data Strategy

Big yellow cab

The last taxi I took was in New York City circa 2012. (Uber started operations in the Big Apple in 2011.) A friend and I were gearing up for a weekend getaway and took a cab from the airport to Manhattan. I remember the back windows were rolled down, despite not wanting the city air blasting through. An annoying television monitor blared infomercials and advertisements to see tourist sites and restaurants. Finally, the quintessential question lingered over the entire ride to Manhattan: How much will this cost? In a cab, you never know until you get there. I remember thinking how rude the whole taxi experience was… but wasn’t that just NYC? 

Now, I could rail about how Uber transcended a business model to fill a demand signal for better transportation services, but that’s been covered already many times over by much smarter people. No, I’m using Uber as an example because it’s so familiar. Uber makes it easy to understand and identify how and why big data works. Uber doesn’t pay for the big data that lets you know your car is three minutes away, although it does spend to keep the systems and apps in top performance. Uber leverages the big data available, combines it with tremendous algorithms of its own, and delivers a service that exceeds your expectations. 

Uber tells you how much a ride will cost before you even choose to use the service! It tells you how long until the car arrives and shows its GPS location as it travels toward you. It stores your payment information, so you don’t have to worry about having taxi fare (not having cash for a cab really used to be a big thing). The cars are immaculate and the drivers are friendly. Why? Because customer service is intimately entwined in the product. How does technology influence how nice the driver wants to be? The feedback for the experience—both provider and recipient—is tracked so precisely to weed out participants who don’t abide by the rules and courtesies. An Uber driver can’t have a couple bad days of rudeness or an uncleanly car; the ratings would boot them down to last in the queue. 

It’s not digitizing a bad process; it’s using big data to make a service 1,000 percent better. Your organization needs this, or it will be like a cab: an obnoxious, obsolete, dirty reminder of what failed to get the point of big data.

Virtual paper drill

We make a lot of documents. Businesses and the government make documents to say what they’re going to do. Then they make documents to say what they’ve done. The business of doing business is wrapped in that Microsoft Suite of documents, spreadsheets, and presentations. Vision, mission, values, lines of effort, goals, objectives, and action items are all spelled out in documents, then regurgitated into more documents like standard operating procedures, annual operating plans, strategic plans, and policies. Those documents require briefs to explain what’s contained in them. Rounding those words out are the numbers in spreadsheets, where the gold is counted, and those again require more briefs to explain the numbers. At the end of the year the annual reports combine all the above—words, pictures, and accounting—into PDFs for more reconciliation and explanation. Blah, blah, blah… All the documentation becomes a chokehold on our world.

To do business and to make more documents, we collect information. It’s a painstaking and expensive process, and it’s perceived as necessary to gather data. Filling out forms or surveys. Applications or receipt of funds. Requests for information. A small data world using discrete data capture works with push. Push out the request for specific data and then suck it back in for