Praise for The Visual Organization“The sheer amount of data coming at us these days is overwhelming companies both small and large. It’s no wonder that so many miss out on the opportunities right in front of them. The Visual Organization manifests how a wide range of companies is leveraging new and powerful visual tools. Read it and turn your company into a more efficient, data-driven, decision-making machine.”
Frank Gruber, CEO & Co-Founder, Tech Cocktail; Author of Startup Mixology
“There is data everywhere, but how many of us actually use it to drive our work? People learn in different ways, and for many a visual approach is most powerful. Unfortunately, most organizations have overlooked the opportunity in the visual presentation of data. With The Visual Organization, no longer is there an excuse for doing so. Simon offers a nuanced and refreshing view on contemporary data visualization through compelling storytelling, and yes, great visuals.”
Terri L. Griffith, Chair, Management Department, Santa Clara University; Author of The Plugged-In Manager
“There’s good news in this dazzling book. Yes, Big Data is overwhelming, but progressive organizations have found a way to identify the signal in its noise. Through a mix of analysis and synthesis, Simon demonstrates how it’s possible to see not only the forest, but the trees.”
Brad Feld, Co-founder and Managing Director, Foundry Group; Co-author of Startup Life
“As we’ve come to expect from him, Phil doesn’t just write about a topic. Instead, he explores it deeply, connecting it to the business, technology, and societal world around us. Somehow he has the uncanny knack to offer sage advice for both IT and business professionals–this time about visual data expression–and bedeck it in a fantastic narrative.”
Douglas Laney, Research Vice President, Information Innovation, Gartner
“It’s now critical to display data in ways that leverage our human visual capabilities and empower us to discover predictive insights from data To that end, The Visual Organization is essential reading.”
Eric Siegel, Founder, Predictive Analytics World; Author of Predictive Analytics
“It’s clear that Big Data is transforming business. Less clear until now, however, is how companies can fully leverage its power to generate breakthrough insights Phil Simon’s deft exploration of data visualization will change the way you see the world.”
Dorie Clark, Author of ReinventingYou; Adjunct Professor, Duke University Fuqua School of Business
You need not be a data scientist to present data well. Professionals can—nay, must—represent their data in a persuasive visual format. This book will help them do just that. The book will walk the reader through the current landscape of options available for data visualization tools, such as Tableau, Ease.ly, and others. It will discuss common mistakes people make when presenting data and include in depth real-world examples to show readers what groundbreaking data visualization looks like and the impact it can have.
The era of Big Data as arrived, and most organizations are woefully unprepared. Slowly, many are discovering that stalwarts like Excel spreadsheets, KPIs, standard reports, and even traditional business intelligence tools aren't sufficient. These old standbys can't begin to handle today's increasing streams, volumes, and types of data.
Amidst all of the chaos, though, a new type of organization is emerging.
In The Visual Organization, award-winning author and technology expert Phil Simon looks at how an increasingly number of organizations are embracing new dataviz tools and, more important, a new mind-set based upon data discovery and exploration. Simon adroitly shows how Amazon, Apple, Facebook, Google, Twitter, and other tech heavyweights use powerful data visualization tools to garner fascinating insights into their businesses. But make no mistake: these companies are hardly alone. Organizations of all types, industries, sizes are representing their data in new and amazing ways. As a result, they are asking better questions and making better business decisions.
Rife with real-world examples and case studies, The Visual Organization is a full-color tour-de-force.
The VISUAL ORGANIZATIONData Visualization, Big Data, and the Quest for Better Decisions
Thoreau once said, “It’s not what you look at that matters; it’s what you see.”
In today’s business world, it’s not exactly easy to see what’s going on. Most people are overwhelmed by data.
Amidst all of the hype and confusion surrounding Big Data, a new type of enterprise is emerging: The Visual Organization. An increasing number of organizations have realized that today’s volume, variety, and velocity of data require new applications. More than technology, though, they have adopted a different mind-set—one based upon data discovery and exploration, not conventional enterprise “reporting.” These companies understand that interactive heat maps and tree maps lend themselves to data discovery more than Microsoft Excel, static graphs, pie charts, and dashboards.
For example, most people have heard of Netflix. Still, relatively few realize that behind the scenes, Netflix does some remarkable things to make the magic happen. Netflix uses fascinating dataviz tools to discover trends, diagnose technical issues, and unearth extraordinarily valuable insights about its customers.
Employees at Autodesk use a remarkable and interactive tool that visualizes current and historical employee movement. From this, they can identify potential management issues and see what a corporate reorg really looks like.
And then there’s eBay. Powerful data-discovery tools allow the company’s employees to effectively “see” what ebay.com would look like....as a brick-and-mortar store.
It’s time to get visual.
The Visual Organization is the sixth book by award-winning author, keynote speaker, and recognized technology expert Phil Simon. Simon demonstrates how a new breed of progressive enterprises has turned traditional data visualization on its head In their place, they are embracing new, interactive, and more robust tools. And these tools help separate the signals from the noise that is Big Data. As a result, they are asking better questions and making better business decisions.
Rife with real-world examples and practical advice, The Visual Organization is a full-color tour de force. Simon deftly explains how organizations can do more than just survive the data deluge; they can thrive in it. It is required reading for executives, professionals, and students interested in unleashing the power of data.
Start to see your business differently.
List of Figures and Tables xviiPreface xix
Acknowledgments xxv
How to Help This Book xxvii
Part I Book Overview and Background 1
Introduction 3
Adventures in Twitter Data Discovery 4
Contemporary Dataviz 101 9
Primary Objective 9
Benefits 11
More Important Than Ever 13
Revenge of the Laggards: The Current State of Dataviz 15
Book Overview 18
Defining the Visual Organization 19
Central Thesis of Book 19
Cui Bono? 20
Methodology: Story Matters Here 21
The Quest for Knowledge and Case Studies 24
Differentiation: A Note on Other Dataviz Texts 25
Plan of Attack 26
Next 27
Notes 27
Chapter 1 The Ascent of the Visual Organization 29
The Rise of Big Data 30
Open Data 30
The Burgeoning Data Ecosystem 33
The New Web: Visual, Semantic, and API-Driven 34
The Arrival of the Visual Web 34
Linked Data and a More Semantic Web 35
The Relative Ease of Accessing Data 36
Greater Efficiency via Clouds and Data Centers 37
Better Data Tools 38
Greater Organizational Transparency 40
The Copycat Economy: Monkey See, Monkey Do 41
Data Journalism and the Nate Silver Effect 41
Digital Man 44
The Arrival of the Visual Citizen 44
Mobility 47
The Visual Employee: A More Tech- and Data-Savvy Workforce 47
Navigating Our Data-Driven World 48
Next 49
Notes 49
Chapter 2 Transforming Data into Insights: The Tools 51
Dataviz: Part of an Intelligent and Holistic Strategy 52
The Tyranny of Terminology: Dataviz, BI, Reporting, Analytics, and KPIs 53
Do Visual Organizations Eschew All Tried-and-True Reporting Tools? 55
Drawing Some Distinctions 56
The Dataviz Fab Five 57
Applications from Large Enterprise Software Vendors 57
LESVs: The Case For 58
LESVs: The Case Against 59
Best-of-Breed Applications 61
Cost 62
Ease of Use and Employee Training 62
Integration and the Big Data World 63
Popular Open-Source Tools 64
D3.js 64
R 65
Others 66
Design Firms 66
Startups, Web Services, and Additional Resources 70
The Final Word: One Size Doesn’t Fit All 72
Next 73
Notes 73
Part II Introducing the Visual Organization 75
Chapter 3 The Quintessential Visual Organization 77
Netflix 1.0: Upsetting the Applecart 77
Netflix 2.0: Self-Cannibalization 78
Dataviz: Part of a Holistic Big Data Strategy 80
Dataviz: Imbued in the Netflix Culture 81
Customer Insights 82
Better Technical and Network Diagnostics 84
Embracing the Community 88
Lessons 89
Next 90
Notes 90
Chapter 4 Dataviz in the DNA 93
The Beginnings 94
UX Is Paramount 95
The Plumbing 97
Embracing Free and Open-Source Tools 98
Extensive Use of APIs 101
Lessons 101
Next 102
Note 102
Chapter 5 Transparency in Texas 103
Background 104
Early Dataviz Efforts 105
Embracing Traditional BI 106
Data Discovery 107
Better Visibility into Student Life 108
Expansion: Spreading Dataviz Throughout the System 110
Results 111
Lessons 113
Next 113
Notes 114
Part III Getting Started: Becoming a Visual Organization 115
Chapter 6 The Four-Level Visual Organization Framework 117
Big Disclaimers 118
A Simple Model 119
Limits and Clarifications 120
Progression 122
Is Progression Always Linear? 123
Can a Small Organization Best Position Itself to Reach Levels 3 and 4? If So, How? 123
Can an Organization Start at Level 3 or 4 and Build from the Top Down? 123
Is Intralevel Progression Possible? 123
Are Intralevel and Interlevel Progression Inevitable? 123
Can Different Parts of the Organization Exist on Different Levels? 124
Should an Organization Struggling with Levels 1 and 2 Attempt to Move to Level 3 or 4? 124
Regression: Reversion to Lower Levels 124
Complements, Not Substitutes 125
Accumulated Advantage 125
The Limits of Lower Levels 125
Relativity and Sublevels 125
Should Every Organization Aspire to Level 4? 126
Next 126
Chapter 7 WWVOD? 127
Visualizing the Impact of a Reorg 128
Visualizing Employee Movement 129
Starting Down the Dataviz Path 129
Results and Lessons 133
Future 135
A Marketing Example 136
Next 137
Notes 137
Chapter 8 Building the Visual Organization 139
Data Tips and Best Practices 139
Data: The Primordial Soup 139
Walk Before You Run . . . At Least for Now 140
A Dataviz Is Often Just the Starting Point 140
Visualize Both Small and Big Data 141
Don’t Forget the Metadata 141
Look Outside of the Enterprise 143
The Beginnings: All Data Is Not Required 143
Visualize Good and Bad Data 144
Enable Drill-Down 144
Design Tips and Best Practices 148
Begin with the End in Mind (Sort of) 148
Subtract When Possible 150
UX: Participation and Experimentation Are Paramount 150
Encourage Interactivity 151
Use Motion and Animation Carefully 151
Use Relative—Not Absolute—Figures 151
Technology Tips and Best Practices 152
Where Possible, Consider Using APIs 152
Embrace New Tools 152
Know the Limitations of Dataviz Tools 153
Be Open 153
Management Tips and Best Practices 154
Encourage Self-Service, Exploration, and Data Democracy 154
Exhibit a Healthy Skepticism 154
Trust the Process, Not the Result 155
Avoid the Perils of Silos and Specialization 156
If Possible, Visualize 156
Seek Hybrids When Hiring 157
Think Direction First, Precision Later 157
Next 158
Notes 158
Chapter 9 The Inhibitors: Mistakes, Myths, and Challenges 159
Mistakes 160
Falling into the Traditional ROI Trap 160
Always—and Blindly—Trusting a Dataviz 161
Ignoring the Audience 162
Developing in a Cathedral 162
Set It and Forget It 162
Bad Dataviz 163
TMI 163
Using Tiny Graphics 163
Myths 165
Data-visualizations Guarantee Certainty and Success 165
Data Visualization Is Easy 165
Data Visualizations Are Projects 166
There Is One “Right” Visualization 166
Excel Is Sufficient 167
Challenges 167
The Quarterly Visualization Mentality 167
Data Defiance 168
Unlearning History: Overcoming the Disappointments of Prior Tools 168
Next 169
Notes 169
Part IV Conclusion and the Future of Dataviz 171
Coda: We’re Just Getting Started 173
Four Critical Data-Centric Trends 175
Wearable Technology and the Quantified Self 175
Machine Learning and the Internet of Things 176
Multidimensional Data 177
The Forthcoming Battle Over Data Portability and Ownership 179
Final Thoughts: Nothing Stops This Train 181
Notes 182
Afterword: My Life in Data 183
Appendix: Supplemental Dataviz Resources 187
Selected Bibliography 191
About the Author 193
Index 195