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The Sentient Enterprise. The Evolution of Business Decision Making

  • ID: 4339974
  • Book
  • November 2017
  • Region: Global
  • 176 Pages
  • John Wiley and Sons Ltd
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The Sentient Enterprise summarizes the achievement of "sentience" that an analytics journey should lead companies toward. It′s not meant to represent an actual destination.

The Sentient Enterprise is more of a North Star that every large business should aspire to be, as it struggles to make decisions at the speed of data. However, Mohan and Oliver did determine that a Sentient Enterprise must have five foundational qualities.

It must be:

  • Proactive and able to sense micro–trends signaling the next opportunity or alerting the next crisis
  • Frictionless because it can act as a single organism without any impedance or bottlenecks
  • Autonomous to listen to data and make decisions in real time without much human intervention
  • Scalable to any size company and able to leverage unlimited data for making decisions
  • Evolving through intelligence that is native and emergent

In order to get there, any enterprise has to go on a journey. The Sentient Enterprise journey is the way your company will get there. This methodology is disrupting entire industries and changing the very nature – the very identity – of large companies across nearly all sectors of our economy. It is a journey every big company should take if they seek to understand how data can help them become even better in order to survive and compete in today′s data–driven marketplace.

It will change the way everyone in business makes decisions – from small, tactical ones to mission–critical ones – by continuously decomposing problems into manageable components.

But it is a journey only a few brave ones have started because it is as long–term and complex as it is realistic and valuable. But make no mistake about it – it′s an ongoing journey.

There is no finish line.

This is not for the meek or faint of heart.

It′s for the early adopters among you who want to get ahead of the competition or for the followers among you to ensure your survival.

And for the unconcerned? Hmm… well… odds are you will lose out to your competitors who are already building architectures and strategies to lead the way.

Mohan and Oliver believe you can be the pioneers of your organizations. You want to take your company in the direction it needs to go to survive, lead, and disrupt in this changing, data–intensive world.

This book will inspire you by getting you to think about how this model can bring you competitive advantage and not just ideas about data innovation. Success is possible if you embrace the changes and methods needed to fully leverage big data analytics for your businesses.

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Foreword ix

Introduction xiii

Chapter 1 Reimagining the Enterprise 1

Disruption and Decision Making 3

Self–Disruption at Cisco: On Purpose and at Scale 4

Self–Disrupt in Sustainable Ways 5

Analytic Pain Points and a Self–Service Revolution 6

Access and Control 8

A Necessary Evolution 11

Putting It All Together 12

Chapter 2 Leveraging an Expanding Universe of Data 15

A Universe of Data: Expanding Exponentially with New Sources 17

Game–Changing Capabilities 20

Well–Intentioned Anarchy 22

Data Marts and Their Discontents 23

A Solution? “LinkedIn for Analytics” 25

Getting Back to eBay: Fulfilling the Analytics Mandate 27

Chapter 3 The Agile Data Platform 31

Retaining Agility at Scale 32

Rethinking Waterfall Methodologies 34

Agile Analytics 35

Spreading Agility Company–Wide with the Virtual Data Mart 36

A Virtual Data Mart (by Any Other Name) in Action 38

Time Boxing 39

Fewer Requirements, More Prototypes 40

Analytics on Analytics 41

Making It Real with the Layered Data Architecture 42

Driving Change in the Auto Industry 45

Remembering the Big Picture 46

Chapter 4 The Behavioral Data Platform 49

Personalized—If Not Personal—Interaction 52

New Measures for Success, Built on Behavioral Data 53

Leveraging Behavioral Data for Real–World Business Challenges 55

Behavioral Data Is Everywhere 58

Agile Systems for Behavioral Data 59

Back Inside the Layered Data Architecture 62

Reaping Value and Insight 64

Proactive Data Standards and Designing for the Unknown 65

Chapter 5 The Collaborative Ideation Platform 67

Avoiding “Anti–Social” Analytics 68

The Problem of Metadata at Scale 70

Collaboration and Context at Scale 72

Merchandising Analytic Insights 73

Staying on the Path to Value through Analytics on Analytics 75

Adoption Takes Time 77

Operationalizing Insights 78

Chapter 6 The Analytical Application Platform 81

Turning Analytic Insight into Action Across the Organization 83

Lessons from the Cloud 85

Creating an App Economy for the Enterprise 86

DevOps to Make It Real 88

Less ETL . . . 91

. . . More “Data Listening” 92

Setup for Sentience 94

Chapter 7 The Autonomous Decisioning Platform 97

Fast–Changing Capabilities 99

Self–Driving Cars … and Companies 100

“System of Systems” Building Blocks for Sentience 101

Algorithms: A Must–Have for Autonomous Decisioning 102

Strategically Applying Algorithmic Intelligence in the Enterprise 105

Algorithmic “Magic” 106

Analytics on Algorithms to Improve Decision Making 107

Combining Algorithms on the Home Stretch to Sentience 109

Agility as the Ultimate Litmus Test 111

Chapter 8 Implementing Your Course to Sentience 113

Ask the Right Questions, Warts and All 115

Agile Strategic Planning Is Not an Oxymoron 116

Adopt a Start–Up Mind–Set and Don’t Boil the Ocean 118

Pick the Right Internal Partners to Demonstrate Value 119

Embrace Agile Project Management Strategies 120

Embrace Concurrency, Ensure Scalability 120

Design in Governance That’s Seamless and Repeatable 121

Optimize a Workforce to Act Fast, Fail Fast, and Scale Fast 122

“It’s the Culture, Stupid” 123

Conclusion 125

Acknowledgments 137

About the Authors 139

Index 141

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Oliver Ratzesberger
Mohanbir Sawhney
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