A NEW MODEL FOR ANALYTIC CAPABILITY, MATURITY, AND AGILITY AT SCALE
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.
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
About the Authors 139