+353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)

PRINTER FRIENDLY

Agile by Design. An Implementation Guide to Analytic Lifecycle Management. Wiley and SAS Business Series

  • ID: 3110165
  • Book
  • 288 Pages
  • John Wiley and Sons Ltd
1 of 3

MAXIMIZE YOUR ANALYTIC TEAM′S VALUE–ADDED INNOVATION BY EMBEDDING ANALYTICS INTO YOUR OPERATIONS

Agile by Design offers the qualified science and instruments to ignite dramatic improvement in the analytic lifecycle management practices of your company. First, it takes you on an in–depth exploration of what analytics projects are and why they require special treatment from traditional development initiatives, and then equips you with everything you need to customize and apply agile methodologies to individual projects and teams.

Based on a framework of agile delivery techniques, this approach opens up the silos operating in any company and enables business, analytic, and IT groups to unite their work with the essential operational disciplines for superior analytics. This one system will coordinate and make sense out of all your predictive and analytic models, while simultaneously making them more valuable and relevant to improving your customer–centric values. Become an analytic game changer at your company by:

  • Mastering the principles, processes, and practices distinguishing remarkable analytic lifecycle management
  • Developing skill sets of agile methodologies for playing an initiating, planning, and executing role in analytic development projects
  • Identifying the specific analytics projects best suited for the different frameworks in your business

Whether you′re an analytic pro or a newbie, adding the structure and rigor outlined in Agile by Design to your analytic project will increase your chances of success by connecting the modelers and business managers to create a business with a competitive edge.

Note: Product cover images may vary from those shown
2 of 3

Introduction xiii

About the Author xix

Chapter 1 Adjusting to a Customer–Centric Landscape 1

It s a Whole New World 1

From Customer–Aware to Customer–Centric 3

Being Customer–Centric, Operationally Efficient, and Analytically Aware 6

Our Example in Motion 9

Enabling Innovation 10

Chapter 2 The Analytic Lifecycle 13

What Are Analytics, Anyway? 13

Analytics in Your Organization 15

Case Study Example 17

Beyond IT: The Business Analytic Value Chain 18

Analytic Delivery Lifecycle 19

Stage One Perform Business Discovery 20

Stage Two Perform Data Discovery 21

Stage Three Prepare Data 22

Stage Four Model Data 23

Stage Five Score and Deploy 24

Stage Six Evaluate and Improve 25

Getting Started 25

Summary 26

Chapter 3 Getting Your Analytic Project off the Ground 27

A Day in the Life 29

Visioning 30

Facilitating Your Visioning Session 32

Think Like a Customer 33

Summary 36

Chapter 4 Project Justification and Prioritization 37

Organizational Value of Analytics 37

Analytic Demand Management Strategy 38

Results 40

Project Prioritization Criteria 42

Value–Based Prioritization 43

Financial–Based Prioritization 45

Knowledge Acquisition Spikes 46

Summary 47

Chapter 5 Analytics the Agile Way 49

Getting Started 49

Understanding Waterfall 51

The Heart of Agile 53

The Agile Manifesto/Declaration of Interdependence 54

Selecting the Right Methodology 57

Scrum 58

eXtreme Programming (XP) 59

Summary 61

Chapter 6 Analytic Planning Hierarchies 63

Analytic Project Example 63

Inputs into Planning Cycles 66

Release Planning 69

Analytic Release Plan 70

Release Train 71

Summary 73

Chapter 7 Our Analytic Scrum Framework 75

Getting Started 75

The Scrum Framework 77

Sprint Planning 78

Sprint Execution 80

Daily Standup 81

How Do We Know When We re Done? 82

Sprint Review 83

Sprint Retrospective 85

Summary 85

Chapter 8 Analytic Scrum Roles and Responsibilities 87

Product Owner Description 89

Product Owner: A Day in the Life 91

ScrumMaster Description 92

ScrumMaster: A Day in the Life 94

Analytic Development Team Description 95

Additional Roles 97

Summary 98

Chapter 9 Gathering Analytic User Stories 101

Overview 101

User Stories 103

The Card 104

Analytic User Story Examples 105

Technical User Stories 106

The Conversation 107

The Confirmation 107

Tools and Techniques 108

INVEST in Good Stories 109

Epics 111

Summary 112

Chapter 10 Facilitating Your Story Workshop 113

Stakeholder Analysis 113

Managing Stakeholder Influence 116

Agile versus Traditional Stakeholder Management 118

The Story Workshop 118

Workshop Preparation 119

Facilitating Your Workshop 121

Must–Answer Questions 123

Post–Workshop 124

Summary 126

Chapter 11 Collecting Knowledge Through Spikes 127

With Data, Well Begun Is Half Done 127

The Data Spike 129

Data Gathering 131

Visualization and Iterations 135

Defining Your Target Variable 136

Summary 138

Chapter 12 Shaping the Analytic Product Backlog 141

Creating Your Analytic Product Backlog 141

Going DEEP 145

Product Backlog Grooming 146

Defining Ready 146

Managing Flow 147

Release Flow Management 148

Sprint Flow Management 148

Summary 149

Chapter 13 The Analytic Sprint: Planning and Execution 151

Committing the Team 151

The Players 153

Sprint Planning 154

Velocity 155

Task Definition 156

The Team s Definition of Done 158

Organizing Work 159

Sprint Zero 160

Sprint Execution 161

Summary 163

Chapter 14 The Analytic Sprint: Review and Retrospective 165

Sprint Review 165

Roles and Responsibilities 168

Sprint Retrospective 168

Sprint Planning (Again) 171

Layering in Complexity 173

Summary 175

Chapter 15 Building in Quality and Simplicity 177

Quality Planning 177

Simple Design 181

Coding Standards 183

Refactoring 184

Collective Code Ownership 185

Technical Debt 186

Testing 187

Verification and Validation 188

Summary 189

Chapter 16 Collaboration and Communication 191

The Team Space 191

Things to Put in the Information Radiator 194

Analytic Velocity 195

Improving Velocity 196

The Kanban or Task Board 197

Considering an Agile Project Management Tool 198

Summary 200

Chapter 17 Business Implementation Planning 203

Are We Done Yet? 203

What s Next? 205

Analytic Release Planning 206

Section 1: What Did We Do, and Why? 206

Section 2: Supporting Information 208

Section 3: Model Highlights 208

Section 4: Conclusions and Recommendations 208

Section 5: Appendix 209

Model Review 209

Levers to Pull 210

Persona–Based Design 211

Segmentation Case Study 213

Summary 214

Chapter 18 Building Agility into Test–and–Learn Strategies 215

What Is Test–and–Learn? 215

Layering in Complexity 218

Incorporating Test–and–Learn into Your Model Deployment Strategy 219

Creating a Culture of Experimentation 221

Failing Fast and Frequently 222

Who Owns Testing? 222

Getting Started 223

Summary 225

Chapter 19 Operationalizing Your Model Deployment Strategy 227

Finding the Right Model 227

Simplicity over Complexity 231

How Deep Do We Go? 231

What Is an Operational Model Process? 232

Getting Your Data in Order 234

Automate Model–Ready Data Processes 235

So Who Owns It? 236

What If I Can t Automate This Process Right Now? 236

Determine Model Scoring Frequency 237

Model Performance Monitoring 239

Analytics the Success to Plan For 241

Summary 243

Chapter 20 Analytic Ever After 245

Beginning Your Journey 245

Supporting the Analytic Team 246

The Importance of Agile Analytic Leadership 248

Finding a Pilot Project 249

Scaling Up 249

The End of the Beginning 251

Sources 253

Index 255

Note: Product cover images may vary from those shown
3 of 3

Loading
LOADING...

4 of 3
Rachel Alt–Simmons
Note: Product cover images may vary from those shown
Adroll
adroll