A Field Guide to Digital Transformation

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Beschreibung

A Field Guide to Digital Transformation is a complete tutorial on digital transformation concepts, tools, technologies and practices, organized into a proven industry framework for adoption. Best-selling IT author Thomas Erl and long-time practitioner Amin Naserour offer end-to-end coverage of the full project lifecycle, walking readers through planning, defining, designing, building, and governing digital transformation solutions. The authors highlight common risks, pitfalls, and adoption considerations, sharing practical insights into the organizational, cultural, technological, and operational impacts associated with digital transformation initiatives.

Uniquely detailed and practical, this guide reflects the authors' deep experience driving value from digital transformation using technologies available right now.

Über den Autor

Thomas Erl is a best-selling IT author who has authored and co-authored 15 books published by Prentice Hall and Pearson Education and dedicated to topics focused on contemporary information technology and practices. These titles were delivered for the Pearson Digital Enterprise Series from Thomas Erl (formerly the Prentice Hall Service Technology Series from Thomas Erl) for which Thomas also acts as series editor.

As founder and president of Arcitura Education ([...] Thomas also leads the development of curricula for internationally recognized, vendor-neutral training and accreditation programs. Arcitura's portfolio currently consists of over 100 courses, over 90 Pearson VUE exams, and over 40 certification tracks, covering topics such as Digital Transformation, Robotic Process Automation (RPA), DevOps, Blockchain, IoT, Containerization, Machine Learning, Artificial Intelligence (AI), Cybersecurity, Service-Oriented Architecture (SOA), Cloud Computing and Big Data Analytics.

Roger Stoffers is a TOGAF-certified Enterprise Architect passionate about Digital Transformation and Integration. Roger has worked for (and with) organizations in Telecommunication, Government and Finance industries, building 25 years of experience in multinational organizations. He has served as principal and lead Enterprise Domain Architect for digital business transformation initiatives, with strong focus for customer relationships and sustainable organizational agility in distributed environments.

Presently Roger works as Enterprise Architect for de Volksbank, fostering Customer Centricity and the organization's Sustainability & Social Responsibility goals with Data-Driven Customer Engagement and Decisioning. Independently, Roger is a worldwide consulting architect for digital transformation and integration, and a senior trainer for (enterprise) architecture topics and contemporary vendor-neutral technology and next-generation IT topics. He is a speaker at conferences about Digital Transformation, SOA and Microservices and Enterprise Architecture. He is a contributor for the Service-Oriented Architecture: Analysis and Design for Service and Microservices book from the Pearson Digital Enterprise Series from Thomas Erl.

Inhaltsverzeichnis

About This Book xxvii

PART I: DIGITAL TRANSFORMATION FUNDAMENTALS

Chapter 1: Understanding Digital Transformation 3

(What is Digital Transformation?) 3

Business, Technology, Data and People 5

Digital Transformation and Business 6

Digital Transformation and Technology 7

Digital Transformation and Data 9

Digital Transformation and People 10

Digital Transformation and Organizations and Solutions 11

Chapter 2: Common Business Drivers 13

(What Led to Digital Transformation?) 13

Losing Touch with Customer Communities 14

Inability to Grow in Stale Marketplaces 16

Inability to Adapt to Rapidly Changing Marketplaces 16

Cold Customer Relationships 19

Inefficient Operations 19

Inefficient Decision-Making 21

Chapter 3: Common Technology Drivers 23

(What Enables Digital Transformation?) 23

Enhanced and Diverse Data Collection 25

Contemporary Data Science 27

Sophisticated Automation Technology 29

Autonomous Decision-Making 29

Centralized, Scalable, Resilient IT Resources 31

Immutable Data Storage 33

Ubiquitous Multiexperience Access 34

Chapter 4: Common Benefits and Goals 37

(Why Undergo a Digital Transformation?) 37

Enhanced Business Alignment 39

Enhanced Automation and Productivity 42

Enhanced Data Intelligence and Decision-Making 44

Improved Customer Experience and Customer Confidence 44

Improved Organizational Agility 48

Improved Ability to Attain Market Growth 50

Chapter 5: Common Risks and Challenges 53

(What Are the Pitfalls?) 53

Poor Data Quality and Data Bias 55

Increased Quantity of Vulnerable Digital Data 55

Resistance to Digital Culture 58

Risk of Over-Automation 59

Difficult to Govern 61

Chapter 6: Realizing Customer-Centricity 63

What Is a Product? 64

What Is a Customer? 65

Product-Centric vs. Customer-Centric Relationships 67

Transaction-Value vs. Relationship-Value Actions 69

Customer-Facing vs. Customer-Oriented Actions 71

Relationship Value and Warmth 71

Warmth in Communication 71

Warmth in Proactive Accommodation 74

Warmth in Customer Rewards 76

Warmth in Exceeding Customer Expectations 76

Single vs. Multi vs. Omni-Channel Customer Interactions 77

Customer Journeys 81

Customer Data Intelligence 84

Chapter 7: Data Intelligence Basics 89

Data Origins (Where Does the Data Come From?) 90

Corporate Data 92

Third-Party Data 92

Creating New Corporate Data Intelligence 92

Common Data Sources (Who Produces the Data?) 93

Operations Data 95

Customer Data 95

Social Media Data 95

Public Sector Data 96

Private Sector Data 97

Data Collection Methods (How Is the Data Collected?) 97

Manual Data Entry 98

Automated Data Entry or Collection 98

Telemetry Data Capture 98

Digitization 99

Data Ingress 101

Data Utilization Types (How Is the Data Used?) 101

Analysis and Reporting 101

Automated Decision-Making 102

Solution Input 103

Bot-Driven Automation 103

Model Training and Retraining 103

Historical Record Keeping 104

Chapter 8: Intelligent Decision-Making 105

Manual Decision-Making 107

Computer-Assisted Manual Decision-Making 107

Conditional Automated Decision-Making 108

Intelligent Manual Decision-Making 109

Intelligent Automated Decision-Making 112

Direct-Driven Automated Decision-Making 113

Periodic Automated Decision-Making 114

Realtime Automated Decision-Making 115

Intelligent Manual vs. Intelligent Automated Decision-Making 115

PART II: DIGITAL TRANSFORMATION IN PRACTICE

Chapter 9: Understanding Digital Transformation Solutions 121

Distributed Solution Design Basics 122

Data Ingress Basics 127

File Pull 127

File Push 128

API Pull 129

API Push 129

Data Streaming 130

Common Digital Transformation Technologies 132

Chapter 10: An Introduction to Digital Transformation Automation Technologies 135

Cloud Computing 137

Cloud Computing in Practice 138

Common Risks and Challenges 143

Blockchain 144

Blockchain in Practice 145

Partial Business Data Capture 147

Full Business Data Capture 148

Log Data Access Capture 150

Partial Business Data Store 151

Ledger Export 152

Common Risks and Challenges 153

Internet of Things (IoT) 154

IoT Devices 154

IoT in Practice 160

Common Risks and Challenges 163

Robotic Process Automation (RPA) 164

RPA in Practice 165

Common Risks and Challenges 168

Chapter 11: An Introduction to Digital Transformation Data Science Technologies 171

Big Data Analysis and Analytics 172

The Five V's of Big Data 175

Big Data in Practice 177

Common Risks and Challenges 178

Machine Learning 179

Model Training 180

Machine Learning in Practice 180

Common Risks and Challenges 184

Artificial Intelligence (AI) 186

Neural Networks 186

Automated Decision-Making 187

AI in Practice 189

Common Risks and Challenges 189

Chapter 12: Inside a Customer-Centric Solution 193

Scenario Background 195

Business Challenges 195

The Original Customer Journey 196

Business Objectives 201

Terminology Recap 201

Key Terms from Chapter 6: Realizing Customer-Centricity 202

Key Terms from Chapter 7: Data Intelligence Basics 202

Key Terms from Chapter 8: Intelligent Decision-Making 203

Key Terms from Chapter 9: Understanding Digital Transformation Solutions 203

Key Terms from Chapter 10: An Introduction to Digital Transformation Automation Technologies 204

Key Terms from Chapter 11: An Introduction to Digital Transformation Data Science Technologies 204

The Enhanced Customer Journey 204

Supporting Data Sources 205

Step-by-Step Business Process 206

Future Decision-Making 241

About the Authors 243

Index 245

Details

Medium:	Taschenbuch
ISBN-13:	9780137571840
ISBN-10:	0137571844
Sprache:	Englisch
Einband:	Kartoniert / Broschiert
Autor:	Erl, Thomas Stoffers, Roger
Hersteller:	Pearson Education
Maße:	231 x 176 x 15 mm
Von/Mit:	Thomas Erl (u. a.)
Erscheinungsdatum:	06.12.2021
Gewicht:	0,552 kg

Artikel-ID: 120064062