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Produktbild: Field Guide to Digital Transformation, A

Field Guide to Digital Transformation, A

32,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.01.2022

Verlag

Pearson Education Limited

Seitenzahl

288

Maße (L/B/H)

23,1/17,6/1,5 cm

Gewicht

570 g

Auflage

1

Sprache

Englisch

ISBN

978-0-13-757184-0

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.01.2022

Verlag

Pearson Education Limited

Seitenzahl

288

Maße (L/B/H)

23,1/17,6/1,5 cm

Gewicht

570 g

Auflage

1

Sprache

Englisch

ISBN

978-0-13-757184-0

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Field Guide to Digital Transformation, A
  • 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