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Produktbild: Field Guide to Digital Transformation, A

Field Guide to Digital Transformation, A

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.01.2022

Verlag

Pearson

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

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@libri.de

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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