| Description |
1 online resource (xiv, 119 pages) |
| Series |
Business guides on the go, 2731-4766 |
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Business guides on the go.
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| Contents |
Background and drivers of the data-driven organization -- Characteristics of the data-driven organization -- Challenges and barriers of the data-driven organization -- Process model for data management -- Process model for implementing the data-driven organization -- Closing words |
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Intro -- Foreword by Vanessa Stützle -- Preface -- Contents -- 1: Background and Drivers of the Data-Driven Organization -- 1.1 Business Intelligence Development -- 1.2 Drivers of the Data-Driven Organization -- 1.2.1 Change in the Technological Environment -- 1.2.2 Changed Decision Situation -- 1.2.3 Changing Competition and New Business Models -- 1.2.4 Changing Customer Behavior -- 1.2.5 Drivers Summary -- References -- 2: Characteristics of the Data-Driven Organization -- 2.1 Derivation of the Data-Driven Organization -- 2.1.1 What Is Data? |
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2.1.2 What Is a Data-Driven Business? -- 2.2 What Do "Better" Choices Mean? -- 2.3 Maturity Levels of Data-Driven Companies -- 2.4 Properties of Data for the Data-Driven Organization -- 2.5 Types of Analyses -- 2.6 Advantages of a Data-Driven Company -- References -- 3: Challenges and Barriers of the Data-Driven Organization -- 3.1 Empirical Studies on Challenges and Barriers -- 3.2 Summary of Findings and Evaluation -- References -- 4: Process Model for Data Management -- 4.1 The Five Steps -- 4.2 Collect-Collect Data -- 4.2.1 What Is Data? -- 4.2.2 How Can We Differentiate Data? |
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4.2.3 Which Data from Which Sources Can Be Used? -- 4.2.4 More Data, More Knowledge? -- 4.2.5 How Do Data Silos Arise and How Do We Deal with Them? -- 4.2.6 What Criteria Are Relevant in the Choice of Technology? -- 4.2.7 What General Conditions Do We Have to Consider? -- 4.2.8 Guiding Questions for Collect -- 4.3 Understand-Understanding the Collected Data -- 4.3.1 Why Is Understanding Central? -- 4.3.2 What Conditions Do We Need to Be Able to Understand? -- 4.3.2.1 Technical Requirements -- 4.3.2.2 Analytical Requirements -- 4.3.3 What Must a Technical Preparation Look Like? |
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4.3.4 How Can We Tap into Data? -- 4.3.5 What Does Emotionalizing Data Mean? -- 4.3.6 How Can We Facilitate an Understanding? -- 4.3.6.1 Reference to a Comparable Size -- 4.3.6.2 Establishing a Time Reference -- 4.3.6.3 Reference to Known Objects -- 4.3.7 Guiding Questions for Understand -- 4.4 Decide-Decide on the Basis of the Collected Data -- 4.4.1 What Distinguishes a Data-Driven Decision from a Gut Decision? -- 4.4.2 What Types of Decisions Are Made in Companies? -- 4.4.3 What Are the Requirements for Making a Good Decision? -- 4.4.4 What Role Does the Time Factor Play in Decisions? |
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4.4.5 How Can We Visualize Data? -- 4.4.6 Data Versus Gut-Or Better in Combination? -- 4.4.7 Guiding Questions for Decide -- 4.5 Automate-Automation -- 4.5.1 Why Can't We Get Around Automation? -- 4.5.2 What Are the Technical Requirements for Automation? -- 4.5.3 What Added Value Does AI Create in the Context of Automation? -- 4.5.4 Is Automation Even More Than AI? -- 4.5.5 How Do We Manage to Transfer Our Findings into Processes in an Automated Way? -- 4.5.6 What Can Be the Causes of Resistance to the Data-Driven Organization? -- 4.5.7 Guiding Questions for Automate -- 4.6 Summary |
| Summary |
Data has become an indispensable success factor for every company. However, the road towards a data-driven organization is paved with numerous challenges. This book presents a process model for the path to a data-driven company and provides recommendations for the design of all relevant fields of action: Which structures need to be created? Which systems and processes have proven beneficial? How can the quality of the data be ensured and what requirements exist for a data-driven organization in the areas of governance and communication? And last but not least: How can employees be brought along on the journey and what implications does the data-driven organization have for our corporate culture? The book presents an orientation and action framework for the strategic and operational design of a data-driven organization and is valuable for managers who are involved in data management in companies and organizations |
| Bibliography |
Includes bibliographical references |
| Notes |
Translated from German |
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Online resource; title from PDF title page (SpringerLink, viewed December 28, 2022) |
| Subject |
Business information services.
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Information technology -- Management.
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Big data.
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Big data
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Business information services
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Information technology -- Management
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| Form |
Electronic book
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| ISBN |
9783031206047 |
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3031206045 |
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