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Cover: 9789811957185 | Defining Enterprise Data and Analytics Strategy | Prakash Sah | Buch
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Defining Enterprise Data and Analytics Strategy
Pragmatic Guidance on Defining Strategy Based on Successful Digital Transformation Experience of Multiple Fortune 500...
Buch von Prakash Sah
Sprache: Englisch

67,75 €*

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Beschreibung
This is the first of its kind book that describes key elements of enterprise data and analytics strategy, and prescribes a pragmatic approach to define the strategy for large enterprises. The book is based on successful digital transformation experience of multiple Fortune 500 and other large enterprises. It is estimated that more than 50% of data and analytics initiatives fail globally because of the inherent complexity of such initiatives. Some of the questions that enterprises struggle with are: How to define enterprise data and analytics strategy? What are the key elements that should be considered while doing so? Why one-size-fits-all approach does not work for all enterprises? How to align data and analytics initiative with the business strategy of the CEO? How to establish a futuristic technology and architecture foundation, given the exponential rate of innovation in data and analytics technologies? How to define the right data and analytics organization model? Why data and analytics organization and processes need to be different from other functions? How to manage organizational change to ensure success of data and analytics initiative? How to define a business value measurement framework and calculate ROI from data and analytics initiative? What are the key skills required in a data and analytics leader to wade through political and other challenges of a large enterprise? This book will help executives, chief digital/analytics officers, data and analytics professionals, and consultants, in answering the above questions. It will help them in addressing various dilemmas that they face every day and making their enterprises data-driven.
This is the first of its kind book that describes key elements of enterprise data and analytics strategy, and prescribes a pragmatic approach to define the strategy for large enterprises. The book is based on successful digital transformation experience of multiple Fortune 500 and other large enterprises. It is estimated that more than 50% of data and analytics initiatives fail globally because of the inherent complexity of such initiatives. Some of the questions that enterprises struggle with are: How to define enterprise data and analytics strategy? What are the key elements that should be considered while doing so? Why one-size-fits-all approach does not work for all enterprises? How to align data and analytics initiative with the business strategy of the CEO? How to establish a futuristic technology and architecture foundation, given the exponential rate of innovation in data and analytics technologies? How to define the right data and analytics organization model? Why data and analytics organization and processes need to be different from other functions? How to manage organizational change to ensure success of data and analytics initiative? How to define a business value measurement framework and calculate ROI from data and analytics initiative? What are the key skills required in a data and analytics leader to wade through political and other challenges of a large enterprise? This book will help executives, chief digital/analytics officers, data and analytics professionals, and consultants, in answering the above questions. It will help them in addressing various dilemmas that they face every day and making their enterprises data-driven.
Über den Autor

Prakash Sah has three decades of multi-faceted consulting and leadership experience in data and analytics. His experience spans across multiple industries and cultures. While working in 13 different countries, he helped CXOs and other leaders of many Fortune 500 companies in defining their enterprise data and analytics vision, strategy, and roadmap.

Prakash has been invited as speaker/panelist at various international conferences and innovation events. He has also been delivering guest lectures at few B Schools. He has been mentoring many students and professionals in academia and industry respectively. He has authored various papers and articles on enterprise data and analytics.

Prakash is a mechanical engineer from IIT Kharagpur and an MBA from IIM Calcutta - two premier institutes in India. He is currently working as Managing Partner at TCS (Tata Consultancy Services), one of the world's leading consulting and IT services MNC. Prakash is based out of Thane in Mumbai metropolitan region, India, where he stays with his wife and two daughters.

Linked-in profile: [...]

Zusammenfassung

First book in the world that provides pragmatic approach to define enterprise data and analytics strategy

Prescribes how to lay down data and analytics foundation that forms the core of enterprise digital transformation

Gives pragmatic guidance on driving organizational change management to succeed in a data and analytics initiative

Describes a comprehensive framework to measure business value and ROI from data and analytics initiative

Explains skills required in data and analytics leader to wade through political/other challenges of a large enterprise

Inhaltsverzeichnis
Chapter 1: What is Data and Analytics Strategy
Key elements that should be part of the strategy
Data and Analytics Strategy and its Criticality to Drive Enterprise Digital Initiatives
Data and Analytics Strategy: A Case in Point
Five Elements of Data and Analytics Strategy
¿ Business capabilities
¿ Technology and architecture
¿ Team, processes, and governance
¿ Organizational change management
¿ Value measurement framework
Summary
Chapter 2: First Element of Strategy - Business Capabilities
Taking a top-down approach to align with business strategy
Aligning with Organization's Business Priorities
Establishing Enterprise Performance Management Framework
¿ A brief historical perspective on performance measurement
¿ Key performance indicators (KPIs): lagging and leading indicators
¿ KPI trees to drive enterprise performance management
¿ Challenges of implementing enterprise KPI framework
¿ KPI framework defined for scenario 1 (organization A) discussed at the beginning of this chapter
Driving Enterprise Digital Strategy
¿ Approach for scenario 2 (organization B): Digital transformation leveraging data and analytics
Approach for Defining Data and Analytics Strategy, Starting with Business Capabilities
¿ Step 1: Enterprise churning - "Samudra Manthan"
¿ Step 2: Defining required business capabilities and other strategy elements
¿ Step 3: Prioritizing and creating an integrated roadmap
Summary
Chapter 3: Second Element of Strategy - Technology and Architecture
Establishing technology and architecture foundation that is futuristic and flexible
How Not to Define Technology and Architecture Strategy?
Understanding Non-Functional Requirements to Define Data and Analytics Architecture
¿ Data sources
¿ Mode of delivery/access (of data)
¿ Temporal
¿ Data security
¿ Data type
¿ Data atomicity
¿ Latency
¿ Data quality and integrity
¿ Business model
¿ Data usage
¿ Metadata
Defining Data and Analytics Architecture
Selecting Relevant Technologies after Defining Data and Analytics Architecture
Summary
Chapter 4: Third Element of Strategy - Team, Processes, and Governance
Establishing building blocks, including an agile team, for success
Why Data and Analytics Organization and Processes Need to be Different from Other IT Functions?
Choosing the Right Data and Analytics Organization Model
¿ Decentralized organization
¿ Centralized organization
¿ Federated organization
Defining Data and Analytics Organization and Processes
¿ Governance tower
¿ Business tower
¿ Technology and architecture tower
¿ Solution delivery tower
¿ Service delivery tower
Week-in-the-Life of Data and Analytics Team
Summary
Chapter 5: Fourth Element of Strategy - Organizational Change Management
Driving and managing change across the enterprise to ensure success
Need for Change Across the Enterprise
¿ Till 2010 - A brief history of MIS era
¿ The 2010s - Data visualization becomes all-pervasive across enterprises
¿ The latter half of 2010s - Advent of digital technologies
¿ Why organizational change management
Driving Change - Focus Areas & Objectives
¿ Four Focus Areas - People, Processes, Technology, and Data
¿ Three OCM Objectives
¿ Twelve OCM Strategy Elements for Data and Analytics
Stages of Change & Change Leadership
¿ The Three Stages of Change
¿ Importance of Change Leadership
Summary
Chapter 6: Fifth Element of Strategy - Value Measurement Framework
Establishing a framework to define and measure value of data and analytics program
The Need for a Value Measurement Framework
Defining and Measuring Business Value
¿ First impact area: Revenue increase
¿ Second impact area: Cost reduction
¿ Third impact area: Business risk mitigation
¿ Fourth impact area: Company's image building
¿ Business value measurement: Correlation does not necessarily mean causality
Defining and Measuring Operational Efficiency - Continuous Improvement
¿ People performance
¿ Process effectiveness
¿ Technology capability
¿ Data maturity
¿ Operational efficiency and maturity assessment
Calculating ROI from Data and Analytics Investment
¿ Calculating benefits
¿ Calculating costs
¿ Calculating ROI
Summary
Chapter 7: The Profile of a Data and Analytics Leader
Key skills of a leader who can lead the enterprise to success
Key Skills that any Enterprise Data and Analytics Leader Must Possess
Hard Skills
¿ Technology
¿ Data science
¿ Business
Soft Skills
¿ Dealing with ambiguity
¿ Team leadership
¿ Innovation and risk-taking
¿ Organizational change management
¿ Design thinking and empathy
¿ Marketing
Summary
Details
Erscheinungsjahr: 2022
Fachbereich: Management
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
Seiten: 192
Titelzusatz: Pragmatic Guidance on Defining Strategy Based on Successful Digital Transformation Experience of Multiple Fortune 500 and Other Global Companies
Reihe: Management for Professionals
Inhalt: xv
174 S.
33 s/w Illustr.
6 farbige Illustr.
174 p. 39 illus.
6 illus. in color.
ISBN-13: 9789811957185
ISBN-10: 9811957185
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Sah, Prakash
Auflage: 1st ed. 2022
Hersteller: Springer Singapore
Springer Nature Singapore
Management for Professionals
Maße: 241 x 160 x 17 mm
Von/Mit: Prakash Sah
Erscheinungsdatum: 07.11.2022
Gewicht: 0,459 kg
preigu-id: 122102961
Über den Autor

Prakash Sah has three decades of multi-faceted consulting and leadership experience in data and analytics. His experience spans across multiple industries and cultures. While working in 13 different countries, he helped CXOs and other leaders of many Fortune 500 companies in defining their enterprise data and analytics vision, strategy, and roadmap.

Prakash has been invited as speaker/panelist at various international conferences and innovation events. He has also been delivering guest lectures at few B Schools. He has been mentoring many students and professionals in academia and industry respectively. He has authored various papers and articles on enterprise data and analytics.

Prakash is a mechanical engineer from IIT Kharagpur and an MBA from IIM Calcutta - two premier institutes in India. He is currently working as Managing Partner at TCS (Tata Consultancy Services), one of the world's leading consulting and IT services MNC. Prakash is based out of Thane in Mumbai metropolitan region, India, where he stays with his wife and two daughters.

Linked-in profile: [...]

Zusammenfassung

First book in the world that provides pragmatic approach to define enterprise data and analytics strategy

Prescribes how to lay down data and analytics foundation that forms the core of enterprise digital transformation

Gives pragmatic guidance on driving organizational change management to succeed in a data and analytics initiative

Describes a comprehensive framework to measure business value and ROI from data and analytics initiative

Explains skills required in data and analytics leader to wade through political/other challenges of a large enterprise

Inhaltsverzeichnis
Chapter 1: What is Data and Analytics Strategy
Key elements that should be part of the strategy
Data and Analytics Strategy and its Criticality to Drive Enterprise Digital Initiatives
Data and Analytics Strategy: A Case in Point
Five Elements of Data and Analytics Strategy
¿ Business capabilities
¿ Technology and architecture
¿ Team, processes, and governance
¿ Organizational change management
¿ Value measurement framework
Summary
Chapter 2: First Element of Strategy - Business Capabilities
Taking a top-down approach to align with business strategy
Aligning with Organization's Business Priorities
Establishing Enterprise Performance Management Framework
¿ A brief historical perspective on performance measurement
¿ Key performance indicators (KPIs): lagging and leading indicators
¿ KPI trees to drive enterprise performance management
¿ Challenges of implementing enterprise KPI framework
¿ KPI framework defined for scenario 1 (organization A) discussed at the beginning of this chapter
Driving Enterprise Digital Strategy
¿ Approach for scenario 2 (organization B): Digital transformation leveraging data and analytics
Approach for Defining Data and Analytics Strategy, Starting with Business Capabilities
¿ Step 1: Enterprise churning - "Samudra Manthan"
¿ Step 2: Defining required business capabilities and other strategy elements
¿ Step 3: Prioritizing and creating an integrated roadmap
Summary
Chapter 3: Second Element of Strategy - Technology and Architecture
Establishing technology and architecture foundation that is futuristic and flexible
How Not to Define Technology and Architecture Strategy?
Understanding Non-Functional Requirements to Define Data and Analytics Architecture
¿ Data sources
¿ Mode of delivery/access (of data)
¿ Temporal
¿ Data security
¿ Data type
¿ Data atomicity
¿ Latency
¿ Data quality and integrity
¿ Business model
¿ Data usage
¿ Metadata
Defining Data and Analytics Architecture
Selecting Relevant Technologies after Defining Data and Analytics Architecture
Summary
Chapter 4: Third Element of Strategy - Team, Processes, and Governance
Establishing building blocks, including an agile team, for success
Why Data and Analytics Organization and Processes Need to be Different from Other IT Functions?
Choosing the Right Data and Analytics Organization Model
¿ Decentralized organization
¿ Centralized organization
¿ Federated organization
Defining Data and Analytics Organization and Processes
¿ Governance tower
¿ Business tower
¿ Technology and architecture tower
¿ Solution delivery tower
¿ Service delivery tower
Week-in-the-Life of Data and Analytics Team
Summary
Chapter 5: Fourth Element of Strategy - Organizational Change Management
Driving and managing change across the enterprise to ensure success
Need for Change Across the Enterprise
¿ Till 2010 - A brief history of MIS era
¿ The 2010s - Data visualization becomes all-pervasive across enterprises
¿ The latter half of 2010s - Advent of digital technologies
¿ Why organizational change management
Driving Change - Focus Areas & Objectives
¿ Four Focus Areas - People, Processes, Technology, and Data
¿ Three OCM Objectives
¿ Twelve OCM Strategy Elements for Data and Analytics
Stages of Change & Change Leadership
¿ The Three Stages of Change
¿ Importance of Change Leadership
Summary
Chapter 6: Fifth Element of Strategy - Value Measurement Framework
Establishing a framework to define and measure value of data and analytics program
The Need for a Value Measurement Framework
Defining and Measuring Business Value
¿ First impact area: Revenue increase
¿ Second impact area: Cost reduction
¿ Third impact area: Business risk mitigation
¿ Fourth impact area: Company's image building
¿ Business value measurement: Correlation does not necessarily mean causality
Defining and Measuring Operational Efficiency - Continuous Improvement
¿ People performance
¿ Process effectiveness
¿ Technology capability
¿ Data maturity
¿ Operational efficiency and maturity assessment
Calculating ROI from Data and Analytics Investment
¿ Calculating benefits
¿ Calculating costs
¿ Calculating ROI
Summary
Chapter 7: The Profile of a Data and Analytics Leader
Key skills of a leader who can lead the enterprise to success
Key Skills that any Enterprise Data and Analytics Leader Must Possess
Hard Skills
¿ Technology
¿ Data science
¿ Business
Soft Skills
¿ Dealing with ambiguity
¿ Team leadership
¿ Innovation and risk-taking
¿ Organizational change management
¿ Design thinking and empathy
¿ Marketing
Summary
Details
Erscheinungsjahr: 2022
Fachbereich: Management
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
Seiten: 192
Titelzusatz: Pragmatic Guidance on Defining Strategy Based on Successful Digital Transformation Experience of Multiple Fortune 500 and Other Global Companies
Reihe: Management for Professionals
Inhalt: xv
174 S.
33 s/w Illustr.
6 farbige Illustr.
174 p. 39 illus.
6 illus. in color.
ISBN-13: 9789811957185
ISBN-10: 9811957185
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Sah, Prakash
Auflage: 1st ed. 2022
Hersteller: Springer Singapore
Springer Nature Singapore
Management for Professionals
Maße: 241 x 160 x 17 mm
Von/Mit: Prakash Sah
Erscheinungsdatum: 07.11.2022
Gewicht: 0,459 kg
preigu-id: 122102961
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