Sah Defining Enterprise Data and Analytics Strategy

Pragmatic Guidance on Defining Strategy Based on Successful Digital Transformation Experience of Multiple Fortune 500 and Other Global Companies
1. Auflage 2022
ISBN: 978-981-19-5719-2
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 174 Seiten, eBook

Reihe: Management for Professionals

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Sah, Prakash

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 towerWeek-in-the-Life of Data and Analytics TeamSummary
Chapter 5: Fourth Element of Strategy – Organizational Change ManagementDriving and managing change across the enterprise to ensure successNeed 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 managementDriving Change - Focus Areas & Objectives? Four Focus Areas – People, Processes, Technology, and Data? Three OCM Objectives? Twelve OCM Strategy Elements for Data and AnalyticsStages of Change & Change Leadership? The Three Stages of Change? Importance of Change LeadershipSummary
Chapter 6: Fifth Element of Strategy – Value Measurement FrameworkEstablishing a framework to define and measure value of data and analytics programThe Need for a Value Measurement FrameworkDefining 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 causalityDefining and Measuring Operational Efficiency – Continuous Improvement? People performance? Process effectiveness? Technology capability? Data maturity? Operational efficiency and maturity assessmentCalculating ROI from Data and Analytics Investment? Calculating benefits? Calculating costs? Calculating ROISummary
Chapter 7: The Profile of a Data and Analytics LeaderKey skills of a leader who can lead the enterprise to successKey Skills that any Enterprise Data and Analytics Leader Must PossessHard Skills? Technology? Data science? BusinessSoft Skills? Dealing with ambiguity? Team leadership? Innovation and risk-taking? Organizational change management? Design thinking and empathy? MarketingSummary

Über Autor(innen)

Linked-in profile: https://www.linkedin.com/in/prakash-sah-9581964/