 | Big Data for Big Decisions: Building a Data-Driven Organization Subjects: Computer Science; Economics Finance Business & Industry; Management of IT; Business Management and Marketing; Databases; Data Preparation & Mining; Building a data-driven organization (DOD) is an enterprise-wide initiative that may consume and lock-up resources for a long term. Understandably, managers in organizations considering such an initiative would insist on a roadmap and a business-case to be prepared and evaluated prior to approval. Executive management would expect any such DDO initiative to have a clearly defined scope, objectives, and measures of success including a quantified monetary return from data-driven decisions. To meet this need, Big Data for Big Decisions: Building a Data-Driven Organization covers this white-space. It presents a step-by-step methodology to create a roadmap and business case and provides a narration of the constraints and experiences of managers who have attempted setting-up a data-driven organization. Many CIOs are struggling to explain to senior management the value an organization can gain from analytics. Given the hype in the market for Big Data, analytics, and AI, every organization has a budget for analytics, but very few make any headway. Most companies end-up investing into a visualization platform, which basically is an improved version of their business intelligence (BI) dashboard. Industry analysts have estimated that more than 75% of all analytics projects fail to deliver any value. This book provides a method to ensure materially improved decision-making and demonstrable value from investments in analytics. The book emphasizes "Big Decisions," which are the 10% of organizational decisions that influence 90% of business outcomes and are the key-decisions that seriously affect the profitability and growth-potential. Qualitative improvement of such key-decisions made on the basis of actionable insights have the potential to determine an organization's competitive advantage in the market. Also covered are: Decision prioritization The concept of knowns and unknowns Johari window for the organization as a person Decision prioritizationEvery enterprise aspires to become 100% data driven. This book provides guidance for such endeavors and encouragement for organizational managers as they make the data journey. Introduction Part I Foundation Chapter 01 Quo Vadis: Before The Transformational Journey Chapter 02 Decision-Driven Before Data-Driven Chapter 03 Known's, Unknowns And The Elusive Value From Analytics. Chapter 04 Towards A Data-Driven Organization: A Roadmap For Analytics Chapter 05 Identifying The 'Big' Decisions... Chapter 06 Decisions To Data: Building A 'Big' Decision Roadmap & Business Case Part II Data Strategy & Governance Chapter 07 Unchartered: A Brief History Of Data Chapter 08 Building A Data-Driven 'It' Strategy Chapter 09 Building A Data Strategy Part III Data-Driven Marketing Function Chapter 10 Building A Data-Driven Marketing Strategy Chapter 11 Integrated Data Governance |
