Big Data for Big Decisions: Building a Data-Driven Organization

Building a data-driven organization (DDO) is an enterprise-wide initiative that may consume and lock up resources for the long term. Understandably, any organization considering such an initiative would insist on a roadmap and business case to be prepared and evaluated prior to approval. This book presents a step-by-step methodology in order to create a roadmap and business case, and provides a narration of the constraints and experiences of managers who have attempted the setting up of DDOs. The emphasis is on the big decisions - the key decisions that influence 90% of business outcomes - starting from decision first and reengineering the data to the decisions process-chain and data governance, so as to ensure the right data are available at the right time, every time.

Investing in artificial intelligence and data-driven decision making are now being considered a survival necessity for organizations to stay competitive. While every enterprise aspires to become 100% data-driven and every Chief Information Officer (CIO) has a budget, Gartner estimates over 80% of all analytics projects fail to deliver intended value.

Most CIOs think a data-driven organization is a distant dream, especially while they are still struggling to explain the value from analytics. They know a few isolated successes, or a one-time leveraging of big data for decision making does not make an organization data-driven. As of now, there is no precise definition for data-driven organization or what qualifies an organization to call itself data-driven. Given the hype in the market for big data, analytics and AI, every CIO has a budget for analytics, but very little clarity on where to begin or how to choose and prioritize the analytics projects. Most end up investing in a visualization platform like Tableau or QlikView, which in essence is an improved version of their BI dashboard that the organization had invested into not too long ago. The most important stakeholders, the decision-makers, are rarely kept in the loop while choosing analytics projects.

This book provides a fail-safe methodology for assured success in deriving intended value from investments into analytics. It is a practitioners' handbook for creating a step-by-step transformational roadmap prioritizing the big data for the big decisions, the 10% of decisions that influence 90% of business outcomes, and delivering material improvements in the quality of decisions, as well as measurable value from analytics investments.

The acid test for a data-driven organization is when all the big decisions, especially top-level strategic decisions, are taken based on data and not on the collective gut feeling of the decision makers in the organization.

建立一個以數據為基礎的組織（DDO）是一個企業範圍的倡議，可能需要長期消耗和鎖定資源。可以理解的是，任何考慮這樣一個倡議的組織都會堅持在批准之前準備和評估路線圖和商業案例。本書提供了一種逐步方法，以便創建路線圖和商業案例，並提供了那些嘗試建立DDO的經理人的限制和經驗的敘述。重點是在大決策上 - 影響90％業務結果的關鍵決策 - 從首次決策和重新設計數據到決策過程鏈和數據治理，以確保正確的數據在正確的時間提供。

投資於人工智能和以數據為基礎的決策現在被認為是組織保持競爭力的生存必需品。雖然每個企業都渴望成為100％以數據為基礎的，每個首席信息官（CIO）都有預算，但根據Gartner的估計，超過80％的分析項目未能提供預期的價值。

大多數CIO認為以數據為基礎的組織是一個遙不可及的夢想，特別是當他們仍在努力解釋分析的價值時。他們知道一些孤立的成功，或者一次性利用大數據進行決策並不能使組織成為以數據為基礎的。目前，對於以數據為基礎的組織或者什麼樣的組織有資格稱之為以數據為基礎的，還沒有確切的定義。鑑於市場上對於大數據、分析和人工智能的炒作，每個CIO都有一個分析預算，但對於從何處開始或如何選擇和優先考慮分析項目卻很少有明確的清晰度。大多數最重要的利益相關者，即決策者，在選擇分析項目時很少被納入討論。

本書提供了一種確保從分析投資中獲得預期價值的失敗安全方法。這是一本實踐者手冊，用於創建一個逐步的轉型路線圖，優先考慮大決策的大數據，即影響90％業務結果的10％決策，並提供從分析投資中的決策質量的實質改善以及可衡量的價值。

以數據為基礎的組織的試金石是當所有大決策，特別是高層戰略決策，都是基於數據而不是組織決策者的集體直覺時。

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

導言
第一部分 基礎
第01章 哪裡去：轉型之前的旅程
第02章 決策驅動先於數據驅動
第03章 已知、未知和來自分析的難以捉摸的價值
第04章 走向數據驅動組織：分析的路線圖
第05章 辨識「重大」決策...
第06章 從決策到數據：建立「重大」決策路線圖和商業案例
第二部分 數據策略與治理
第07章 未知領域：數據的簡史
第08章 建立數據驅動的「IT」策略
第09章 建立數據策略
第三部分 數據驅動的市場營銷職能
第10章 建立數據驅動的市場營銷策略
第11章 整合數據治理