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Monetizing Data Management

Book Description

What's the Return on Investment (ROI) on data management? Sound like an impossible question to answer? Not if you read this book and learn the value-added approach to managing enterprise resources and assets. This book defines the five interrelated best practices that comprise data management, and shows you how by example to successfully communicate data management ROI to senior management. 

The 17 cases we share will help you to identify opportunities to introduce data management into the strategic conversations that occur in the C-suite. You will gain a new perspective regarding the stewardship of your data assets and insulate your operations from the chaos, losses and risks that result from traditional approaches to technological projects. And you will learn how to protect yourself from legal challenges resulting from outsourced information technology projects gone badly due to incorrect project sequencing and focus. With the emerging acceptance and adoption of revised performance standards, your organization will be better prepared to face the coming big data deluge! 

The book contains four chapters:

  • Chapter 1 gives a somewhat unique perspective to the practice of leveraging data. We describe the motivations and delineate the specific challenges preventing most organizations from making substantial progress in this area.
  • Chapter 2 presents 11 cases where leveraging data has produced positive financial results that can be presented in language of immediate interest to C-level executives. To the degree possible, we have quantified the effect that data management has had in terms that will be meaningful to them also.
  • Chapter 3 describes five instances taken from the authors' experiences with various governmental defense departments. The lessons in this section however can be equally applied to many non-profit and non-defense governmental organizations.
  • Chapter 4 speaks specifically to the interaction of data management practices, in terms of both information technology projects and legal responsibilities. Reading it can help your organization avoid a number of perils, stay out of court and better vet contractors, experts and other helpers who play a role in organization information technology development.


From John Bottega Foreword: 
Data is the new currency. Yes, an expression that is being used quite a bit of late, but it is very relevant in discussing the importance of data and the methodologies by which we manage it. And like any currency, how we manage it determines its true value. Like any currency, it can be managed wisely, or it can be managed foolishly. It can be put to good use, or it can be squandered away. The question is – what factors determine the path that we take? How do we properly manage this asset and realize its full value and potential? 

In Monetizing Data Management, Peter and Juanita explore the question of how to understand and place tangible value on data and data management. They explore this question through a series of examples and real-world use cases to exemplify how the true value of data can be realized. They show how bringing together business and technology, and applying a data-centric forensic approach can turn massive amounts of data into the tools needed to improve business processes, reduce costs, and better serve the customer. Data monetization is not about turning data into money. Instead, it's about taking information and turning it into opportunity. It's about the need to understand the real meaning of data in order to extract value from it. And it's about achieving this objective through a partnership with business and technology. In Monetizing Data Management, the authors demonstrate how true value can be realized from our data through improved data centric approaches.

Table of Contents

  1. Table of Contents
  2. Acknowledgements
  3. About the Authors
  4. Foreword
  5. Executive Summary
  6. Chapter 1: Data Management as a Prerequisite to Data Leveraging
    1. Data leveraging requires architectural and engineering disciplines
    2. What is data management?
    3. Why is data management important?
    4. An incorrect educational focus
    5. Lack of agreement over who is responsible for data assets
    6. Value-added data management is derived from data-centric development best practices
    7. Data-centric approach leads directly to organizational productivity advantages
    8. Data management consists of five integrated practice areas
    9. Improving organizational data management maturity
    10. Data management pay-offs
  7. Chapter 2: Bottom Line Pay-offs: Eleven Financial Cases
    1. Who’s doing what, and why? ($25 million annually)
    2. Three ERP cases that also apply to software application package implementation
    3. Real solution cost ($30,000,000 versus a roomful of MBAs)
    4. Two tank cases
    5. The additional 45% is worth $50 million
    6. What happened to our funding? (at least $1 million in government funding)
    7. But data stuff is complicated; how do I explain it? (£500 really increased project clarity)
  8. Chapter 3: Real Live Pay-offs: Five Non-Monetary Cases
    1. Everyone has bills to pay (but some bills are more equal than others)
    2. Identifying payment error correction and boosting troop morale? (priceless)
    3. Saving warfighter lives (friendly fire death prevention)
    4. Saving warfighter lives (US Army suicide prevention: a clear data governance success)
  9. Chapter 4: And Then There Are the Lawyers: An Illustrative Legal Matter
  10. Conclusion: Your Charge
  11. References