Monetizing Data Management: Finding the Value in your Organization’s Most Important Asset, by Peter Aiken and Juanita Walton Billings
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.
What is data? An objective definition
Data leveraging requires architectural and engineering disciplines
What is data management?
Why is data management important?
An incorrect educational focus
Lack of agreement over who is responsible for data assets
Value-added data management is derived from data-centric development best practices
Data-centric approach leads directly to organizational productivity advantages
Data management consists of five integrated practice areas
Improving organizational data management maturity
Data management pay-offs
How many times do we have to spend that money? ($10 million annually)
Who’s doing what, and why? ($25 million annually)
Three ERP cases that also apply to software application package implementation
How much will the data conversion cost? (2 Years and $3,000,000)
How about measuring before deciding to customize? (If $1 million is substantial)
Is it really that complicated? ($5,500,000 and a person-century of labor savings)
Real solution cost ($30,000,000 versus a roomful of MBAs)
Two tank cases
Why are we spending money on stuff we can’t even use? ($5 billion)
The vocabulary of tanks ($4 million alternative to software package customization)
The additional 45% is worth $50 million
What happened to our funding? (at least $1 million in government funding)
But data stuff is complicated; how do I explain it? (£500 really increased project clarity)
Determining objective selection criteria for legacy system consolidation (and avoiding a Congressional inquiry in the process)
Everyone has bills to pay (but some bills are more equal than others)
Identifying payment error correction and boosting troop morale? (priceless)
Saving warfighter lives (friendly fire death prevention)
Saving warfighter lives (US Army suicide prevention: a clear data governance success)
Distinct incentives: Data management saves legal costs
Issue #1: Who owned the risks?
Issue #2: Who was the project manager?
Issue #3: Was the data of poor quality?
Issue #4: Did the contractor (Company Y) exercise due diligence?
Issue #5: Was Company Y’s approach adequate?
Issue #6: Were required standards of care followed, and were work products of the required quality?
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:
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.
Peter Aiken is acknowledged to be a top data management authority. As a practicing data manager, consultant, author, and researcher, he has been actively attempting to improve this area for more than 25 years. His expertise has been sought by some of the world’s most important organizations, and his achievements have been recognized internationally. In addition to examining more than 500 data management practices, he has spent multi-year immersions with organizations as diverse as the US DoD, Deutsche Bank, Nokia, Wells Fargo, and the Commonwealth of Virginia. As President of DAMA International (dama.org), his practice leadership is unquestioned. He has been a member of the Information Systems Department at Virginia Commonwealth University’s Business School since 1993 and jointly owns, with the University, Data Blueprint(.com) an award-winning, data management/information technology consulting firm.
With over 30 years of broad experience in the public, private and academic sectors, Juanita Walton Billings is a pragmatic, ISO-certified business professional who specializes in analysis, design and auditing of enterprise architectures. Beginning her career as a clerk-typist for a mortgage banking firm, she worked her way up through positions requiring a more sophisticated and technical skill set. She went on to earn a BBA/MIS at James Madison University and an MS/IS at Virginia Commonwealth University. Employed by CMU/SEI to conduct a comparison of the pivotal Zachman Framework and the then-evolving Department of Defense Architecture Framework, she was introduced to enterprise architecture. Since then, she has established a proven track record based on experience and knowledge gained at the Office of the Attorney General for the Commonwealth of Virginia and various commands, services and agencies of the Department of Defense, in addition to that acquired in privately held legal, health care, banking, not-for-profit, insurance and bonding, retail and construction organizations. She served on the Department of Defense Data Metamodel working group, and she is a published author as well as a former entrepreneur and instructor in the field of management information systems. Her self-proclaimed most-valued professional assets include a keen eye for detail and the ability to act as a bridge between technical staff and business users.
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