In this post, we take a look at the recent publication "Data Driven" (Profiting From Your Most Important Business Asset) by Tom Redman.

We also speak with Tom to discuss some of the themes of the book and his views on the data quality industry.

Plus, we're giving away a number of Data Driven books to members of Data Quality Pro so read on for details of how to enter the draw for your copy.

Data Driven: Book Review

Tom "Data Doc" Redman is widely regarded as one of the founding fathers of data quality.

Following his earlier pioneering work in extending quality principlies into the world of data at the AT&T Bell Laboratories Data Quality Lab he went on to publish several books which are, even several years later, still essential reading for data quality practitioners and organisations focused on addressing data quality improvement.

His latest book, "Data Driven", focuses on the benefit of data as a corporate asset and provides a series of techniques and methods to help organisations harness data as a competitive weapon.

The book is structured into 4 main sections:

Part One
Introduction
Chapter 1: The Wondrous and Perilous Properties of Data and Information in Organizations

Part Two
Chapter 2: The (Often Hidden) Costs of Poor Data and Information
Chapter 3: Assessing and Improving Data Quality

Part Three
Chapter 4: Making Better Decisions
Chapter 5: Bringing Data and Information to the Marketplace: Content Providers
Chapter 6: Bringing Data and Information to the Marketplace: Facilitators

Part Four
Chapter 7: Social Issues in the Management of Data and Information
Chapter 8: Evolving the Management System for Data and Information
Chapter 9: The Next One-Hundred Days

The main body of the book comes in at just over 200 pages and is aimed predominantly at the business reader who has the capacity to make serious improvements.

Whilst there are numerous references to data quality improvement techniques, these are presented in a far more business-friendly manner than many other data quality publications currently available. As a result  most readers should find it simple to digest and understand the core concepts.

A central theme of the book is teaching organisations how to profit from their own data after it has been improved. This is an excellent concept and most organisations overlook just how valuable their data assets are. This should really appeal to those business leaders who are looking for extra value-add from their data quality improvement initiatives.

The book takes the reader on a journey through the nuts and bolts of data quality improvement all the way through to data asset capitalisation and then finally closing with a 100 day action plan which is clearly drawn from Tom's own experiences at the sharp end of data quality consulting.

In summary, a great addition to any data quality bookshelf. Business focused, highly readable and adds some invaluable new concepts and techniques for the profession so it comes highly recommended.

For more information on the book and to read numerous reviews please click here.

The book can be purchased directly from our online bookshop, click here.

Want to win a copy of Data Driven?

To enter the draw all you need to do is send us a message via our contact page (click here) telling us what you would like to see published on Data Quality Pro next month.

DQ Tutorials? Product reviews? Professional interviews? DQ challenges?

What are the burning issues you would like us to publish content on? In return for your submission you will be entered into the draw for a free copy of Data Driven.

Following the review we contacted Tom to pose him a few questions regarding the book and his thoughts on the current data quality industry, his responses are provided below.

Tom Redman Interview

Data Quality Pro: Your first data quality book was released in 1992. What are your thoughts 16 years down the line - do you feel organisations are smarter at managing the quality of their data than they were 16 years ago?

Tom Redman: This is an interesting question.

Sixteen years ago I worked at Bell Labs and my primary client was AT&T. The years surrounding 1992 were an amazing period of innovation, as we figured out how to adapt the techniques of quality management for manufactured product to data. I had one foot in the Labs and one foot in enormous AT&T problems. We took enormous strides, both in figuring out how to address data quality and in saving the company hundreds of millions of dollars.

In 1992, my window outside AT&T was pretty narrow. Computer scientists had coined the phrase "Garbage In, Garbage, Out," but most people and companies didn't think too much about their data.

Today everyone I talk to knows that data quality is an enormous problem. And opportunity. But most companies aren't approaching the problem properly.

So I guess the answer to your question is this: "More organizations are aware. But most aren't as smart."

Data Quality Pro: There is obviously a great deal of focus on business stakeholders in "Data Driven", and the financial sector in particular. In light of the global credit crisis, do you think we'll see greater DQ governance and improvement when the dust settles?

Tom Redman: I sure hope so.

Poor quality data aren't the only cause of the current crisis, but they are right up there. And I can't see how we get out of this crisis and start growing the economy again without far better data.

But nothing is certain. There are already calls for greater regulation.

You may recall similar calls after the Enron scandal about seven years ago. In response, the US enacted Sarbanes-Oxley and companies spend an enormous amount of time and effort complying. But today banks don't trust one another's balance sheets.

So in my view Sarbox failed.

This is not to say we don't need regulation. We do. We just have to be a whole lot smarter about it than we were with Sarbox.

It is even more important that company leaders view financial reform as their responsibility. They must focus on customers, improve transparency and accuracy, make financial statements easier to understand, and get in the habit of continuous improvement.

By the way, data quality professionals MUST create opportunities to help company and government leaders understand these points. The stakes are very, very high.

To net all these factors out, I'm cautiously optimistic.

Data Quality Pro: I particularly liked your "100 Day Panorama" section in the book. One thing that impressed me was the lack of focus on data quality tools in favour of simple, practical techniques. Do you feel that there is too much emphasis on technology to solve DQ issues?

Tom Redman: First, thanks. I'm glad you liked the 100-day panorama. It's proving pretty effective.

The answer to your question is a bit involved. The first point is that technology alone can't solve any important data quality problems. Improving data quality requires leadership and management and I've yet to see the technology that can supply them. So in many cases there is not just too much emphasis on technology. That emphasis is wrong-headed.

The second point is that technology can be very effective at helping lock in the gains after one improves a process. For example, once a business is well-defined and managed, one can use technology to automate data edits and stop simple errors in their tracks. That is nearly impossible if the process is not well-defined and managed.

So we need technology. We just need it to be far more supportive of good management.

Data Quality Pro: You allude many times in the book to our insatiable desire for data. With data volumes continuing to climb ever higher, do you ever feel we will reach a point where DQ management is simply not sustainable?

Tom Redman: Personally, I think we're either in the late Stone or early Bronze Age when it comes to DQ management.

Most data, in most organizations is simply not very good. I'm often amazed at how far and fast organizations can improve with relatively simple tools. I think many of the underlying principles of data quality management will hold up for a long time. For example, I don't think we'll ever outgrow "hold those who create data responsible for their quality." Similarly, focusing on the most important data will never go out of style.

That said, surely we will need new techniques as demands for quality and data volumes grow. Remember it is not just more data. It is also different kinds of data and more and different customers with different needs.

Data Quality Pro: Finally, many of our members are senior managers from organisations starting out on their DQ journey. What advice does the book offer these folks for sustaining a data-driven organisation?

Tom Redman: I find that most senior managers intuitively understand that data have the potential to be assets on par with other assets such as capital and people. But they don't know how to manage them to unlock the potential.

Data Driven offers three, inter-related prescriptions:

• Improve the quality of all important data by at least an order of magnitude.
• Put your data to work. There are many ways to do so, but the most important is to bring data to market, either selling them directly or using them to enhance other products and services.
• Recognize that data have properties that present both opportunities and perils unlike any other asset. Evolve your management systems to accommodate these properties.

Of the three, I think senior management needs to focus most on the second prescription, putting data to work. After all, that is the entire thrust of the Information Age.

About Tom Redman

Thomas C. Redman, “the Data Doc,” is President of Navesink Consulting Group, which he founded in 1996. Dr. Redman was the first to extend quality principles to data and information and he is the leading inventor of practical techniques that help organizations improve. His clients report from order-of-magnitude improvements and reap many benefits. Prior to founding Navesink, Tom established the AT&T Bell Laboratories Data Quality Lab in 1987 and led it until 1995. Recently he has turned his attention to the ways companies can put their data to work, in their marketplaces, and the nettlesome issues associated with managing data as a business asset. Dr. Redman has written dozens of papers and three previous books. He holds two patents.