A New Way of Thinking – July 2004

Published in TDAN.com July 2004

About a year ago, in one of my first articles for TDAN.com, I introduced some ideas regarding the development of a Return on Investment (ROI) model for information quality. Conceptually, the need
for developing a business case in practically a no-brainer; however, until the recent recession, the development of the business case for information technology investments was largely viewed as an
administrative task. Today, not only is a business case necessary to convince senior management of the value of technical solutions, it is moreover seen as a management tool to shape the direction
of technology investments. In essence, the savvy information technology manager with a long-term view will want to deploy tactical business cases as part of a long-term information strategy.

In the year that has passed since my original ROI article, I have seen a growing interest in this area from prospects, clients, and even some experts in the field. I have gained some insights
through observations made over that time period that I think may provoke valuable thought processes, and so this issue’s column is devoted to further explorations on Information Quality ROI.
Here are my observations, in no specific order:

Observation 1: The people expected to develop ROI or business justifications are not always the right people to do it.

Historically the role of information quality stewardship has fallen to the Information Technology staff, mostly due to the fact that the approaches to addressing information quality problems are
technical solutions (e.g., address standardization, data cleansing, etc.). Not only that, when data problems are exposed to the end-client, the assumed culprits are the IT staff, who innocently
assume the roles associated with information quality problem remediation. It is likely that the same individuals are tasked with justifying the costs associated with information quality
improvement. While these people are good at information management, they are probably not trained in business, and it is even less probable that they have ever seen a reasonable ROI model, let
alone construct one. When stewardship is a responsibility shared by both business and information professionals, building the business case for information quality improvement should be a shared
task.

Observation 2: Monetary impacts associated with specific information quality problems are necessarily related to the value of the information that is flawed as well as the baseline costs
related to unflawed information.

If you are willing to believe what you can read in organizational information stewardship policies, there are some stirrings in the business community to start looking at information as a corporate
asset. The implication is that there is some intrinsic value to the information for its role or use within the company, whether that is in terms of using information to run the business or to
improve the business. Poor quality degrades the value of information.

Observation 3: Information Valuation is, at best, misunderstood, and at worst, an extremely flawed academic exercise.

Despite the approach to treating information as an asset, I still have not yet seen a company’s information listed in its balance sheet. While I have seen some interesting ideas with respect
to information valuation, most people I know struggle with the concept. As recently as this past Spring I sat in on a talk whose title had some promise in terms of the holy grail of a method for
information valuation, but was relatively disappointed. It is very difficult to gauge the loss of value of information caused by poor information quality when approaches to quantifying information
value are so tenuous.

Observation 4: Companies are obsessed with “hard” dollars.

Senior managers are more swayed by “hard” dollar justifications than “soft” ones, even if the soft benefits are much more compelling. Instituting a program to monitor and
improve information quality not only can decrease costs associated with scrap and rework, it can also improve the value of the information asset, which can be used more effectively in many ways,
including risk reduction, opportunity creation, and organizational efficiency. However, most organizations cannot allow for the quantification of potential benefits that are not sure bets.
Therefore, the business case for investing in the information quality program is better when tied to hard dollars, which typically relate to cost reduction (i.e., elimination of routine scrap and
rework) or cost avoidance (i.e., specific recognizable instances of auxiliary costs incurred when an error is detected; one example is a regulatory fine).

Observation 5: Improvement value is not always measured in monetary units.

Despite the focus on hard dollars, not every benefit to be had from information quality improvement is always measured is currency. Social health and welfare, civil service, the police, medical
research groups, etc., all rely on information to get their job done, although the success of each job may be measured in terms of reduced crime, increased child support, fewer deaths, longer
lives, fewer plane crashes, etc. Each of these kinds of organizations routinely rely on information as much as their for-profit counterparts, and they are not immune to information quality
problems. Consequently, it should not be viewed as unreasonable to calculate return on investment using specific metrics derived within any specific business context.

Observation 6: As with any proactive measure, the benefits of information quality must be seen in terms of the value of prevention of problems.

We clearly see the sense in periodically changing the oil in our cars, and not brushing our teeth would be seen as ridiculous. Those with health insurance policies don’t see paying a monthly
premium as being unreasonable either. But if one does not change the oil on the car, does not necessarily imply that the car will break down on the highway? Of course not – instead, it just
increases the probability of a break down. Each of these examples involves periodic proactive measures taken to prevent something bad from happening. In other words, we are willing to invest either
time, money, or both up front to reduce the probability of a potential problem. Proactive information quality programs should be seen in the same light – an up front investment that reduces
the probability of failure in the future.

Observation 7: The body of experience and knowledge regarding costs associated with information quality problems remains largely uncollected.

It is desirable to look at information quality investments in the same way as health insurance. However, health insurance products are developed, priced, and sold based on a comprehensive actuarial
basis related to the population of individuals to be covered, the kinds of health risks that exist, and the cost impacts associated with addressing illnesses within a specific geographic area.
Years of information contributing to a significant body of historical knowledge helps health insurance organizations are used to determine the best ways to keep their members healthy.
Unfortunately, the body of experience associated with different kinds of information quality problems across different industries, and their corresponding impacts is largely drawn from individual
business cases along with a multitude of anecdotes, which prevents a serious evaluation of industry-based analysis of information quality impacts.

I have come to two conclusions based on these observations. The first is that there may be two different, yet successful, approaches to selling data quality within an organization – a
tactical, bottom-line, hard-dollar approach and a strategic, forward looking, information value improvement approach. When considering building your information quality business case, consider
which approach will be more likely to succeed within your organization.

The second conclusion is that there is a need for more detailed research into accumulating that body of knowledge regarding the costs of poor information quality. To that end, Knowledge Integrity
will be embarking on a research study to better understand information quality ROI, and to that end I am seeking individuals who would be willing to share their experiences with me regarding how
they assessed the costs related to the value of information quality, how they built a business case or ROI model, the kinds of systems employed to track performance against original estimates, and
what the resulting return on information quality investment. If you are interested and willing to participate in this study, please send email to me at loshin@knowledge-integrity.com. All participants will receive a copy of the study report, which I hope to summarize in a future TDAN column.

Copyright © 2004 Knowledge Integrity, Inc.

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About David Loshin

David is the President of Knowledge Integrity, Inc., a consulting and development company focusing on customized information management solutions including information quality solutions consulting, information quality training and business rules solutions. Loshin is the author of The Practitioner's Guide to Data Quality Improvement, Master Data Management, Enterprise Knowledge Management: The Data Quality ApproachÊand Business Intelligence: The Savvy Manager's Guide. He is a frequent speaker on maximizing the value of information. David can be reached at loshin@knowledge-integrity.com or at (301) 754-6350.

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