Seizing Opportunity in Data Quality

The cost of bad data is an astonishing 15% to 25% of revenue for most companies.

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Frontiers

An MIT SMR initiative exploring how technology is reshaping the practice of management.
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Getting in front on data quality presents a terrific opportunity to improve business performance. Better data means fewer mistakes, lower costs, better decisions, and better products. Further, I predict that many companies that don’t give data quality its due will struggle to survive in the business environment of the future.

Bad data is the norm. Every day, businesses send packages to customers, managers decide which candidate to hire, and executives make long-term plans based on data provided by others. When that data is incomplete, poorly defined, or wrong, there are immediate consequences: angry customers, wasted time, and added difficulties in the execution of strategy. You know the sound bites — “decisions are no better than the data on which they’re based” and “garbage in, garbage out.” But do you know the price tag to your organization?

Based on recent research by Experian plc, as well as by consultants James Price of Experience Matters and Martin Spratt of Clear Strategic IT Partners Pty. Ltd., we estimate the cost of bad data to be 15% to 25% of revenue for most companies (more on this research later). These costs come as people accommodate bad data by correcting errors, seeking confirmation in other sources, and dealing with the inevitable mistakes that follow.

Fewer errors mean lower costs, and the key to fewer errors lies in finding and eliminating their root causes. Fortunately, this is not too difficult in most cases. All told, we estimate that two-thirds of these costs can be identified and eliminated — permanently.

In the past, I could understand a company’s lack of attention to data quality because the business case seemed complex, disjointed, and incomplete. But recent work fills important gaps.

The case builds on four interrelated components: the current state of data quality, the immediate consequences of bad data, the associated costs, and the benefits of getting in front on data quality. Let’s consider each in turn.

Four Reasons to Pay Attention to Data Quality Now

The Current Level of Data Quality Is Extremely Low

A new study that I recently completed with Tadhg Nagle and Dave Sammon (both of Cork University Business School) looked at data quality levels in actual practice and shows just how terrible the situation is.

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Topics

Frontiers

An MIT SMR initiative exploring how technology is reshaping the practice of management.
See All Articles in This Section

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Comment (1)
Dante Rossi
Hi Mr. Redman!
Wonderful article, here in Brazil  many executives face decisions without foundation because of their belief in their previous knowledge, they don't care about the data quality or analysis.
Great article with great warning, tips and advices.
Congrats and best regards!!

Dante Rossi