It is a commonplace to say we should manage data like a resource. But when you think about it, data is an asset but not a resource.  Data isn’t a thing like real estate, employees, or customers, but rather it represents all of those things.  In data-geek-speak, data is a meta-resource that holds information about resources.  That makes data a lot like money.

In his book Money Mischief Milton Friedman made the point that money has no intrinsic value: “The value of money is the value people attribute to what they want to exchange, no more, no less.” Likewise, data has no value in itself.  Its value is derived from people’s desire to know about the things the data describes, and how reliably and accurately it describes those things.  So an organization’s data, like its money, is not a resource in itself.  It is an asset that represents the resources that an organization manages and controls.  It follows then that data management should look a lot like money management.

A cornerstone of our economic stability is consensus that organizations must manage money well and make their internal money management visible to investors, regulators, and independent standards groups.  We’ve evolved a standard for money management where a department represented by a C-level executive administers formal accounting, budgeting, planning, and financial reporting.  The organization evaluates every manager’s compliance to money management policies, and independent auditors evaluate the organization’s soundness in terms of its money management.  Accounting professionals meet rigorous, generally respected certification standards.

Overall, our volume of online purchases and use of FDA-approved drugs, for example, attest to our general confidence in current data management practices.  But still, data  professionals know that it could be a lot better.  Scarcely a week goes by without another scandal involving lost customer data, and consider these snafus:

• This article cites multiple non-compliant databases as a significant contributor to the chaos in reuniting families in the wake of the Katrina disaster
• “The Mars Climate Orbiter, a key part of NASA’s program to explore the planet Mars, vanished in September 1999 after rockets were fired to bring it into orbit of the planet. An investigative board later discovered that NASA engineers failed to convert English measures of rocket thrusts to newtons, a metric system measuring rocket force, and that was the root cause of the loss of the spacecraft. The orbiter smashed into the planet instead of reaching a safe orbit.” (cited here)
• One Fortune 1000 services company carried separate customer records in each of its operating units resulting in a number of anomalies visible to the customers.  For example, the same customer would receive separate invoices with different terms for each of the services purchased from the company.

In parallel with emergence of these types of issues, regulators and industry associations have set data management standards for many industries and practice areas.   Food and consumer product safety rests on a regulatory foundation of correctly recording and managing results of inspections.  The International Air Transport Association sets standards for safety data collection and management.  Likewise, the US Food and Drug Administration and other governing bodies set clinical safety data management and reporting standards.

It is just a matter of time before the many separate externally imposed data management guidelines congeal into a a set of general best practices that apply across the organization.  Then investors, regulators, and standards groups will hold organizations responsible for effective data management in the same way they are held to account for effectively managing money. An internal department represented by a C-level executive will administer formal data management standards and procedures.  The organization will evaluate every manager’s compliance with data management policies, independent auditors will evaluate the organization’s soundness in terms of the quality of its data management, and data management professionals will be held to rigorous, generally respected certification standards.

Farfetched? Maybe.  But it isn’t farfetched to think that as a society we’ll begin to recognize what data professionals have known for a long time: that the quality of an organization’s products, its care of and protection of its customers, workforce, resources, stewardship of the environment, and even its financial health depend to a significant degree on sound data management practices.

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Here are some resources on data management:

DAMA, the organization for data management.

The Wikipedia page quotes this definition: “Data management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets.”

Data Stewardship Strategy: 6 Keys to Success by Jill Dyché: “As executives increasingly agree that data is a corporate asset, they are also funding data governance and data quality efforts more willingly. But … entrenched organizational behaviors are much more difficult to shift. Many companies have introduced the role of data steward before fully defining the role. In these cases, the beleaguered data stewards are doomed before they even begin. ”

Leverage Data Quality to Build an Effective Enterprise Architecture by Mark Amspoker.  “It might be time to rethink the notion that effective information architecture development will solve the data quality problem.”

Guidelines for Responsible Data Management in Scientific Research from the Office of Research Integrity, US Department of Health and Human Services.   “Data management is one of the essential areas of responsible conduct of research, as outlined by the Office of Research Integrity. This educational course will educate new investigators about conducting responsible data management in scientific research.”