The use of data has evolved. At first data were used to record an event or a state of being for future reference. Now data can serve multiple purposes, such as improving business performance, complying with legal mandates, detecting improper payments, and making wiser choices with regard to business partners and customers. We are getting better at making data sweat, so the intrinsic value of data as an asset is increasing. Yet it is the most poorly managed asset in every organization. Why is this? Can we do better? The Consortium for Advanced Management International (CAM-I) Intelligent Data Quality Management (IDQM) working group is tackling this very problem by creating an equation that can place a dollar value on any record of data. And by knowing the value of a record, intelligent decisions regarding its management can be made.
Data are a corporate asset that reduces uncertainty about decisions, affects behavior, and can even have its own market value. When data are compromised by quality problems, not only does the value of data as an asset decrease, but there can also be more extensive consequences (e.g., cost efficiency, risk management, regulatory compliance, agility, revenue growth, readiness).
According to a study performed by Gartner in 2011, poor data quality was a primary reason for why 40 percent of all business initiatives failed to achieve their targeted benefits, and data quality can also affect overall labor productivity by as much as 20 percent. Most importantly, Gartner predicted that as more business processes become automated, data quality will become the rate-limiting factor for overall process quality. This means that no matter how well we improve the performance of a process, eventually we will be constrained by the data that govern that process. This certainly warrants further investigation.
Read the full report addressing the problem of poor data management by creating an equation that places a dollar value on any record of data.
For more information on the subject contact Jeff Lawton.