By Bruce Leyton
Everyone talks about the importance of data quality—from software vendors to end users such as hospitals and health systems. However, before we talk about why quality matters and how to manage it, shouldn’t we be sure we know what it means? For the purposes of this article, let’s agree that, put simply, quality means the expectation that a product will work as promised, for the use intended, without defect or failure. Inherent in this definition—for all products, not just software—is the idea of meeting the expectations of your customers. When those expectations are not met, consequences can be dire.
Let’s look, for example, at the furniture and home goods store IKEA. The retailer has more than 355 locations in 29 countries, and has a reputation among its customers for good, consistent customer service and quality. Regardless of country or individual store locations, IKEA customers know what to expect. Part of that consistency, which has helped build a loyal customer base and a strong reputation, are the delicious and iconic Swedish Meatballs IKEA serves in its restaurant area. All told, the restaurant sales don’t account for a large portion of the company’s profit margins, but they do contribute to the customer experience the company has worked hard to craft. They stand out as a differentiator that may entice customers to visit an IKEA store and subsequently choose to buy their affordable furniture at IKEA rather than from other competitors at a similar price point.
With such a strong reputation and loyal fan base, the announcement in 2013 that some of the meatballs being sold in IKEA’s European locations contained horsemeat took everyone by surprise. IKEA had not knowingly cut corners or misled its customers; the issue turned out to be a supply chain problem that led to a quality problem, which quickly turned into a public relations problem. IKEA recovered nicely by voluntarily recalling any products that may have been affected, then went above and beyond to retain customer loyalty by announcing a “farm to fork” initiative, which involved audits along every step of the supply chain journey to ensure quality, as well as DNA testing for each individual batch of meatballs.
IKEA learned a valuable lesson from this experience that is applicable to so many other industries, software included. The lesson is, of course, that your products are only as good as the quality of the materials that make up the supply chain. In the software industry, then, this means that the quality of your product relies heavily on the quality of the data that will be ground up and put into it—data, too, needs “DNA testing” for each batch. In either case, it comes down to trust and reliability. If you think quality data isn’t your problem, think again.
Healthcare Data Challenges
As organizations move to align to the new, data-driven paradigm, they are facing challenges within their own data supply chain. This challenge has become particularly apparent within healthcare. The ever-increasing complexity of the healthcare industry and healthcare/patient data is the perfect storm for a horsemeat-level quality crisis. In healthcare in particular, the cost of not having a strategy to maintain data quality can be severe.
Poor quality data in hospitals can lead to duplicate tests, billing and medical errors, and wasted marketing resources, among other problems. Operating without a strong data management solution in place in hospitals has the very real potential to negatively affect patient outcomes; studies have shown that four of every 100 cases involving duplicate records have a negative impact on care, and that more than 100,000 people die annually because of identity or "wrong patient" errors. In addition to patient outcomes, the financial risk is great as well; a study of one hospital in Texas showed that duplicate records made up 22 percent (250,000) of its records, and that each of those records was costing the hospital more than $96.
A Holistic Approach to Data Quality
The solution, managing the data supply chain, lies with not just the quality of the data, or the software solution being used, or the IT team managing the data onsite at the hospital. Rather, the industry needs to start considering data quality as a holistic “supply chain problem.” This data supply chain has many complex parts, and many touchpoints along the way where there is an opportunity to correctly manage the quality, value, cost, and risk associated with these critical data assets.
Remember, IKEA had done nothing wrong, but in their case, someone else’s mistake turned out to be their public relations crisis. Like any other asset, data has a “supply chain” journey, and must be managed as such. Good quality data inputs are the beginning of the journey.
This is how VisionWare looks at the challenge of data management; quality is a tenet of the solutions we build. To learn more about the software we offer for this journey, contact VisionWare by clicking the button below: