Understanding your customer is one of the keys to success in business. Thanks to big data and analytics, enterprises have more tools and information than ever to compile detailed profiles of customers in order to better serve them and anticipate their needs.
But volume isn’t the only consideration when it comes to leveraging data: The quality of the data is integral to an enterprise’s success in gaining actionable insights. A new study by Forbes Insights brings home that point.
“The problem for many companies is that understanding the data can be complicated by various quality issues: distributed and decentralized storage, duplicate (or multiple) records, and records that are otherwise incomplete or inaccurate,” the study notes. “This often leads to multiple records for the same customer, with conflicting or missing information in many records. Rather than facilitating a single or 360-degree view of each customer, these classic scenarios are emblematic of poor data quality.”
One immediate impact of poor data is decreased efficiency. As research firm Gartner concludes in its report, “Measuring the Business Value of Data Quality,” data quality affects overall labor productivity “by as much as a 20%.”
If that sounds like a nightmare, the strategic implications of poor data quality are even more troubling: Enterprises can make disastrous decisions based on bad customer data because that data can misrepresent who their customers are. As the Forbes Insights study notes, “Companies that continue to manage customer information in disparate silos characterized by duplicated, incomplete and invalid data will do so at a disadvantage, and will likely fail to fully realize the benefits of initiatives built around customer experience or engagement.”
Does your enterprise have quality controls in place for its data?