Seventy percent of investment banks cite data quality as their biggest day-to-day issue, 59 percent understand the problem but can’t quantify the cost, and barely 11 percent actively measure the cost of bad data. Those were just a few of the key findings from a recent study of 133 buy- and sell-side professionals conducted by Accenture and Greenwich Associates. Put simply: Firms know there is an issue, but many have no real sense of how—or how much—data quality is really affecting their business.
Still, the demand for reference data continues to grow, compounding the risk. The market hit $3 billion in 2015, according to Douglas B. Taylor of Burton-Taylor International Consulting LLC estimates, and has an expected five-year compound annual growth rate of 9 percent. More than one-third of our survey respondents anticipate increases in their data and processing costs. Furthermore, our research suggests that for every dollar spent on reference data input, another two dollars are spent on cleansing, reconciliation and IT.
So what’s the solution?
Just 17 percent of our survey respondents reported developing their data management strategies directly in response to the needs of their business. Many approach data quality as an IT or operations issue, rather than an enterprise-wide opportunity with far-reaching impacts. Investment banks can take three steps to start shifting their perspective:
1. Create space for a CDO.
Most firms already have CDOs, but their role and authority are not always well defined outside of the IT hierarchy. Give your chief data officer (CDO) control of the entire data lifecycle, a clear mandate, a dedicated budget and direct support from senior leadership, including your chief operating officer (COO).
2. Treat data as an asset.
Develop a reference data strategy that addresses your unique business challenges and can evolve with your organization’s changing needs. By thinking about data as an asset instead of a liability, investment banks can identify new ways to create value throughout the organization—ideas and initiatives that can be championed by CDOs.
3. Take advantage of analytics and robotics.
Make sure to use the tools at your disposal. Analytics can help your CDO understand your organization’s relationship with reference data, including which processes use which data, who purchases data and from whom, and where processing bottlenecks exist. Robotic process automation can help eliminate human error and reduce processing costs in a highly scalable, highly flexible way.
Changing how your firm views and manages reference data is no easy feat, but it can have significant impacts on your top and bottom lines. At a certain point, you have to ask yourself if the cost of bad data isn’t greater than the price of change.
For more survey results and data management ideas, read the full report: