Yet, while those in financial services today understand the necessity for high-quality data, for many of them, the process of developing a data quality program is harder than they expect. Of the businesses we spoke with, 54 percent said they found the process of building a business case for data quality to be difficult, and 77 percent believed that too many stakeholders were involved in the process. Given the challenges around building a business case, it’s not surprising that most financial institutions that embark on data quality programs take 6-12 months to fully implement it.
In order to expedite this processes and achieve success, it’s critical to identify some of the common challenges other organizations have encountered, and work to address them before you begin your own program. Through our study, we identified a lack of budgets and return on investment (ROI) as leading obstacles that organizations face. This is likely due to an inability to quantify the effects of poor data quality on the business, which is a common hurdle we see stakeholders face when asking for funding. Obviously, it can be difficult to determine budget and return on investment when you don’t understand the monetary impact on the business.
If you’re in a similar circumstance, building a case for a data quality program can be easy if you think about the broader effects of bad data on the business. For instance, can data quality issues be linked to wasted time? Do data quality issues make your business processes inefficient or unachievable? Can data quality We help organizations like yours improve their data quality every day. Let us help you build a business case! Use our worksheet to get started. Start my proposal issues increase risk to the business, such as regulatory risk, or negatively impact brand value? If you’re able to answer these questions, you’re well on your way to building a business case.
Conclusion
If your financial institution is putting forward a proposal for a data quality program, you will want to focus your efforts around strategic business initiatives that are specific to your organization. These might include objectives like achieving regulatory compliance, increasing revenue, improving worker productivity, enhancing the customer experience, or expanding market penetration. By focusing on strategic areas for your business, decision makers will find it much easier to see the value in your data quality program.