The power of truth in credit union analytics
Data generation continues to grow at an exponential rate throughout the credit union industry. In order to hear the signals through the noise, credit unions must establish a single version of the truth.
New technologies are enabling credit unions to collect a vast array of data only dreamed about in the past. However, this massive amount of data will only create more confusion if it is not organized into a single version of the truth (SVOT). Agreement on data definitions and how data is collected, integrated and acted upon is paramount. Analytics will only have power if all employees can agree and rely on a SVOT. If conflicting information and disagreements on what data to trust continue, analytics will only cause more confusion instead of uniting the credit union around the truth.
Single Version of Truth (SVOT)
The SVOT can be defined as:
“A single set of reports and definitions for all business terms, a way, in short, to make sure every manager has a common understanding of accurate corporate information.” -Frank Buytendijk
A SVOT brings unity to a credit union by granting employees access to accurate corporate information in business terms everyone can easily understand and agree on. For example, if the executive team wants to know how many members exist within the credit union, analysts can simply access the SVOT to determine exactly how many members there have. Unfortunately, if analysts within a credit union are asked this question today, they will have widely different answers (even in the same department)! The reason these answers are so different is the lack of a SVOT and the vision of management to grant credit union analysts access to its power.
Data Quality
The foundation of the SVOT is quality data stored within databases. Before credit unions can build the SVOT, the data they are working with must be reliable from its source. Since the SVOT is downstream from its data sources, it is only able to reflect data from the source. Without high quality data feeding the SVOT, analysts will be agreeing on incorrect data. If the credit union develops a SVOT with unreliable data, they will have false confidence in data while making critical decisions. Once quality data is collected from its sources, a credit union can begin constructing the SVOT.
Data Sources and Derived Data
Determining how to integrate the various business systems (along with data derived from 3rd party sources and analytic models) into a data warehouse is the next step in erecting the SVOT. Every business system houses data about members that is also stored simultaneously in other business systems. For example, the CRM and core system might have different email addresses for a member. Determining which data element (from what system) should be considered the system of record (or “Golden Record”) is the next perquisite in solidifying the SVOT.
SVOT in Context: Business Processes
After integrating data and establishing a SVOT, credit unions must build views of the truth for different business processes. These views will empower employees to make proactive decisions that will bring excellence into the credit union. The context of each business process must be taken into account before developing standard datasets for decision making. Utilizing the SVOT, employees will be united in the business process they are working to improve. Analytics derived from the SVOT will empower credit unions to revolutionize their business processes.
Analytics: Truth in Action
Establishing high quality data, a SVOT, and implementing different views of that truth (based on business processes) will give credit unions a clear understanding of their data. Establishing a SVOT will bring employees together to build the credit union of the future. With a SVOT as their foundation, credit unions will be able to excel in serving members and staving off competition. The power of truth within analytics will empower employees to make better decisions that will strengthen their credit union and enable more efficient collaboration within the industry.
