As credit unions get on board with Big Data and realize the benefits and value of the data they have at their disposal, there continues to be quite a bit of struggle with developing a program to store the right data, and retrieve and successfully utilize the data they collect. Beyond these challenges, data sources in credit unions are more heterogeneous than ever before, and as a result, it can be difficult to pull this data together to create a singular picture. In order to overcome these challenges, credit unions must create and maintain a data governance policy.
The first step in creating a data governance policy is appointing the Data Owner Team. This is a team of individuals within your organization responsible for implementing data management policies and procedures that are aligned to meet the organization’s data objectives and corporate strategy. Identifying the right people for this team is often the most difficult part of building a data governance program. Depending on the size of the credit union, complexity of the data, and data sources, the data owner can be one person or a group of people across different divisions of the credit union.
Unfortunately, by default this role is typically assigned or assumed by the credit unions’ IT department exclusively. There are a number of reasons this presents a problem. First, for most credit unions, IT’s primary role is to keep servers running and software functional for maintaining day-to-day business transactions. This responsibility requires a much different skillset than that of data governance.
Secondly, but most importantly, typically IT lacks the requisite knowledge of the data point definitions and uses of the data. Let’s think about this in practice. I was recently at a credit union where IT was “voluntold” that they would be in charge of the organization’s data. This made sense to the credit union at the time, because the IT department managed the servers on which the data was hosted.
Additionally, there were members of the IT staff that were proficient at report writing. When groups needed reports, they simply submitted a request to IT and within a couple of days (sometimes longer), IT would hand over the report that met the specs that were outlined in the request. All seemed good. Well, it wasn’t until the credit union was involved in a core system conversion that it was discovered that many interpretations of the data and their definitions were incorrect and resulted in a couple years of erroneous reporting. This is just one example of many where data missteps have resulted from credit union management requiring that IT staff stray from their core competency in order to single-handedly manage data collection practices, policies and procedures.
If Not IT, Than Who?
Let’s put IT to the side for a moment and focus on the people within your organization that enter, access, use, decipher, and share your data. Business stakeholders such as lending managers, accounting, senior vice presidents, compliance, marketing, etc. are the people and departments within the organization that consume corporate data as a part of their day-to-day responsibilities. They must rely on good, useful, and meaningful data to carry out their individual functions, which puts them in a better position to validate the data being reported and improve data collection practices. These experts from various areas within the credit unions should be the key members of the Data Owner Team.
How many times have you been in a meeting with coworkers in order to develop a solution to a complicated problem? After an hour or more of deliberations, a sigh of relief comes over the room. We've found our solution! As everyone begins to leave the meeting however, your wheels start spinning and you remember an important fact about your organization that throws a potential monkey wrench in the solution that was determined. While unpleasant to bring up, that piece of legacy knowledge will save the company significant time, energy, and money pursuing a solution that ultimately would not work as conceptualized. This is probably why you were included in the meeting to begin with.
My point is, that while it can be very easy to dismiss the “non-techies” from this group, there is unquantifiable value in subject matter experts’ legacy knowledge. This should also be a major consideration when selecting the members of the Data Owner Team.
You’re Not In The Clear, IT!
Although not the owners of Big Data, the importance of IT’s role should not be overlooked. IT should indeed be included on the Data Owner Team to represent the credit unions’ technology focus, including hardware and software considerations, data security, and data integrity. For small to mid-size credit unions, IT is often responsible for (among other things) building, maintaining, and understanding the credit union’s data structures. This provides the team with unique insight into a very important component of the data governance program. Data warehousing, database administration, and data mining are concepts that are often foreign to other groups, but important to understand when developing data governance policies. IT should be a key source of input on these matters.
If Everyone Owns It, No One Does
In my experience, when Data Owner Teams are developed without assigning a lead position, many assumptions are made as to who is doing what. Once all of the members of the team are identified and established, it’s critical to designate roles and responsibilities to each member, most importantly the Data Owner Team Leader. This individual should be responsible for ensuring that all aspects of the data governance policies are being adhered to. This includes, but is not limited to routine audits of data collection activities, assigning new members to the team as necessary, and conducting regularly scheduled data governance meetings.
Ultimately, leveraging a successful Big Data strategy that helps drive loan growth and improved portfolio performance greatly relies on the implementation of a Data Owner Team that makes data governance a priority.
Courtney Collier is product manager for analytic products at CU Direct.
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