However, any flaws in the benchmarking process can lead to inaccurate perceptions of your credit union’s performance. That’s why you’ll want to avoid these five common pitfalls that can lead to errors in your analysis.
- Imprecise Peer Groups
Peer groups based solely on asset size or geographic proximity don’t account for the wide range of other factors that can impact performance. Adding measures like field of membership, charter type, and operational metrics as criteria creates more accurate peer groups by narrowing your peers to only those that are most similar to your credit union. - Benchmarking Infrequently
The credit union industry is dynamic. Therefore, annual benchmarking can mask performance lags and prevent your institution from making timely operational changes. Whether it’s pricing strategies, interest rates, or housing market prices, the definition of credit union success is continuously changing, making it imperative to benchmark at least quarterly. - Limiting Potential Peers
If banks are competing in the same market, they should be part of your benchmarking analysis. While differences in the NCUA and FDIC reporting formats are an obstacle, tools like Callahan’s Peer-to-Peer make it possible. Instead of market-to-market comparisons, which may not be useful due to operational and business model differences, consider using bank peers when looking at market share, setting market-based growth goals, and identifying market trends. - Not Excluding Your Institution from Peer Groups
Including your own institution in peer groups can skew your benchmarks, preventing you from getting a true representation of your peers and the competitive landscape. The metrics you are measuring may change directionally without your institution in the mix, depending on economic factors and individual credit union performance. - Assuming Average is Excellent
Using peer averages may give insight as to how the group is performing directionally but should not be used as a measurement of excellence. The average will hide outliers both under and outperforming the peer group. Peer group averages can be used to set a baseline, but generally should not be used as a goal unless using an aspirational peer group consisting of high-performing credit unions.
Callahan can help you avoid these pitfalls.
More than 600 credit unions across the county and asset-sizes rely on Callahan’s data and analytics programs Peer-to-Peer, CUAnalyzer, MortgageAnalyzer, and BranchAnalyzer to accurately measure and track their credit union’s performance versus other credit union peers and banking competitors.
Callahan clients can access their benchmarking tools on their client portal.
Not a client? Learn how to optimize your benchmarking to make better informed strategic decisions.
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