Use Benchmarks to Optimize Retail Investment Services Programs (part 2)

When measuring your investment services program’s performance, it is critical to understand how individual benchmarks represent a piece of the puzzle. If considered separately, the individual metrics do not tell the whole story as to how the program’s management team should improve the program’s overall productivity.

 
 

Two weeks ago we looked at one credit union example of appropriately benchmarking the retail investment services program. This week we build on that example, although it is not necessary to have read the first article.

A credit union's investment services program's overall productivity and performance can be effectively managed as it grows and becomes a vital member service following its initial launch. Yet, to do so, requires that the management team of both the individual program and credit union have a balanced scorecard that guides them in setting their goals and objectives and provides a disciplined approach to monitor results.

Credit Union Example

This credit union, to review, has $500M in shares with seven branches and two FCs. The program is structured as a Dual Employee program, in which representatives are employed by both the broker-dealer and the credit union.

  • The program's total GDC is $620,000 per year.
  • Each FC generates, on average, $310,000 in revenue per year.
  • Assets under management total $120 million.
  • Each FC services, on average, 1,500 accounts.
  • The program's GDC per million of Shares and average branches per FC is about average with their peer group of similarly structured programs.
  • The credit union's wallet share metric (19.4%) is significantly higher than the dual employee program average (11.5%).

 

Credit Union Example

Dual Employee Average

GDC per Million of Shares

$1,240

$1,269

Average GDC per FC

$310k

$308k

Branches per FC

3.5

3.6

Accounts per FC

1,500

848

Wallet Share Metric

19.4%

11.5%

At a glance, our credit union example performs well when comparing their primary benchmarks (GDC per Million of Shares, Average GDC per FC, Average Branches per FC and the Wallet Share Metric) to their peer group.

Metrics Indicate Potential Problem Sources

However, adding additional metrics (average accounts per FC) indicates a potential problem area. The program's FCs serve, on average, 1,500 accounts, roughly twice the number of their peers. The number of accounts should not be confused with the number of households served. Generally each household relationship with the program will have two to three accounts. For the credit union and program management, this high ratio must be considered a red flag. Each FC can only effectively oversee and service a finite number of account relationships. If this metric continues to increase, program growth and existing client service will be severely affected.

The industry standard for service assumes that a performing FC cannot effectively maintain an appropriate level of service or relationship development once the total number of accounts has passed approximately 750 accounts.

Of those 750 accounts, FCs should segment the accounts based on the complexity or size of the accounts, considering, as well, other servicing factors that call for a prioritized approach to ongoing service.

Solutions through Adjusting Staffing Models

Utilizing the Callahan/SCS Scorecard, the management team of the credit union will recognize that a shift to their service and support staffing model will help avoid a decline of member service. Adjusting the model will allow the program’s continued growth and minimize the risk of losing valuable member relationships. If done properly, the Accounts per FC ratio will decline to peer levels.

As is the case with all programs, the solution is not necessarily one of simply adding more FCs. The management team should examine their metrics to determine if the credit union's branch network has the capacity for an additional producing FC, and that adding the FC will reduce the Accounts per FC metric. If there is too little capacity in the branch network, the Accounts per FC metric would decline, however, GDC per FC and other financial metrics would decline as well. If there is too much capacity in the branch network, the FC would be performing at a similar level to the program's current FCs – the financial metrics would increase, but Accounts per FC would remain the same. Most programs in this situation add licensed sales assistants or Associate FCs who manage the servicing of member accounts. This effective approach expands the capabilities of the overall team rather than dividing up the branches that the FCs service. Furthermore, there is normally minimal to no disruption to members or the branch staff with the addition of support staff.

Conclusion

Focusing on one or two metrics can, in the short term, be effective. However, to build a sustainable business model for a credit union's investment services program, management must bundle multiple benchmarks that demonstrate the breadth and depth of a program’s productivity and performance.

 

 

 

July 6, 2009


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