Consider an insurance company where the employees have some latitude to waive the excess on a policy if the person making the claim has mitigating circumstances. Each person may make decisions on a variety of different policies (home. contents. car, boat, accident, personal liability etc.)
Now suppose you wanted to judge whether any of your employees were being overly generous in waiving excesses.
One measure you might use is to simply look at the proportion of claims that a person processed during some time period for which they waived the excess. You might compare this to the total proportion waived over all claims processed by all employees and target those employees who deviated too much from this average. However this is a very crude measure since it fails to take into account the types of claims each individual is processing.
A more refined measure might be to take the average proportion waived by all employees for each individual claim type and then calculate what each individuals waive rate would have been had they waived at these rates for the claims they actually processed. This is a fairer measure since it takes into account that the waive rate might differ between different kinds of claims. And again, you might target those employees for whom the deviation between actual and expected waive rates was too great. However, if any of your employees is just processing a single type of claim then they may be making the largest contribution to the waive rate for that claim type so you would effectively be comparing that person against themselves with little chance of a major deviation.
Both of these methods compare what an individual is doing against what everyone else is doing so it is a comparison against a norm of behavior rather than against any objective measure of what should be happening. For all you know, most employees might be being less generous than you might like, so the person who appears to be being more generous might actually be doing what you want. However, the attraction of these methods is that they are simple to implement.
The more important question however is what is the intended outcome of this policy and whether what your employees are doing is achieving this outcome. Every time an employee waives the excess it is a cost to your company, so presumably you want an outcome that will compensate for this cost. Otherwise, you would just be throwing money out the window. You would need to establish some metrics against which to measure the success of your policy (e.g. customer loyalty as measured by policy cancellations, taking out additional policies etc).
In the case of increased customer loyalty, you might gain an increase in policies due to word of mouth or conversely be able to reduce your advertising costs. Whatever measure you use, you should be able to measure the costs of the policy to your company versus the benefits gained and this in turn might give you a clearer indication as to how generous your employees should be. This would take a lot more gathering and analysis of data but would allow a more targeted approach. You might find that waiving the excess for one type of claim might result in no benefit at all. Or that placing conditions (e.g. 10 years without a claim) around a policy type in order to realise any benefits.
The major differences between this approach and the approach based on averages are:
- In this approach the policy has a clear purpose and you are more interested in whether the total effect of employees actions is achieving that purpose. In the 'average based' approach, you are interested only in how employees compare with each other (whether or not this benefits the business)
- This approach provides information that enables you to evaluate and refine the policy itself. The 'average based' approach allows you to change the behavior of individuals but such change might actually adversely affect the business.
