Many managers struggle to measure the impact of the employee's contribution toward the firm's ability to produce effectively and/or efficiently a market offering. Marshall Fisher writes about this struggle from a retailer's perspective. The money quote:

I think the root cause is business-school thinking gone wrong. We teach our students to be rigorous and manage by the numbers. Not a bad idea, except that it leads to over-weighting the measurable and under-weighting what's hard to measure. In a store, what's measurable is the payroll checks a retailer writes every week to its stores' staffs. What's hard to measure is the impact that stores' staffs have on revenue.

He makes a good point. A manager can easily measure the efficiency of a cashier by counting how many people the cashier moves through the line in a time block. That number represents an efficiency measure. To measure the effectiveness, we need to measure something else; namely, how long people stood in line.

Consumers avoid retailers who have long lines. This avoidance, though, remains relative. Roughly, the larger the perceived discount, the longer the consumer is willing to wait. Standing in a slower moving line at Whole Foods, a consumer will become unsatisfied very quickly. Standing in a similar slower moving line at Aldi, the same consumer will remain satisfied.

Given the relative nature of wait time and its relationship to satisfaction, the value-generating manager will use a Poisson distribution to determine when a line is too slow, too fast, or just right. Remember, the Poisson distribution provides the probability we will observe a number given that we observed some range of data. That is, the Poisson distribution can be used with any from of count data.

By using the Poisson distribution tool, the manager can better assess the employee's contribution toward the firm's ability to produce effectively a market offering.