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From Dr. Scott Sampson's Understanding Services Businesses Book (click for table of contents)
SBP 14b: A Measure of Motivation⇐Prior —[in Unit 14: Measuring Service Quality and Productivity]—

SBP 14c: Comparing Apples and Oranges

With multi-location service companies, varying clientele may make production difficult to compare across locations.

Why it occurs

This principle occurs because of heterogeneous inputs from customers, and heterogeneous outputs to compare.


Multi-location service companies may desire to compare service quality and productivity across the various locations. Reasons might include:

  • To identify outstanding locations to set as examples for the rest of the company.
  • To motivate location managers to improve results by having the various locations compete for rewards or recognition.
  • To identify locations with problems in need of management attention.

These are potential advantages for having objective ways to comparing across service locations. However, with service companies measurement comparison across locations needs to be done with caution. The comparison of numerical measurements may not accurately reflect the comparison of how the various locations are operating.

For example, which is a more productive law office, the one who has two attorneys who win three cases and lose two in a given month, or the one who has four attorneys who win five cases and lose six in a given month? You may say the first, since it has more wins per attorney. However, the second has handled more cases. But, the first has a greater success rate. Yet, the second probably has more billable hours per attorney. Further, we have no idea of the complexity of each case, or the quality of the inputs (the client's position). Some cases are easy, and others are not. The bottom line is that comparisons of service quality and productivity can be very difficult.

How it effects decisions

Service providers should decide how to define quality and productivity, especially if employees or offices are given bonuses or other rewards based on superior quality and productivity.

What to do about it

There is no general rule for establishing comparative measures of quality and productivity. However, measures should normally adjust for environmental factors beyond the control of the service employees. One technique for doing this is known as Data Envelopment Analysis (DEA). DEA considers the various inputs into a service process and the resulting outputs. It uses a mathematical procedure to evaluate outputs adjusted according to inputs, and can tell which service locations tend to get more (or better) outputs for fewer inputs.

For example

A 114-location automotive service chain desired to improve customer service by rewarding store managers and other employees based on customer satisfaction ratings. The company developed a complex system for gathering customer satisfaction data, including in-store surveys, telephone surveys, complaint and compliment letters, and “mystery shopper” inspections by employees posing as customers. The challenge they found was that some stores received higher ratings than others for reasons other than how well the employees were providing customer service. For example, some stores sold mostly tires, which is a low-risk and easily satisfiable interaction with customers. Other stores sold mostly mechanical service, which is a highly divergent process subject to greater variability in satisfaction. Also, some stores were located in highly competitive areas, whereas others were in more rural regions. The result was that it was difficult to compare the customer satisfaction ratings to identify stores providing truly superior quality.

My airline example

Airlines have locations in numerous cities, called stations. How easy would it be to compare quality and productivity across the locations? The environment of each location certainly varies, including the availability of passengers and competition. Also, the design of airports might limit the ability to provide service quality. (What is an airline to do about cramped gate waiting areas?) Major hubs are likely to have higher overall traffic. Commuter routes are likely to have higher customer loyalty. Regional (i.e. smaller) airports are likely to have sporadic demand, more difficult planning of capacity, therefore lower utilization.

How manufacturing differs

With manufacturing, quality and productivity are generally measured in objective terms, allowing easier comparisons.

Analysis questions

  1. Is this a multi-location service company?
  2. Is production standardized across locations?
  3. Do customer inputs vary across locations?
  4. Do the management challenges vary across locations?
  5. On what basis can the various locations be compared?

Application exercise

Design a bonus system for rewarding employees based on service quality and/or productivity. What measurements would you use? How would you account for environmental factors, including variations in customer inputs and requirements? Comment on the advantages and disadvantages of your system.

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