Metrics_ How to Improve Key Business Results - Martin Klubeck [81]
Measuring the Frequency of Use of the internet and telephones still seems meaningless since they are high-use services that we held as a monopoly.
The following are two points that I want to make clear:
Some of the measures can be “not applicable.” Although triangulation dictates that you attempt to have at least three measures from different viewpoints, it is not mandatory.
Just because you can think of measures, doesn't mean that you have to use them.
Just because you can think of measures, doesn't mean that you have to use them.
So, back to the Service Desk. Let's look at the specific measures which were identified for this service.
As explained in Chapter 5, the Delivery measures of Availability, Speed, and Accuracy would be measured objectively through information gathered from the service provider. The great news for us was that the manager of the department was (and still is) an extremely compassionate leader. Where much of the dangers and warnings I've written about come from fear, uncertainty, and doubt—the realization of those trepidations occurs most times because the manager misuses the metrics. In the case of our Service Desk, I didn't worry that the manager would misuse or abuse the information we provided. If I told her the data showed that a worker was negligent, lazy, or incompetent, rather than take premature action, she'd investigate to first find out the “truth” behind the data. Then if the interpretation I offered was accurate, she'd work with the staff member to address the issues—compassionately.
The manager's attitude made the Service Desk an excellent service to start with. We had a high confidence level in her ability to help us sell the program to her staff and become a solid example for other service providers.
Another positive from starting with this service provider was the large amount of data easily attained. The Service Desk was the highest user of the trouble call tracking system. The majority of the data would be through this system. The Availability data (abandoned calls) was available through a totally automated call system, making it an objective set of measures. Customer satisfaction was handled by a third-party survey organization. So, this service provider had all the data we could want and most of it was through objective collection methods. All of it was obtainable without intruding on the departments' day-to-day operations. An ideal service to start with.
Speed would be tracked with a little less objectivity than Availability. Since it was based on the speed of resolution, it would be derived from the time to open and time to close trouble-call cases. This required that the analyst answering the call logged in the call accurately at each phase—opening and closing. Since the manager believed in metrics, she encouraged (and ensured) the workers logged cases accurately.
Accuracy was also measured using the trouble-call tracking system. Rework was defined as cases that were prematurely (incorrectly) closed. We could try to identify errors (defects) throughout the solution process, but since much of finding solutions to customer problems included trial and error, this was not an easy place to start. Even with the manager's compassion, I didn't want to ask the analyst to track how many different guesses they tried before they got it right. This would require a high level of trust (for the worker to not believe it would reflect about herself), a trust I hadn't developed yet. Another problem with this possibility was that the information might not reflect the customer's view point. Most customers expect a fair amount of trial and error, and hunting around for the right solution.
In each case—Abandoned Call Rate, Time to Resolve, and Rework, the data would reflect the customer's view point.
Moving from Delivery to Usage was, in this case a more difficult set of measures. Since the Service Desk was an internal service provider