• Choose a category
• All
• Classic-Fiction

Let's continue on in this manner in Table 10-11.

We again have decisions to make. Are Delivery, Usage, and Customer Satisfaction of equal value? This is only necessary because we are attempting to roll up the grades to a single grade. In my organization, we stopped at this level, choosing to keep these three key information categories separate, even across different services. So if we were to roll up three support services (Service Desk, second- and third-level support) we'd show a roll up in the Delivery overall, Usage overall, and finally Customer Satisfaction overall. We found the view of a service using this basic triangulation as far as we needed to go. If you want to roll it into a final grade (GPA), the only question left is the weighting. For the purposes of this example, we'll keep it simple and make their values of equal weight.

So the final Report Card for the Service Desk, based on the weights for each category of information, resulted In an overall grade of M*. This can be interpreted easily to mean that the service is meeting expectations overall with some anomalies that should be investigated.

If you looked at the grades as my organization does, not rolling up the major categories, into a single grade, but looking at each major “subject” area separately, you would get the following:

Delivery: O is an Opportunity for Improvement. Time here should be spent investigating the causes for the anomalies.

Usage: M means that we Meet Expectations. No investigation required in this area.

Customer Satisfaction: E means that we Exceed Expectations. Time here should be spent investigating the causes for the anomalies.

The final summary Report Card would look like Figure 10-16.

Figure 10-16. Report Card

With each, prose should be included once the investigation has concluded. This prose communicates to the leadership what the service provider has determined to be the cause for the anomaly and any suggested actions to mitigate, avoid, rectify, or replicate the causes. These changes are to processes (not people) and should be designed to control future results.

If we learn from our past mistakes, we should not continue to repeat them.

Likewise, if we learn from our past successes we should find ways to make the anomaly into the common place (if it is deemed an equitable choice).

Recap

The Report Card allows us to aggregate grades at each level of our metric. You can decide at what level to stop compiling to a final grade. You do not have to end with a single grade. This chapter has been a step-by-step example of how the concepts presented to this point can be (and have been) applied to create a service-level metric.

I have reviewed in this way working from data to measures to information and finally a metric. From measures onward, I showed how you will apply expectations to each so as to give context and meaning to each. Along with applying expectations, I showed a suggested method of normalizing the information across measurement types and areas. The use of percentages is only one means of consistency. As you use different measures, evaluating various services and products, you will find that this may not remain easy to do. In my experience, the measures used will differ in type.

Another tool of normalization is the scoring method, in which at every turn we seek to err on the side of excellence. This is why an Opportunity for Improvement is treated as a zero and only an Exceeds will balance it out to Meets. Since we don't round up (again to ensure we err on the side of excellence), just one Opportunity for Improvement will keep the total (average) grade from ever being an M unless there is an E included.

What we want are Meets Expectations. Anything else is an anomaly and requires investigation.

Recall some of the following ways that impressions can be skewed:

Artistic license—color choices, alignment, etc.

The scale used to represent the measures

The format used to represent the data (ratio, average, percentage,