• Choose a category
• All
• Classic-Fiction

A metric development plan is not a luxury. It’s a necessity.

The plan not only helps in the creation of the metric, but it also provides guidance for the maintenance and final disposition.

The metric development plan is made up of the following components: A purpose statement

An explanation of how it will be used

An explanation of how it won’t be used

A list of the customers of the metrics

Schedules

Analysis

Visuals or “a picture for the rest of us”

A narrative

Accuracy is critical. I stressed the importance of accuracy in your data (source dependent), your collection (process dependent) and your analysis (process and tool dependent). I also offered the benefits of making your processes repeatable.

Conclusion

We have set some of the foundation for designing and using metrics responsibly. We provided some tools for the practical implementation of a metrics program. The next three chapters will cover the dangers inherent in a metrics program and I will provide warnings, mitigations, and threats to help you avoid the headaches many fall victim to. I believe this is a logical progression—because before you use a powerful and, therefore, potentially dangerous tool, it is important that you understand what it is, how it should be used, and how to avoid injury.

In almost every serious effort, you are told to document your work. It is stressed in everything from software engineering to grant writing. The problem is, it’s tedious. I don’t know of anyone who is passionate about documenting their work. If you fail to document everything else, I’ll forgive you—as long as you document your metric.

Using Metrics as Indicators

To keep things simple, thus far I’ve focused only on the following basic concepts:

Metrics are made up of basic components: data, measures, information, and other metrics.

Metrics should be built from a root question.

It’s more important to share how you won’t use a metric than how you will.

This chapter introduces another basic concept about creating and using metrics—metrics are nothing more than indicators. That may seem to be a way of saying they aren’t powerful, but we know that’s not the case. Metrics can be extremely powerful. Rather, the concept of metrics as indicators warns us not to elevate metrics to the status of truth.

Metrics’ considerable power is proven by how much damage they can do. Metrics’ worth is rooted in their inherent ability to ignite conversations. Metrics should lead to discussions between customers and service providers, between management and staff. Conversations should blossom around improvement opportunities and anomalies in the data. The basis for these conversations should be the investigation, analysis, and resolution of indicators provided through metrics.

Metrics should be a catalyst to investigation, discussion, and only then, action. The only proper response to metrics is to investigate. Not the type of general investigation discussed in Chapter 15 on research, but instead a directed and focused investigation into the truth behind the indicator.

Facts Aren’t Always True

If you search the internet for things we know to be true (supported, of course, by data), you’ll eventually find more than one site that offers evidence “debunking” past and present-day myths. What was thought to be a fact is proven to be an incorrect application of theory or the misinterpretation of data.

Our earlier examples of health information are a ripe area, full of things people once believed to be true but now believe the opposite. Think about foods that were considered good for you ten years ago but today are not. Or foods that were considered not to be good for you, which now are considered healthy fare. Are eggs good for you or not? The answer not only depends on who you ask, but when.

The US Government’s “food pyramid” changes periodically.

Who doesn’t remember the scenes of Rocky downing raw eggs?

It seems like each year we get a new “diet” to follow—high