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These questions are being asked at the right time—compared with if we started with the data. If we started with a vague idea (instead of a root question) and jumped to the data—we’d be asking these questions after collecting reams of data, perhaps analyzing them and creating charts and graphs. Only when we showed the fruits of our labor to the client would we find out if we were on the right track.

I want to help you avoid wasting your time and resources. I want to convince you to build your metrics from a position of knowledge.

Collecting Measures and Data

Now that we’ve identified the information needed (and measures that make up that information) we need to collect the data. This is a lot easier with the question, metric picture (answer), and information already designed. The trick here is not to leave out details.

It’s easy to skip over things or leave parts out because we assume it’s obvious. Building on the workload example, let’s look at some of the data we’d identify.

First we’ll need task breakdowns so we know what the “work” entails. What comprises the tasks—so we can measure what tasks each worker “can” do. With this breakdown, we also need classifications for the types of tasks/work. When trying to explain concepts, I find it helpful to use concrete examples. The more abstract the concept, the more concrete the example should be.

Task 1: Provide second-level support

Task 1a: Analyze issue for cause

Task 1b: Determine solution set

Task 1c: Select best solution

This example would be categorized as “support.” Other categories of a task may include innovation, process improvement, project development, or maintenance.

We’ll also need a measure of how long it takes each worker to perform each task, as seen in Table 2-1.

If we have measures for the work components, we should be able to roll this data “up” to determine how long it takes to do larger units of work.

Next, we’ll need measures of what is assigned currently to each worker.

Worker A is working on support while workers B and C are working on maintenance.

Since we need to know what each worker is capable of (“can do”) we will need to know the skill set of each worker. With specific identification of what they “can’t” do. Many times we find the measure of X can be determined in part (or fully) by the measure of the inverse value ¹/x.

Worker A is not capable of doing maintenance work. That’s why he isn’t assigned to maintenance and does the support-level work instead.

Again, it’s a lot easier once we work from the top down. Depending on the answers we would perform investigations to ensure the assumptions we come to are correct. Then we can make changes (improvements) based on these results.

Worker A wants to do more maintenance-type tasks, but doesn’t feel confident in her abilities to do so. The manager chose to develop a comprehensive training program for Worker A.

Workers B and C showed they had the skills necessary to provide support, and were willing to do so. The manager divided the support work more evenly between the team.

These types of adjustments (and new solutions) could be made throughout, depending on the answers derived from the metrics.

It was not necessary to be “perfect” in the identification of all measures and data. If you are missing something, that should become evident when trying to build the information and, finally, the metric. If you’re missing something, it will stand out. If you have data or measures that you don’t need, this, too, will become quickly evident when you put it all together for the metric.

You’re not trying to be perfect out of the gate, but you definitely want to be as effective as possible. You’d like to be proactive and work from a strong plan. This happens when you use the root question and metric as your starting point.

It is truly amazing to see how a picture—not charts and graphs, but a creative drawing depicting the answer—works. It helps focus your efforts and keeps you from