Metrics_ How to Improve Key Business Results - Martin Klubeck [13]
The three little pigs also ran into this paradox. The first pig’s doctor was happy with data and measures, but ignored the bigger, more important requirement. He lost his patient, but did it with “healthy” numbers. Business can do the same. You can have good data points (sales per customer, profit/sale, or repeat customers) and still go out of business.
We have to start with the complex to uncover the simple—start at the root question and drive unerringly toward data.
Identifying the correct root question is not as simple as it sounds, nor as difficult as we normally make it. We need to be inquisitive. We need to keep digging, until we reach the truth, the question at the root, the need, the requirement. What is the purpose of the metric? What is it that you really want to know? This root need enables us to form a picture of the answer. This picture is the design of the metric.
Once you know the root question, you can draw a picture.
The picture, the design of the metric, can be created without any idea of the actual answers. The metric provides the form for the information. The information tells us what measures we’ll need, and the measures identify the data required. This is the best way to create a metric. From the question to the metric to the information to the measures and, finally, to the data.
Unfortunately, most times we attempt it in the opposite direction, starting with the simple (data) trying to expound on it to develop the complex (root question). This process seldom succeeds. But when we start at the complex, forming a picture of what the question is and how the answer will look, it becomes easy to work down to the data.
Data, measures, information, and metrics all serve the same master: the root question. They all have a common goal: to provide answers to the question. Because of this, the question defines the level of answer necessary.
Let’s pose the following question: How far is it to Grandma’s house? You don’t need a metric to provide the answer to this question. You don’t even need information. A measure (for example, the number of miles) will suffice. And you will be fully satisfied. For data to be sufficient, you have to ask the question with enough context to make a simple number or value an adequate answer. How many miles is it to Grandma’s house? How much longer will it take to get to Grandma’s house? In these cases, data is all you need. But data is rarely useful in and of itself.
Let’s pose another question: Do we have time to do any sightseeing or shopping along the way and still make it in time for Grandma’s turkey dinner? To answer this, we require information. The measures and data might include the following:
The time Grandma is serving dinner
The current time
The number of sightseeing or shopping stops along the way
The estimated time to sightsee/shop per stop
We still don’t need a metric. And we definitely don’t need a recurring metric in which we have to collect, analyze, and report the results of building information on a periodic basis.
The problem is, management—anyone above staff level—has been conditioned to almost always start with data. The few that start with metrics already have the answer in mind (not a bad thing per se), but lack the question. This leads to them asking for recurring (weekly, monthly, quarterly, or annual) reports. They’d like to see the metrics in a certain format: trend lines with comparison to a baseline based on best practices, both monthly and with a running annual total. Sounds great, but without knowing the root question, asking for this answer runs the risk of wasting a lot of resources.
Sometimes clients (managers, department heads, organizational leaders, etc.) who know the answer (metric) they want before they know the question, realize that the answers don’t really fulfill their needs