#63 Got A Performance Measure Dictionary?

Many organisations have hundreds, even thousands, of performance measures. And some of the problems associated with having so many performance measures are:

* lots of measures can be unnecessarily duplicated, and dozens of people are taking dozens of hours each month independently reporting the same things
* measures that should be calculated the same way often aren't, and therefore don't have the power of consistency (aka "apples with apples" comparability)
* measures that aren't brought to life yet have no clear implementation plan or blueprint
* it's difficult to formally flag unneeded or unimportant measures for deletion or modification

One very important strategy to manage your suite of measures is to have a performance measure dictionary, a structured, single system where details about every measure you monitor is kept up to date.

The data *about* your measures

A well structured Performance Measure Dictionary contains fields where you can detail exactly how each measure is to be named, the correct way to calculate it, the appropriate data to use (and where to find it), how to report it, what signals to interpret and who is responsible for it.

This is the data about your measures, often referred to as metadata, and what types of metadata you choose to define your performance measures is important. It can't be vague or incomplete - it has to be sufficient for people to know and understand how to report each measure, so the measure actually tells you what you think it's telling you, and that it is consistent over time.

How to set up your Performance Measure Dictionary

First step in capturing and organising your performance measures is to decide what metadata you're going to use. At the very least, you'll need the measure's name, a brief description, a statement or formula for how it is calculated, where the source data comes from, and who is responsible for the measure.

Second step in setting up your Performance Measure Dictionary is to create a single system to capture these details about all your measures. You could start out using a simple Excel Spreadsheet or Word document, but it will quickly become cumbersome, particularly because it's difficult to sort and report summary measure information like their current 'bring to life' status or all the measures owned by Bob. A Microsoft Access database is a better starting point. And as you get more advanced, some dashboard and scorecard software - like SAS's SPM - enable you to record your measure definitions.

Third step is to stocktake your measures. This is time consuming, but get it done now and you'll save much time down the track that would otherwise be wasted trying to determine exactly how a measure was calculated, or whether the wrong data was used, or why two different reports show the same measure with different trends. You can get someone to go around and collect all the performance reports and details, then enter all the measures into your Performance Measure Dictionary. Or you can send copies of a measure definition form throughout your organisation or business for people to fill in and send back to a data entry person.

Fourth step is to develop some standards or policy around how the Performance Measure Dictionary should be used, and how all new measures in the organisation should be treated. Unless the measure has been documented in the Dictionary, it will be ignored by decision makers. Like all new behaviours, it's not going to be habit straight away, so give it time and encouragement to become the normal way of managing performance measures.