By: Stacey Barr
Where do you start improving your organisation's performance measures? What kinds of things could you improve about how your organisation measures its performance? In what ways are you already good at performance measurement?
These questions may not be exactly keeping you awake at night, but certainly by answering them, you could both save a lot of time and effort in the process of getting better measures to manage your organisation's performance. That's because with the answers to these questions you can decide where to focus your efforts to make performance measurement work better.
So to give you a start in answering these questions, here is a rough-and-ready checklist of the key criteria to assess where your current performance measurement system is working well, well enough, or needs more work. Tick it if you do it well. Tally up your ticks for each section and start exploring how you might improve those sections where your tick count is lowest.
1) Selecting performance measures that are meaningful.
[ ] The organisation's strategy is the guideline for what should be measured.
[ ] Each performance measure provides objective evidence of the degree to which a specific result is occurring over time.
[ ] Ownership of the measures happens.
[ ] No one is responsible for more than 7 (or so) performance measures.
[ ] All performance measures are defined using a consistent definition framework that specifies exactly how each measure will be constructed, reported and used.
[ ] Performance measures are driving the right behaviour (which has been defined).
[ ] The linkages or relationships between all performance measures are understood.
2) Collecting performance measure data that is reliable and relevant.
[ ] Only relevant and useful data is collected.
[ ] There is a policy that makes explicit the degree of integrity required of data for each measure.
[ ] The data collection tools that used throughout the business are designed to collect data with the degree of trustworthiness required.
[ ] Each data item collected is defined consistently as part of a 'data dictionary' for the organisation.
[ ] Data collection processes dovetail into work processes seamlessly with minimum, if any, disruption to operational effectiveness or efficiency.
3) Storing and managing performance measure data for easy and quick access.
[ ] Data capture is simple, effective and maintains data integrity.
[ ] Data can be easily accessed by those who need it, when it is needed.
[ ] Historical data is readily available when required (historical data means data that is more than a couple of years old).
4) Analysing performance measure data to reveal the data's story.
[ ] All data analyses performed, whether internal or external to our organisation, are focused on answering pre-defined driving questions.
[ ] Statistical techniques are used validly and appropriately.
[ ] Variation in the performance of business processes is measured (not % differences, true statistical variation).
5) Presenting performance measures to make interpretation easy and valid.
[ ] All performance reports produced have a clearly defined and understood purpose and a clear target audience (or audiences).
[ ] The physical layout of reports is simple to follow and makes finding information easy and quick.
[ ] Graphs are the preferred method of presenting performance measures (and the correct graph type is used to answer the driving question).
6) Interpreting performance measures to draw the right conclusions.
[ ] The owners of performance measures are the people that interpret those performance measures and communicate their conclusions to others.
[ ] Statistical methods (such as statistical process control charts) are used to flag signals in the data (e.g. levels of stability and change in process performance).
[ ] There are consistent and well defined guidelines for interpretation of performance measures (such as a definition of the evidence of a true trend or change in performance levels).
[ ] People involved in using data and information have the appropriate level of skill in interpreting it effectively, efficiently and validly.
7) Applying performance measures to improve performance.
[ ] The results of performance improvement decisions are tracked using the same measures of performance that these decisions aimed to improve.
[ ] The results of interpretation of performance measures are an input into our planning review process, taking a visible role in the formulation and evaluation of our business goals & targets.
[ ] The root causes of performance results are identified through further analysis of lead indicators and/or other data.
[ ] Performance improvements are decided upon through application of systemic thinking and are prioritised before they are taken on and implemented.
[ ] Intuition, emotion and gut feel are used to guide further collection and analysis of objective data (both quantitative and qualitative) rather than to drive decision making alone.