I was planning to write yet another article on key performance indicators for Dashboard Insight
because I felt Dashboard Insight needed an up-to-date reference for those who
did not practice in performance management. I initially started writing the
article, thinking I didn't need any reference material. I've lived through
understanding, discovering, and refining measures for the last six years and I
felt I could write it solely on experience.
Surprisingly, I had a hard time defining what a key performance indicator is
without having to introduce more terms and, thus, more explanations.
Further reflecting on my experiences in business intelligence, I wasn’t sure if
a simple explanation was possible. One person's performance indicator may be
another's key performance indicator. For example, the number of leads by day
would be a performance indicator for the CEO; however, for the marketing
department, it may be a key performance indicator. The confusion doesn't stop
there. Technically speaking, it could be a key result indicator for marketing -
the number of leads is the result of all the activities marketing performs.
After much confusion trying to explain the difference between performance and
key performance indicators (AND result indicators), I decided to step back and
look at it from a different perspective.
Rather than fight through terminology, these are the questions decision makers
need to ask themselves when choosing measures to look at:
- Is the measure clearly linked to an activity that I am responsible for?
- Does the measure support another measure to help in my decision-making process?
If the answer is no to both questions, than the measure is simply nice-to-have.
There's nothing wrong with having these types of measures as part of your report
If you're not a performance management practitioner, you don't need to
understand concepts like lead and lag indicators or result and performance
indicators. Let the performance management consultants deal in those terms. Just
remember to ask yourself these questions when you're given measures to look at
and you'll know whether or not you need them to help support your decisions.
Many will question the simplicity of my explanation, but I believe that this is
a good starting point for anyone who plans on working with performance