This checklist of 5 basic KPI formulas, with examples for each one, will help you decide the best way to calculate your KPIs.
A good performance measure is defined as “a quantification that provides objective evidence of the degree to which a performance result is occurring over time”. It means that we need to be sure that the way we’re calculating the values of our performance measures – our KPI formula – really is providing the right evidence and to the right degree.
While there are certainly more than that five ways to quantify our performance measures, the following tips give us an excellent starting point. Each method has its pros and cons, and so it’s worth taking just a few minutes to consider alternative quantification methods for a KPI, before we default to our favourite (which is usually a count or percentage).
It might also help to think about what quantification means. Any measure or KPI is really based on quantifying the amount of some evidence we see, that is related to a result or goal we’re trying to achieve. Goals are achieved in the real world, and that’s where we find the evidence upon which our KPIs or measures are based. We first get clear about the evidence of our goal, and then we use the following KPI quantification formulas to turn that evidence into a measure.
Basic KPI formula #1: Counts
Counting is by far the easiest way to put a quantity to something we’re observing:
- Number of customer who are satisfied
- Number of workplace accidents
- Number of sales
Counts work very well when the arena or scope or population within which we are observing a performance result stays pretty much the same size over time.
But when our population changes over time, counts are misleading. A percentage will tell us with more accuracy the degree to which our performance result is happening.
Basic KPI formula #2: Percentages
Percentages are counts of the number of things or people in a population that exhibit a particular feature, divided by the total population size and multiplied by 100:
- Percentage of customers who are satisfied
- Percentage of employees that were injured at work
- Percentage of sales calls that resulted in a sale
Percentages are great when we are interested in how much of a target population matches our performance result.
But percentages assume our result is black or white. Either customers are satisfied, or they aren’t. Employees either had an accident at work or they didn’t. They don’t tell you the degree or extent, though, like how much satisfaction, or how severely injured.
Basic KPI formula #3: Sums or totals
Where counts are usually considered discrete measures because their values can be only integers, sums or totals are generally considered to be continous measures, because their values can just about anything, including decimals:
- Total time spent making sales calls
- Total sales revenue invoiced
Similar to counts, sums and totals can be misleading if the size of the scope or opportunity varies over time. If the total time spent making sales calls in both May and June is 45.25 hours, but the total number of sales calls in May is twice that of June, we’d probably assess performance differently.
Basic KPI formula #4: Averages
An average is usually a sum or total divided by a count of things or people upon which the sum was based:
- Average customer satisfaction rating
- Average days lost due to injuries per employee
- Average sales revenue per sales call
When we’re interested in understanding the overall level of the degree or extent to which a particular result is happening, and not just whether or not it’s happening, then averages are great.
The three main limitations of using averages however, are small populations, outliers and asymmetrical distributions. Small populations make our average very volatile over time, and make it appear more accurate than it really is. Averages based on 2 or 3 values are next to useless.
Outliers can greatly skew the results, like one or two employees having hundreds of days off work due to very serious but very rare injuries. Usually it’s well accepted to leave outliers out of the average calculation, and just make a note of them in a footnote.
Asymmetrical distributions can also skew our average, like when most sales are between $100 and $1000, but there are still quite a few that go as high as $10,000. In this case, a median might be a better indicator of the ‘centre’ of the distribution than an average is.
Basic KPI formula #5: Ratios
A ratio divides one sum (numerator) or total by another sum or total (denominator). It’s different to an average, because the denominator isn’t a count of the population; it’s usually another measure of the same population:
- Total sales revenue received divided by total sales revenue invoiced
- Total sales revenue divided by total hours spent on sales calls that generated that revenue
Ratios are a great way to measure productivity. The numerator is our output and the denominator is our input.
We should keep in mind, though, that it’s very easy to make our KPIs or measures unnecessarily complex when we use ratios. When we take ratios, we need to make sure that they tell us something sensible.
What about existing KPIs?
Many of our existing KPIs and measures may not have had the same level of thought put into their choice of quantification formula. But rather than review all of them, we can focus first on those that are simple counts. Then ask ourselves: “Is that the most appropriate way to quantify the performance result we’re trying to evidence?”
Our performance measures will only give us part of the story, or a skewed version of the story, if we’ve used an inappropriate quantification formula.