Quantitative Versus Qualitative KPIsMay 21, 2013 by Stacey Barr
How to get clear about how qualitative KPIs differ from quantitative KPIs, and how to make the qualitative KPIs measurable.
One of the ways that people like to classify their KPIs and performance measures is by whether they are quantitative or qualitative. Should we do it? And if we do, are we doing it right?
The distinction between quantitative and qualitative measures is often misunderstood. Really if you’re measuring anything, you’re gauging the amount to which it’s happening. And numbers are the essential building blocks of amounts. Even when you use rating scales to turn attitudes into numbers, you’re doing it to gauge an amount. So, technically, every measure is quantitative.
Qualitative measures aren’t actually measures.
In the field of statistics, we distinguish variables as qualitative (or attribute) when those variables are not gauging an amount but rather are simply putting things into buckets. The buckets are classifications like gender or market segment or geographical region or product group.
Qualitative variables aren’t performance measures. But they are used to help us analyse our measures. We can slice Customer Satisfaction Rating into product groups to explore which products to prioritise for improvement. We can dice Employee Engagement Ratio by profession and location to explore where morale might need boosting.
Quantitative measures can take two forms.
In the field of statistics, we distinguish two types of quantitative variables: continuous and discrete. Continuous variables can take any value (including decimals) over a range, and are measured in units like kilograms, hours and minutes and seconds, dollars and cents, metres.
Discrete variables are generally counts of things like complaints, accidents, new customers – anything that takes an integer value. This includes rating scales for measuring attitudes, such as satisfaction or agreement on a 10-point scale.
Performance measures can be based on either continuous or discrete variables. Measures such as Average Delivery Cycle Time or Net Profit and Non-recyclable Mass Sent to Landfill and Average Kilometres Travelled are based on continous variables. Measures such as Average Customer Satisfaction Rating and Number of Lost Time Injuries and Percentage of Projects Completed On-Time are based on discrete variables.
Both types of performance measures – continuous and discrete – are equally useful.
JOIN THE DISCUSSION:
Do you agree that discrete measures are as useful as continuous measures? What’s your reasoning? Share your suggestions on the blog.
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