KPI BASICS #11: Quantitative vs Qualitative KPIs

Summary

This video script discusses the distinction between quantitative and qualitative performance measures, often misunderstood in the field of data analytics. It clarifies that all performance measures, even qualitative ones, are ultimately quantifiable through numbers. Qualitative data, while not directly measurable, serves to provide context and deeper insights into performance. The script also highlights the two types of quantitative variables—continuous and discrete—and their application in key performance indicators (KPIs). The message encourages a better understanding of how qualitative data can be quantified and used in performance measurement.

Takeaways

• 😀 KPIs can be classified as either quantitative or qualitative, but the distinction is often misunderstood.
• 😀 All performance measures, even those seemingly qualitative, involve numbers to gauge amounts.
• 😀 Qualitative measures are more about classifications (e.g., gender, region) rather than quantifying amounts.
• 😀 Qualitative variables are not considered performance measures in statistics or data analytics.
• 😀 Qualitative data (e.g., customer feedback) helps to analyze and provide context for quantitative performance measures.
• 😀 Quantitative performance measures fall into two categories: continuous and discrete variables.
• 😀 Continuous variables can take any value, including decimals, and are measured in units like time, weight, or money.
• 😀 Discrete variables are counts of things (e.g., number of complaints, new customers) and are typically whole numbers.
• 😀 Examples of continuous KPIs include average delivery time, net profit, or kilometers traveled.
• 😀 Examples of discrete KPIs include customer satisfaction ratings, number of injuries, or percentage of projects completed on time.

Q & A

What is the main difference between quantitative and qualitative measures?

The main difference is that quantitative measures deal with numbers and amounts, while qualitative measures categorize or describe attributes, often without using numerical data. However, qualitative data can still be quantified in some cases using scales or classifications.

Can qualitative data ever be considered a performance measure?

No, qualitative data itself is not typically considered a performance measure. It’s used to help analyze performance measures by providing deeper context, identifying themes, or suggesting improvements, but it does not directly measure performance.

What are some examples of qualitative data?

Qualitative data includes categories like gender, market segment, geographical region, or product group. It can also involve richer narratives such as customer satisfaction stories, explanations, or feedback that help explain performance trends.

What are the two types of quantitative variables mentioned in the script?

The two types of quantitative variables are continuous and discrete. Continuous variables can take any value, including decimals, over a range (e.g., time, weight, cost), while discrete variables are counts of things that take whole number values (e.g., number of complaints, accidents, or customers).

How do continuous and discrete variables relate to KPIs?

KPIs can be based on either continuous or discrete variables. For example, continuous variables might include metrics like average delivery time or net profit, while discrete variables might include customer satisfaction ratings or number of lost time injuries.

What are some examples of KPIs based on continuous variables?

Examples include average delivery cycle time, net profit, non-recyclable mass sent to landfill, and kilometers traveled. These are all continuous variables because they can take any value, often including decimal points.

Can you give examples of KPIs based on discrete variables?

KPIs based on discrete variables include customer satisfaction ratings on a 10-point scale, number of lost time injuries, and percentage of projects completed on time. These are discrete because they involve counting or categorizing values.

Why is it important to distinguish between qualitative and quantitative KPIs?

It’s important because this distinction affects how data is analyzed and interpreted. Understanding whether a KPI is qualitative or quantitative helps ensure that the correct methods and tools are used to assess and improve performance.

What is the significance of turning qualitative measures into numbers?

Turning qualitative measures into numbers, such as using a rating scale for customer satisfaction, allows us to quantify subjective assessments, making them easier to analyze and compare. This process provides a way to track performance and identify areas for improvement.

How can qualitative data contribute to performance improvement?

Qualitative data provides context and deeper insights, such as identifying the causes behind low customer satisfaction or pinpointing specific product issues. It helps organizations understand why certain performance measures may not be meeting expectations and what actions could be taken to improve.