Interpreting Quantitative & Qualitative Business Data

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  • 0:00 Business Data
  • 0:55 Quantitative Analysis
  • 2:12 Qualitative Analysis
  • 3:45 Lesson Summary
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

Information is key to help business leaders make decisions. But there are different types of information that businesses can use. In this lesson, we'll examine the different types of data, quantitative and qualitative, and how to approach each.

Business Data

Sam runs the customer service call center for a big bank. Customers from across the country call and Sam and his team help answer their questions and resolve their problems. But Sam wants to know how he can better serve his customers. Should he hire more customer service reps? If so, how many?

Information helps businesses make good decisions. If Sam has enough data, he can know exactly how many, if any, additional representatives he should hire. There's a lot of data out there. In Sam's case, for example, he could track how many calls per day the call center receives, or the average waiting time for customers when they call, or what customers say about their wait times and interactions with the customer service reps. To help Sam sort through the data available to him, let's look at how to approach the two major types of data: quantitative and qualitative data.

Quantitative Analysis

Sam wants to know whether to hire more customer service representatives for his call center. He has some data to help him, but he's not sure exactly what to do with the data. Quantitative data is information made up of numbers. Think of the word 'quantity' and you can remember quantitative. For example, Sam has information on how long different customers had to wait before talking to a customer service representative. The data includes the number of minutes each person had to wait, so it is quantitative. He can use that data to help him decide whether to hire more reps and how many new reps to hire.

Quantitative data is best analyzed using statistical techniques. Whether using simple statistical techniques, like finding the mean of a data set, or complex statistics, like advanced multivariate analysis, Sam can use statistics to make sense of the quantitative data he has. Take the data set about the wait time: Sam can take the numbers he has and find the mean, so he knows how long, on average, customers wait to speak to a rep. With a little more data, like how many representatives were working when the wait time data was collected, he could even calculate an estimate of how that wait time would be shortened if he hires one new rep, or two new reps, and so on.

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