Quantitative Analysis Method

Description of Method

Quantitative analysis uses a formal mathematical method to fit cost functions to past data observations. Columns B and C of Exhibit 10-3 show the breakdown of Elegant Rugs’ total machine-hours (862) and total indirect manufacturing labor costs ($12,501) into weekly data for the most recent 12-week period. Note that the data are paired; for each week, there are data for the number of machine-hours and corresponding indirect manufacturing labor costs. For example, week 12 shows 48 machine-hours and indirect manufacturing labor costs of $963. The next section uses the data in Exhibit 10-3 to illustrate how to estimate a cost function using quantitative analysis. We examine two techniques: the relatively simple high-low method as well as the more common quantitative tool, regression analysis.

Exhibit 10-3 

Weekly Indirect Manufacturing Labor Costs and Machine-Hours for Elegant Rugs

Screenshot of a spreadsheet depicts weekly indirect manufacturing labor costs and machine-hours for Elegant Rugs.

The spreadsheet includes the machine-hours and the indirect manufacturing labor costs termed as (X) and (Y) respectively for 12 weeks. Details of the table are as follows:

Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Week 8

Week 9

Week 10

Week 11

Week 12

Total

Advantages and Challenges

Quantitative analysis, in particular regression analysis, is a rigorous approach to estimate costs. Regression analysis requires detailed information about costs, cost drivers, and cost functions and is therefore more time consuming to implement. However, there are more data available today than ever before and with the declining costs of storage and analysis, it is far easier to do regression analysis and gain important insights than in the past. Newer data analytic techniques, requiring heavy computing power, continue to be developed. These techniques focus on prediction and introduce new ways of thinking about quantitative analysis. We develop these ideas and techniques later in this chapter and in the next chapter.