Overview:

You are working as a business consultant, helping companies to better manage their costs. One

of your clients is Supremo Burritos, a chain of $100$ quick service burrito stores across the state of

Pennsylvania. Supremo Burritos has approached you because they would like to better

understand their operating costs aside from their costs for food, labor and rent. You have been

given a dataset which includes several pieces of data the client has collected over the past two

years. Your goal is to use data analysis to help Supremo Burrito's management generate a cost

equation that will be useful for predicting future "other operating costs" for your client using the

best available cost driver or drivers.

Getting started:

The dataset includes $24$ months of data for Supremo Burritos' "Other Operating Costs" as well as

$6$ possible drivers. The dataset also includes additional data on the underlying items that make up

"the total "Other Operating Costs".

To complete the project you will need to follow the all the steps in parts $1,2,3$ and $4$ and write a

memo as described in part $5.$

Before starting parts $1$ through $4,$ I would recommend setting up a separate tab in your excel

spreadsheet for each possible cost driver and including all of the required items in parts $1-4$ that

relate to that specific cost driver.

For Parts $1-3,$ Treat "Other Operating Costs" as a single cost pool

Part $1$: Estimate the basic cost equation for "Other Operating Costs" using the High$-$low

method separately for each possible cost driver

Use the High$-$low method to determine the cost equation that expresses how monthly "Other

Operating Costs" behave in relation to that particular cost driver. Clearly show the two months

you used to generate the High$-$low equation. Be sure to clearly state and label the resulting high$-$

low equation for each possible cost driver.