# Software Associates Case Study Essay

Words: 2166
Pages: 9

Software Associates Executive Summary
Software Associates was founded by Richard Norton in 1990 in order to perform system integration projects for clients. During the rapid technological growth of the 1990’s the company grew and prospered. Annual revenues exceeded \$12 million, and profit margins were generally between 15%-20%. Their services include a contract business which offers clients experienced consultants to implement personalized IT tools and solutions. However, in 2000, founder and CEO of Software Associates, Richard Norton, had an urgent and tough question to answer; with higher than forecasted revenues, why is their bottom line less than half of what they had budgeted?

Variance Analysis Report
In order to perform a
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Due to the increased expenses per consultant, it is also important to study how costs change with the additional consultant.

In order to examine the relationship of overhead costs and number of consultants, Jenkins found the amount of the budget which was deemed variable and which was deemed fixed. The budgeted variable amount was obtained by multiplying each expense’s budgeted amount by the percent in which was expected to be variable. Then, she subtracted the budgeted amount from the budgeted variable amount to find the budgeted fixed amount. These calculations are shown in Exhibit 3A.

Next, Jenkins took numbers and calculated the spending variance and volume variance. In order to perform a spending variance, she subtracted the actual amount spent from the budgeted amount. In this case the actual amount spent was \$938,560 and the forecasted expenses totaled \$877,300. After subtracting those numbers she found that the spending variance was \$61,260. This is an unfavorable outcome of the quarter and can be mostly attributable to the eight extra consultants that were hired. The volume variance is determined by subtracting the budgeted quantity from the actual quantity and then multiplying the cost per unit. In this case, the expected number of consultants was 105 but the actual number of consultants was 113. To determine the cost per consultant, she took the total