# Software associates case study

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 variance analysis report Jenkins calculated the actual revenues and expenses and found the difference which was \$296,610 in profits. Then Jenkins did the same with budgeted values and found the budgeted profits to be \$606,350. The variance amount in turn is \$309,960 under budget.

Also, the variance amount for revenues is \$32,100. This number is favorable due to the fact that they made more than what they had budgeted for. But on the contrary, the variance amount for expenses was \$342,060, which was unfavorable because they spent far more than what they had budgeted for. This information would not be sufficient in order to explain to Norton why their profit percentage is nearly half of what they budgeted. This variance analysis report only shows the raw numbers and not any details to why they spent more on expenses than what they budgeted.

Jenkins would have a difficult time explaining details to why they went over budget. She would need to show him a detailed expense report of the budgeted items and the actual amount they spent on the items. Then she would have to clearly define which items went over budget and why. This variance analysis report would not help Jenkins in the 8 am meeting she has would need to provide more information. Preparing the Budget: Variance Analysis Report In order to provide more information to Norton, Jenkins will need to perform a variance analysis report.

Jenkins would be required to use the numbers provided in Exhibit 2. She will use the numbers on the budget and actual income statement to identify revenue quantity, which is provided in number of hours. She will then identify actual and expected quantity. The actual number of consultant hours exceeded the expected number of consultant hours. Then Jenkins subtracted the actual amount of hours from the expected amount of hours and then multiplied by the expected labor price of \$90. Jenkins found that Software Associates made a total of \$278,100 when providing the extra amount of hours billed.

This is favorable for Software Associates if the billing rate was \$90 as expected; however the average rate per consultant amounted to \$83. 69. Next, Jenkins determined the average billing rate variance by subtracting the actual price from the expected price. She then multiplied the difference in price and the quantity of work done. Jenkins found that they had a deficit of \$246,090. This is unfavorable because Software Associates is losing money due to the actual rate drop from \$90 to \$83. 69. When Jenkins compared the variance of both quantity of hours and hourly rate, this gave her the total revenue variance of \$32,100.

The total revenue variance is also the difference between the actual revenue and expected revenue. Over all, it is favorable that Software Associates created more revenue. Jenkins then determined whether or not the additional revenue would cover the additional costs incurred for the excess consultants. Jenkins used the same method for consultant expenses. By subtracting the actual number of hours supplied (50,850) from the budgeted number of hours supplied (47,250) and multiplying the expected costs, \$37, Jenkins found a cost of \$133,200. \$133,200 is the amount they paid over the expected cost due to the increase in actual labor.

Next, Jenkins took the actual cost of \$39. 90 and subtracted the expected cost of \$37 then multiplied the actual amount of labor hours, 50,850. This amounted to \$147,465. This is the extra amount Software Associates paid due to the labor cost change. The two numbers, \$133,200 and \$147,465, equal \$280,800. The difference in consultant salaries cost from actual to expect cost is \$280,800. Overall operating expense is broken down into two categories, actual and expected. Subtract the actual operating expense, \$938,560, from the expected operating expense of \$877,300 to get the variance of \$61,260.

This amount is unfavorable. Jenkins found the total expense variance by completing the same equation. She subtracted the expected total expense from the actual total expense. The total expense variance was found to be \$342,060. The extra hours worked created more costs than the extra revenue acquired. This puts the company in an awful position. The budget was not planned out very well. The price of the billed labor decreased while more labor was done and less was billed for. This is an equation for disaster as you can see.

More planning must be taken when figuring out a budget and Software Associates must stick strictly to the budget for reasons like this. Numbers can add up quickly. Expense Analysis: Spending and Volume Variance Analysis of Operating Expenses Jenkins then needed to analyze the expense analysis. Many of the expenses for Software Associates were not entirely fixed costs or variable costs. Rather, many of the expenses were a combination of fixed and variable costs. Therefore, Jenkins evaluated the overhead of the company and prepared Exhibit 3, which shows her judgment about each expenses degree of variability.

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 variable cost [\$525,000] and divided it by the actual number of consultants [113] and got \$4,646. Therefore by multiplying \$4,646 by 8 Jenkins found the volume variance of \$37,168. This is unfavorable and when compared to the spending variance, she determined that one of the major faults in Software Associate’s expenditures for the quarter was hiring the extra eight consultants which were not budgeted for.

Billing Percentage: Analysis of Revenue Change After analyzing the expense analysis, Jenkins wanted to understand why the actual number of consultants was nearly 8% higher than the budgeted amount when revenues only had increased by 1%. Jenkins knew if she viewed the budgeted amount of hours allocated for consultants versus the actual hours spent towards consultants she would be able to determine if the consultants were being less productive. First Jenkins viewed the billing percentage by analyzing how much the consultants were billed for versus how much they were expected to be billed for.

The consultants were billed for 39,000 hours when they supplied 50,850 hours creating an actual billing percentage of 76. 7%. The budget, however, projected to bill for 35,910 hours when actually supplied 47,250 hours creating a 76% billing percentage. Jenkins noticed there was a difference of 3,600 hours that were billed and supplied for which was not allocated in the budget. Each of these numbers was found by Jenkins referring to Exhibit 4. Jenkins also noticed that the average billing rate per consultant decreased from \$90 to \$83. 69.

Overall Jenkins saw that if she took the actual hours supplied [50,850 hours] and multiplied it by the actual billing percentage [76. 7%] and then multiplied that by the actual cost per consultant [\$83. 69] that there was an actual cost of \$3,264,073. 1955 spent towards her consultants. Jenkins also noticed that when she recreated this same equation but in retrospect of Software Associates budgeted amount she found that they were only budgeted to spend \$3,231,900. 00 on consultants. This was found by taking the budgeted hours supplied [47,250 hours] and multiplying it by the actual billing percentage [76. %] and then multiplying that by the actual cost per consultant [\$90. 0]. (Each of these numbers was found by Jenkins referring to Exhibit 4. ) After analyzing the actual amount versus the budgeted amount of money Software Associates allocated towards consultants, Jenkins noticed there was a \$32,173. 1955 increase in spending this quarter. Jenkins noticed that the billing percentage increased and the rate per consultant decreased. Based on the increase of consultants allocated and the increase in salary and fringes per consultant, Jenkins realized she is paying more for consulting.

Their work does not appear to be more productive in the grand scheme of things. Software Associates are paying a lot more money for more consultants and not receiving a high enough overall revenue increase. Jenkins further analyzed Software Associate’s spending towards their increase in consultants by directing her attention towards the increase in hours supplied by the consultants [3,600 hours= 50,850-47,250] and multiplied that by the expected billing percentage [76%] and multiplied that by the expected rate per consultant hour [\$90] and there was a variance of \$246,240. 0. \$246,240. 00 defines the amount that would have been spent per consultant. This is an unfavorable outcome for Software Associates because they are spending a considerable amount of money and not receiving a high return on investment per consultant. The quantity of work is not benefiting the company enough to spend more money on maintaining that number of consultants. Lines of Business: Analysis of Actual versus Budgeted Revenues, Expenses and Margins Appendix Exhibit 1: Exhibit 2: Budget and Actual Income Statement Q2 2000 [pic] Exhibit 3: Expense Items: Budget Q2 2000 | |  |  |  |  | |  |  |  |  |  | |  |Administrative and Support Staff |225,000 |191,250 |80% | |  |Information Systems |  |126,200 |120,000 |80% | |  |Depreciation |  |23,400 |22,700 |0% | |  |Dues and Subscriptions |  |11,800 |13,100 |80% | |  |Education and Training |  |36,200 |38,900 |80% | |  |Equipment Leases |  |  |23,500 |22,440 | |  |Office Supplies |  |86,200 |89,600 |80% | |  |Postage |  |  |27,300 |24,700 | |  |Telephone |  |  |40,000 |38,500 | |  |Utilities |  |  | \$ 26,600 | \$ 24,000 | |Advertising and promotion | 22,100 | 15,100 |0% |0  |15,100  | |Admin. and support staff | 225,000 | 191,250 |80% |153,000  |38,250  | |Information systems | 126,200 | 120,000 |80% |96,000  |24,000  | |Depreciation | 23,400 | 22,700 |0% |0  |22,700  | |Dues and subscriptions | 1,800 | 13,100 |80% |10,480  |2,620  | |Education and training | 36,200 | 38,900 |80% |31,120  |7,780  | |Equipment leases | 23,500 | 22,440 |25% |5,610  |16,830  | |Insurance | 33,600 | 32,200 |0% |0  |32,200  | |Professional services | 39,500 | 34,700 |0% |0  |34,700  | |Office expense | 42,100 | 36,550 |100% |36,550  |0  | |Office supplies | 86,200 | 89,600 |80% |71,680  |17,920  | |Postage | 27,300 | 24,700 |80% |19,760  |4,940  | |Rent – real estate | 117,260 | 117,260 |0% |0  |117,260  | |Telephone | 40,000 | 38,500 |100% |38,500  |0  | |Travel and entertainment | 57,800 | 56,300 |100% |56,300  |0  | |Utilities | 26,600 | 24,000 |25% |6,000  |18,000  | |Total | 938,560 | 877,300 |  |525,000  |352,300  | |Number of consultants |  |  |  |113  |  | |Budgeted variable/consultant |  |  |  |\$4,646  |  |

Exhibit 3B: Expense Items Spending Variance and Volume Variance: Budget Q2 2000 Calculate spending variance from flexible budget |Actual Expenses |Budgeted Fixed |Budgeted Variable per Consultant |Actual Number of Consultants |Flexible Budget |Spending Variance |Favorable/ Unfavorable? | | |\$938,560 |\$352,300 |\$4,646 |113 |\$877,300 |\$61,260 |Unfavorable | | | | | | | | | | |Calculate volume variance | | |Actual Number of Consultants |Budgeted Number of Consultants |Budgeted Variable per Consultant |Volume Variance |Favorable/ Unfavorable? | | | | |113 |105 |\$4,646 |\$37,168 |Unfavorable | | Exhibit 4: Budget and Actual Income Statement: Q2 2000[pic]

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