# Calculating operating variances: completing a benchmarking analysis with your Excel-based Master Budget.

Budgeting. Once the year is over, company leaders often think that the budget no longer serves a purpose. The accountants and management team typically spend a great deal of time and energy creating the budget, but then the year winds to a close, and the budget is pushed to one side or thrown into the recycling bin. A new budget is being created, new data is being gathered, and new decisions are being made. What help could the old budget be now? But throwing away a good budget at the end of the year is like closing the book on a good mystery just before the final chapter. Using your budget to perform solid variance analyses allows you to finish the story: to see how the company performed, when it deviated from the plan, and why those deviations occurred. It also provides you with the tools to create a more convincing story--a more accurate budget--next year.

This is the third and final article in our series describing how you can use an Excel-based Master Budget for making managerial decisions. In the first article, we added a Contribution Margin Income Statement to our Master Budget and calculated breakeven and margin of safety for Bob's Bicycles. In the second article, we created a Flexible Budget and started analyzing the company's sales and contribution margin variances. In this article, we examine Bob's actual results and use them to calculate the company' operating variances. In doing so, we hope to provide enough details and discussion so you can use these tools to analyze any type of business. Unfortunately, we won't be able to look at every possible type of operating variance, but we'll look at some of the most important examples and discuss their implications.

Creating the Actual Contribution Margin Income Statement

In the first two articles of this series, we created two of the three "budgets" needed to analyze last year's results. We developed the Static Budget first (Strategic Finance, July 2011) using the information from Bob's Master Bud-get (originally developed in Strategic Finance, February-July 2010). Next came the Flexible Budget (August 2011) using the budgeted production information but actual sales quantities. This month we add the last "budget," which isn't really a budget at all, even if it does get lumped in with the budgets. Instead, this final statement reports actual results in the Contribution Margin Income Statement format. Putting the "budgets" together allows managers to easily compare actual results side by side with the original budget and the variable budget, and they can investigate the differences, or variances, from their original Master Budget.

[FIGURE 1 OMITTED]

Unlike the Static and Flexible Budget columns, we use the actual results from operations when creating the Actual Results column. Let's take a look at our example company, Bob's Bicycles. If you don't have a copy of the Master Budget, including the Static and Flexible Budgets that we created for this current series, you can get one by e-mailing either author. Open your spreadsheet to the CM IS tab; that's where we put the three versions of the Contribution Margin Income Statement that we'll use to calculate Bob's cost variances. The first column (as you can see in Figure 1) shows the Static Budget, which consists of numbers pulled directly from Bob's Master Budget. The second column is Bob's Flexible Budget, which we created last month. The final column, which you can easily insert into your budget, uses all the same categories, but this time it shows the actual results from Bob's 2010 operations. As we've done in the past, we highlighted the data that we typed directly into our spreadsheet.

You probably noticed that we typed in only the summary information for each type of cost: total direct materials, total direct labor, total manufacturing overhead, etc. We like the clean look this simplified format provides because it's easy to differentiate the actual results from the budgets so we can focus on a summary analysis first. Trying to jump into the details too quickly during a variance analysis can be as bad as ignoring them. We don't want to miss the forest for the trees, so we've given ourselves a visual reminder to begin our analysis where it belongs: at the top. After we calculate these differences, we can "dig down" to examine those areas that are having the biggest impact on our bottom line.

Keep in mind, however, that just because a high-level analysis shows a small overall variance, it doesn't imply that the lower-tier variances also are small. The company could have large positive variances offsetting large negative ones. Your own company history and detailed knowledge of where trouble spots are likely to be found should also guide the variances you "dig into." As you create your own spreadsheet to analyze your company's variances, tailor it to what you need. Occasionally you should also perform a detailed analysis where you don't think you'll find anything. You might be surprised!

Getting Started with Operating Variances

When calculating operating variances, we always compare the Actual Results to the Flexible Budget. The Flexible Budget numbers are our standard input units and costs and our sales prices. Yet sales volume has been adjusted in the Flexible Budget to match actual sales. This eliminates variances caused because we sold more or less than we anticipated and gives us a more accurate picture of what should have happened during the period. For example, we wouldn't want to get excited that we saved \$100,000 in labor costs if we produced and sold only 10,000 units instead of 25,000 units. We know that costs will change as our sales level changes. Variance analysis really helps us when we compare budgeted costs at a given level of sales with the actual amount spent at the same level. With that in mind, let's take a closer look at Bob's operating variances.

Direct Labor Variances

Let's start with Bob's direct labor costs. Bob's payroll records show that the company paid out a total of \$1,126,246 for direct labor during 2010. This was \$63,254 more than Bob's had planned. Because Bob's has only one type of labor, this difference is pretty straightforward. First, though, we need to summarize Bob's actual production, which we've done in Figure 2. This figure provides all the actual data we need to do our variance analysis for Bob's Bicycles, but each company will need to adjust this table based on the variances it wants to examine.

[FIGURE 2 OMITTED]

We calculated Bob's direct labor variances in a new Cost Variances tab that we added to our Master Budget spreadsheet. Using a new tab allows us to keep Bob's Cost Variances separate from the Sales Variances, making our work easier to explain to other managers. In our calculation (see Figure 3), the first row presents the raw data: Bob's actual wage per hour (AP), actual number of hours used (AQ), standard wage per hour (SP), and standard hours required to produce the units sold (EQ). All these numbers are already available in our spreadsheet or can easily be calculated. For example, AP doesn't appear in the budget, but we can calculate it by dividing the total direct labor of \$1,126,246 (available in the Actual Results column of the CM IS tab on the Master Budget spreadsheet) by the actual direct labor hours (available in Bob's actual results, shown in Figure 2). AQ is reported on the CM IS tab. SP comes from Bob's Direct Labor Budget. Finally, EQ is the sum of the total direct labor hours needed for each type of bike (found on the Basic Information tab) times the total number of each type of bike actually sold (found in the Actual Results column on the CM IS tab).

[FIGURE 3 OMITTED]

Row 6 of Figure 3 calculates the products that form the basis of the variance calculation. First, we multiply AP times AQ, then AQ times SP, and finally SP times EQ. Then we calculate the Direct Labor Price and Quantity Variances by subtracting the products as shown in row 8 of Figure 3. The final number, in cell R11, is Bob's total direct labor variance. This final value can be calculated two ways. You can either subtract the actual cost (AP X AQ) from the standard cost (SP X EQ), or you can add up the price and quantity variances. All of these equations are shown in formula view in Figure 4. A more detailed explanation of the math underlying the variance calculations is available from either author.

In our example spreadsheet, we set up the equations for all of the different inputs so that they are automatically calculated each year when we input Bob's budgeted and actual cost, price, and unit values. As part of setting up these equations, we added a simple if/then statement in Excel to automatically report if each variance is favorable or unfavorable. The statement we used looks like this: = IF(Q8 < 0, "unfavorable", "favorable"), which means if the variance is negative, show the word "unfavorable"; if the variance is zero or positive, show "favorable." You can see examples of this equation in Figure 4.

Bob's Labor Rate (or price) Variance is \$40,420 unfavorable (Figure 3). This makes sense because Bob's actual hourly wage was \$0.52 higher on average than expected. When the management team talked to the production manager, they found out that there was a great deal of turnover, so rising starting wages were probably the cause of the higher average wage rate. But another explanation could be that the inexperienced workers needed to put in overtime in order to complete orders on time. Rising wages would need to be reflected in next year's budget, but overtime that was the result of lack of experience would need to be monitored and eliminated as soon as possible.

Bob's Labor Efficiency (or quantity) Variance is also unfavorable, but it's only \$22,834 (Figure 3). This variance was caused by the more than 1,600 extra hours used to produce Bob's bikes during 2010. Again, this variance probably occurred because of extra hours caused by high turnover either in the form of overtime to complete the bikes or learning-curve hours. Either way, it's a number worth watching in the coming year.

[FIGURE 4 OMITTED]

This examination of causes is the true benefit of variance analysis! It allows you to figure out things that are going on in the company that otherwise may never cross your desk. This gives you the opportunity to follow through on operating "inefficiencies," to ensure that the production manager is given the support needed to train the new employees well enough to shorten the learning curve, and to update the budget so next year's predictions are more accurate. Over time, as the line workers' efficiency increases, Bob's will be able to reduce its budgeted number of hours needed to assemble a bike.

[FIGURE 5 OMITTED]

Calculating and Investigating Direct Materials Variances

Direct materials variances are calculated in much the same way as direct labor variances. When creating a Direct Materials Budget as part of the Master Budget (March 2010), most companies base their estimates on the specific units needed for each item they produce. In practice, however, companies typically don't track their direct materials inventory for each production model. The information should be part of a company's cost of goods sold (COGS) calculations, so with a little digging you can find what you need. Luckily, you don't really need to start with a lot of detailed information in a typical variance analysis. You can start with the overall cost of each part and how many parts were used in production compared to how many were budgeted to be used. Only if this general analysis isn't sufficient to improve your production process would you need to dig into separate variances for each item produced. To begin, then, you just need to know the total amount of materials actually used during the year, which you can easily calculate by adding beginning direct materials inventory and net purchases and subtracting ending direct materials inventory.

The result for Bob's Bicycles can be seen in the Total Direct Materials line of our Actual Results column on the CM IS tab (\$2,591,693). If we subtract that number from the Flexible Budget amount, we see that Bob's used \$144,395 more in raw materials than it should have needed to produce 17,074 basic bicycles and 8,356 deluxe bicycles. Figure 5 shows this calculation on the Cost Variances tab of our Excel spreadsheet.

Bob's direct materials variance is unfavorable because the company spent more buying raw material than planned. Be careful, however, not to interpret favorable variances as "good" and unfavorable variances as "bad." An unfavorable variance may be caused by a variety of reasons, including an out-of-date budget, inexperienced labor, rising input prices, or even a sudden increase in demand leading to overtime. A favorable variance could be caused by dropping prices, a change in demand, or a failure to perform maintenance, which might lower variable manufacturing overhead in the short run but lead to huge costs in future years. Similarly, bookkeeping errors can cause variances. The goal is to find the differences between actual and budgeted spending, break the differences into smaller pieces, investigate them, and find the causes. Not until you get to the actual causes can you be sure if a variance is "good" and should be incorporated into your business model or "bad" and should be eliminated.

Since Bob's uses 10 different materials to produce the two types of bicycles it carries, we really need to break its materials variance into at least 10 individual sets of calculations (more if the company wanted to split it out by model). This may seem like a lot of information, but it will provide the detail that management needs to figure out why Bob's spent \$144,395 more than it had planned. Using an Excel-based budget, we can easily automate this process. We have the standard number of parts per bicycle and cost per part in the Master Budget. The only numbers we need from Bob's actual records are how many units of each part the company used in production and the actual costs of those parts. Because we need additional information, we added the actual results to the Cost Variances tab (shown in Figure 2).

[FIGURE 6 OMITTED]

Now we can calculate a price and quantity variance for each of Bob's materials. Each pair of variances can be added together to get a flexible budget variance for that material, and the 10 flexible budget variances can be added together to get the total \$144,395 direct materials variance. The variances for all 10 raw materials appear in our example spreadsheet, but we are only going to show two here (see Figure 6). Luckily, the equations and principles are the same for all of the material cost variances.

Let's first examine the calculation for Bob's most expensive raw material: steel. The AQ for the steel is found in the "Additional Information Needed" table shown in Figure 2. We calculated AP (\$15.73) by dividing the total cost for steel in Figure 2 by AQ. The SP, or standard price per unit, for steel is available in the Direct Materials budget. Since we have two models of bikes and Bob's uses the same type of steel for both, we'll have to calculate two expected values and then add them together to get the total EQ for this analysis. As shown in Figure 4, Bob's should have used 63,394 units of steel to produce the bikes it sold.

Our table for the direct materials variances is set up just like the table for the direct labor variances shown in Figure 3. To calculate the quantity variance, we multiply both the expected quantity (EQ) and the actual quantity (AQ) times the standard price (SP), which gives us \$950,910 and \$956,498, respectively. By taking the difference between these two figures, we get Bob's Steel Quantity Variance: \$5,588 unfavorable. This makes sense because Bob's used 63,767 units of steel instead of the budgeted 63,394. Next, we subtract the total amount actually spent on steel (\$1,002,772) from the product of the actual quantity (AQ) times the standard price (SP). The result, a \$46,274 unfavorable price variance, also makes sense because Bob's spent an average of \$15.73 on steel instead of the \$15 budgeted. The sum of these two variances, Bob's Flexible Budget Steel Variance, is \$51,862 unfavorable.

When Bob's managers began to investigate their steel variances, they discovered two things. First, the price of steel jumped to \$16 a unit in the third quarter, which increased Bob's average cost. Since Bob's has little control over the price of steel, the company needs to update future budgets with the accurate price. Second, new line workers seemed to have problems during their training, and some steel was wasted. The production manager has the ruined material on hand and is trying to sell it as scrap. This isn't something that should continue to hap-pen, so Bob's management team will need to monitor direct materials usage and the training program until they are sure that the production department is operating normally again.

In calculating the remaining direct materials variances, we used the same format. For some items that are used in only one model of bike, however, such as rubber handles and regular seats, we had to be sure that the expected quantity (EQ) included only the model that used the material. As an example, let's take a quick look at the direct materials variance for Bob's expanded gear shift. This gear shift is used only in the production of deluxe bikes. If you look at the calculations in Figure 6, you can see that it, too, had an unfavorable quantity variance, but it had a favorable price variance. Bob's management team discovered that the production manager changed vendors because she found a start-up company willing to give Bob's a price break in exchange for a long-term contract. Again, Bob's will need to use the lower cost of this new item in its next budget.

Bob's ended up with unfavorable quantity variances for all raw materials primarily because of its new workforce. Upper management should monitor the situation careful-ly to make sure that this waste disappears as the training period ends. If it doesn't, the company will need to consider other explanations--shrinkage, for example. It isn't comfortable to suspect that one of your employees is taking home raw materials for personal use, but persistent unfavorable quantity variances can uncover just such a problem. Alternatively, perhaps the "recipe" for raw material usage is wrong and needs to be updated. In Bob's case, though, it's hard to see a bike taking, for example, more than one seat!

Other Variances

Probably the best part about working with cost variances is their similarity. Although the titles and interpretations change, the equations stay the same. Because they are so similar, we aren't going to specifically calculate Bob's overhead variances. Instead, we'll just mention three important facts to keep in mind. First, the Variable Overhead Quantity Variance measures the efficiency of the allocation base or cost driver, not how well variable costs were used. Second, because there isn't an explicit "recipe" of overhead inputs to outputs, determining the cause of overhead variances typically takes some work, so it's best to focus on larger variances. Third, while you can occasionally fire a salaried employee or find a cheaper office space to rent, most Fixed Overhead Variances require a change in future budgets.

Even as you start preparing a new budget for a new year, your old budget doesn't have to stop being useful. Once the year is over, you can use your old budget to examine how your business lived up to the plan that you and your colleagues so carefully crafted before the year began. This series of articles demonstrated some of the analyses that you can do with an Excel-based Master Budget after the year ends. We started by creating a Contribution Margin Income Statement and calculating the breakeven point and margin of safety for our example company, Bob's Bicycles. By adding this tab to your Master Budget, you can have those useful pieces of information at your fingertips from day one of the planning process.

In the second article, we added a Flexible Budget to the spreadsheet and used it to investigate how the contribution margin was affected by changes in unit sales and to calculate the contribution margin variance, sales volume, and sales mix variances for Bob's Bicycles. These slices of information can point a company in the right direction to find out why the business didn't meet its budgeted expectations or how to keep doing something that worked better than expected.

By Jason Porter and Teresa Stephenson, CMA

Jason Porter, Ph.D., is assistant professor of accounting at the University of Idaho and is a member of IMA's Washington Tri-Cities Chapter. You can reach him at (208) 885-7153 or jporter@uidaho.edu.

Teresa Stephenson, CMA, Ph.D., is associate professor of accounting at the University of Wyoming and is a member of IMA's Denver-Centennial Chapter. You can reach her at (307) 766-3836 or teresas@uwyo.edu.

Note: A copy of the example spreadsheet, including all the formulas, is available from either author. IMA members can access all previous articles in the first series via the IMA website at www.imanet.org after logging in.
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