36 S T R AT E G IC F I N A N C E I Au g u s t 2 0 1 1

BUDGETING

Comparing BudgetsP a r t 2 o f 3

How to calculate sales and contribution margin variances with an Excel-based budget

By Teresa Stephenson, CMA, and Jason Porter

This is the second of three articles describing how to

actually use an Excel-based Master Budget for making

managerial decisions rather than just keeping it on dis-

play. In the first article (July 2011), we created a Pro For-

ma Contribution Margin Income Statement and then

used it to calculate the breakeven point and margin of

safety for our example business, Bob’s Bicycles. In this

article, we take that basic analysis to the next step: bench-

marking. We’ll start by adding a Flexible Budget to our

spreadsheet; then we’ll use those numbers to calculate a

set of variances that will let us dig into both the positive

and negative surprises in sales.

Let’s get started.

Creating a Flexible Budget Three “budgets” need to be created in order to perform a

good analysis. The first, a “Static Budget,” is typically pre-

sented as a Pro Forma Contribution Margin Income

Statement, and we created one of those last month using

the information from the Master Budget we developed in

Strategic Finance last year (February–July 2010). The sec-

ond, a “Flexible Budget,” updates the Static Budget using

actual sales in units. When creating this second budget,

we still use our budgeted prices and our expected inputs

for production. The goal with a Flexible Budget is simply

to show what we expect our contribution margin and

profit to be at that level of sales—not to show actual

income. We’ll get to that later. The final “budget” isn’t

really a budget at all, although it’s typically created at the

same time as these other budgets. It’s the actual Contri-

bution Margin Income Statement, using not only our

actual units sold but our actual sales prices, costs, inputs,

etc. (We’ll create that statement next month in the final

article in this series.)

When we create the Static and Flexible budgets, we use

“expected inputs.” An expected input is how many units

typically are needed for production. For example, if we

plan to make 20 gadgets and each gadget requires three

widgets of raw materials, then our expected widget input

would be 60.

Au g u s t 2 0 1 1 I S T R AT E G IC F I N A N C E 37

to Performance

Budgeting. Budgets are often treated like works of art. Enormous amounts of time and

energy are devoted to creating them, including long discussions and careful crafting.

Then, when the masterpiece is finished and ready to be displayed, it’s placed on a shelf

or in a file, but it’s never really used. Yet a good budget should be more than a work of

art—it should be a powerful tool for improving a business. Not only does a good bud-

get provide goals and targets that we can work toward throughout the period, but it also provides a

strong benchmarking tool that we can use to determine what we could be doing better.

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Let’s take a look at the numbers for Bob’s Bicycles. (If

you don’t have a copy of the Master Budget, or if you

need an updated one that contains these analyses, you

can get one from either author.) The Static Budget is in

the tab we set up last month called CM IS (Figure 1, July

2011). Since we created that Contribution Margin

Income Statement based on our original Master Budget,

essentially it’s a Static Budget. As we described before, all

of the numbers we used are based on the planned sales

for the year, with planned sales prices, planned inputs,

and planned costs used to complete the rest of the

Income Statement. This Static Budget provides our best

guess at Bob’s Contribution Margin Net Income for the

period, as well as the estimated fixed costs and the esti-

mated contribution margin. Last month we were able to

calculate Bob’s breakeven point and margin of safety

using these numbers.

Our next step is to add a Flexible Budget to the CM IS

tab. This budget uses the actual sales levels at the end of

the period. That’s all that should change—just the sales

levels. Why? Because comparing only the change from

budgeted units sold to actual units sold (without chang-

ing estimated inputs) allows managers to investigate how

much of the change in profits is strictly because of the

differences between projected and actual sales. And that’s

the first step in performing a good variance analysis.

The first step in creating a Flexible Budget, then, is to

set up columns F and G to look just like the Static Bud-

get. You can copy and paste, or you can insert new

columns and recreate it manually. Just be careful that the

formulas work properly. The per-unit numbers (in col-

umn C of the Static Budget and column F of the Flexible

Budget) should be the same. In fact, you’ll probably want

to link the per-unit numbers in the Flexible Budget

columns to the numbers in the Static Budget. That way

they’ll update automatically each year as you update your

Master Budget. The equations in the Overall column

should be the product of the per-unit number to the left

and the total at the top of the column.

If you copied your Static Budget into the new columns,

be careful to update the equations. When we originally

set up the Static Budget, we used absolute cell references.

For example, in Cell D11 we have =C11*$D$6 so that we

can easily copy our formulas through the rest of the Static

Budget and still have each cell refer to the estimated units

sold. If you copied these columns into the new Flexible

Budget, that permanent reference will still link back to

cell D6. For the Flexible Budget, though, the equation

needs to refer to cell G6. One easy way to fix these refer-

ences is to use the “Find and Replace” function in Excel.

To do that quickly, highlight the cells from G6 to G45,

then type Ctrl+H to open Excel’s “Find and Replace”

function. Put D in the “Find what” box and G in the

“Replace with” box. By choosing “Replace All,” all of the

changes are made in less than a second. You can see the

result in Figure 1. You’ll notice that, without any other

changes, the two budgets give us the same Net Income.

The final step is to replace budgeted units sold with

actual units sold. You’ll notice that we’ve highlighted the

units sold cells in our Flexible Budget in green. Through-

out our budget, we’ve been careful to highlight only those

cells that need to be updated manually. All of the other

cells are equations or links to other data input cells. Most

of the manual inputs are on the Basic Information tab to

make the process of updating the spreadsheet simple, but

occasionally it’s easier or more logical to input the infor-

mation on our actual budget tabs. That’s what we’ve done

here to emphasize the differences between the Static Bud-

get and the Flexible Budget (typing in the information

here allows us to instantly see the differences between

what was planned and what actually happened).

Our investigation showed that Bob’s actually sold

17,074 basic and 8,356 deluxe bikes over the course of the

year. So let’s input those into the Flexible Budget in Cells

G7 and G8. The rest of the information flows through,

instantly updating the total sales revenues, variable costs,

and contribution margin. It’s a beautiful thing to see a

budget working automatically! Of course, the fixed

expenses are the same on both the Static and the Flexible

Budgets since the only difference is in the units sold.

Using the Flexible Budget and Static BudgetOnce you have these two budgets done, you can start

your variance analysis. We aren’t quite ready to do a full

variance analysis; we can’t do that until we finish creating

the actual Contribution Margin Income Statement. But

we can, and should, start our analysis now. Trying to

compare our original Static Budget directly to the actual

results will often confuse the issue: Are the variances

caused by inaccurate sales estimates or problems with

performance? We’ve got to figure out the inaccuracies in

our sales estimates first; then we can move on to evaluat-

ing performance.

In Figure 1, you can see that Bob’s income is $587,646

in the Flexible Budget and $603,748 in the Static Budget.

This difference, about $16,102, is called the Contribution

Margin Volume Variance, and for Bob’s it’s the opposite

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BUDGETING

Au g u s t 2 0 1 1 I S T R AT E G IC F I N A N C E 39

Figure 1: Static Budget and Flexible Budget Together with Sales Still at Budgeted Levels

of what we hope to see. We prefer to see the Flexible Bud-

get income end up higher than the Static Budget income

since that means that we did better than expected. But

you typically won’t see a discussion of the differences

between Net Incomes in these two budgets. Since the

fixed expenses haven’t changed at all between the two

budgets (by definition), any differences are in the contri-

bution margin (hence the name of the variance). The

equation is generally shown as the difference between the

Static and the Flexible Budget contributions to margin,

but the difference between net incomes is the same as the

difference in the contribution margin, so you can calcu-

late it in whichever way makes the most sense to you and

your management team.

In order to get the most information out of a Contribu-

tion Margin Volume Variance, we need to break it down.

The first cause of any differences is probably the sales mix.

Standard costing and cost-volume-profit analysis assume

that sales mix is constant. This assumption allows us to

use a weighted average contribution margin to analyze the

effect of various situations on our profits. But it’s very

unlikely that the sales mix will actually stay constant. To

see the effects of this assumption, start by calculating the

weighted average contribution margin by dividing the

total budgeted contribution margin by estimated total

units sold. For our example, we performed this calculation

on a new Sales Variances tab, shown in Figure 2.

Using the weighted average contribution margin lets

us get a feel for what caused the Contribution Margin

Volume Variance because breaking the total variance into

two smaller variances gives us a better picture of what

happened during the period. The first of these variances

is the Sales Volume Variance, shown in Figure 3, which

allows us to see how overall sales contributed to a drop in

Bob’s budgeted net income. We had originally expected

Bob’s to sell 16,486 basic bikes, but the company really

sold 17,074. They sold almost 500 more basic bikes than

expected, and that’s good. If we multiply the difference

between anticipated and actual sales units by the weight-

ed average contribution margin, we get the dollar amount

of this change. For basic bikes, when we subtract 16,486

from 17,074, we get a favorable unit variance of 588

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BUDGETING

Figure 3: Sales Volume Variance

Figure 2: Sales Variances Tab

units. To get the dollar value, we multiply the 588 units

by the weighted average contribution margin of $55.64

for a total of $32,694. But the deluxe bikes didn’t fare so

well: 8,356 actually sold, so when we subtract the 8,620

expected sales, this yields an unfavorable unit variance of

264 bikes, and when we multiply that by the weighted

average contribution margin, we get an unfavorable vari-

ance of $14,704 ($14,688 if you round to the nearest pen-

ny). The sum of these two variances is a positive $17,990,

a favorable variance. Essentially, this is telling us that

since Bob’s sold 323 more bikes than planned, if the sales

mix had stayed constant, Bob’s would have made $17,990

more than planned. But that isn’t what happened.

To figure out why net income is lower than planned,

we need to calculate the other part of the Contribution

Margin Volume Variance, the Sales Mix Variance. This

variance allows us to see how the change in sales mix

affected Bob’s budgeted net income. Figure 4 shows the

calculations. First, calculate Bob’s expected sales mix by

taking the budgeted unit sales for each model and divid-

ing by the total number of units Bob’s planned on selling.

The sales mix shows that Bob’s has an expected sales mix

of about 66% basic bikes (16,486/25,107) and 34% deluxe

bikes (8,620/25,107). Next, multiply those percentages by

Bob’s actual total sales of 25,430 units. This shows the

number of each model that Bob’s would have sold if the

sales mix had stayed constant. This is the “Flexible Budget

Volume,” or the number of each model Bob’s would have

sold if the budgeted sales mix had actually occurred.

(Remember: On the Flexible Budget, everything remains

at standard except volume.) Next, take the actual number

of units that Bob’s sold for each model and subtract the

Flexible Budget Volume (for example, 17,074 – 16,699 for

basic bikes), and that yields the Sales Mix Variance in

units. In this case, Bob’s sold 375 more basic bikes than

its Flexible Budget predicted at this volume level. You’ll

always have at least one favorable variance and at least

one unfavorable variance when investigating sales mix,

and the sum of these unit variances will always equal

zero. If we had three or more products, the equations

would be more complicated, but the results would still

follow these rules.

This is a long process, but we’re almost finished. As we

did before, we want to turn the unit variances into dollar

amounts. When we calculated the Sales Volume Variance,

we multiplied both unit variances by the weighted aver-

age contribution margin. This time, however, we multi-

plied each unit variance by the budgeted contribution

margin of that unit. You can see this calculation in the

bottom right corner of Figure 4. Now we start to get a

feel for why Bob’s total Contribution Margin Volume

Variance was negative. While we show a $9,175 increase

because of the extra number of basic bikes that Bob’s

sold, the company lost out on more than $43,000 by sell-

ing fewer deluxe bikes. In other words, the company’s

sales mix shifted from the high-margin units to the low-

margin units, dropping its overall contribution margin.

Our analysis, then, demonstrates that Bob’s net income

will fall below the Static Budget income by more than

$30,000 because its sales mix was off!

As depicted in Figure 5, the sum of the Sales Volume

Variance and the Sales Mix Variance is the Contribution

Margin Volume Variance. But that isn’t just a number. We

understand where it comes from and where Bob’s man-

agement can focus its attention in order to improve per-

formance in the future. Bob’s had a big drop in income

because its sales mix shifted to its less profitable units,

and even though some of that loss was offset by higher-

Au g u s t 2 0 1 1 I S T R AT E G IC F I N A N C E 41

Figure 4: Sales Mix Variance

than-expected total sales, Bob’s management needs to try

to shift the sales mix back toward Bob’s high-end units if

they want to improve Bob’s bottom line.

The Effects of Market VariancesFor many managers, the next step would be to get angry

at the sales department for not pushing the more prof-

itable product or at the budget team for setting unrealis-

tic expectations (or perhaps some combination of the

two). But the next step should actually be to dig deeper

into the causes of these variances. Too often managers

and other business leaders do a cursory or high-level

variance analysis and then start trying to fix the problem.

But we don’t yet know enough about Bob’s situation for

the managers to start fixing anything. A true variance

analysis will start with the big picture and then try to dig

a little deeper or a little wider to figure out what caused

the change in sales mix and what allowed the company to

improve the total number of units sold. These questions

aren’t answered easily, but we can look at two additional

pieces of information to glean some preliminary answers.

The first piece of information we need for this analysis

actually comes from outside our business. We need to

figure out both the budgeted number of units sold and

the actual number of units sold in our market. This

information typically can be found in industry publica-

tions and other public sources, but it will depend on the

product you’re selling and your industry. For the sake of

our example, let’s suppose that we found estimates by

industry experts that 2,500,000 bikes would be sold in

2010 in Bob’s market. Since Bob’s had planned to sell a

total of only 25,107 bikes, the sum of both models in

Bob’s Static Budget, the company had anticipated an

approximate market share of 1% (25,107/2,500,000).

Let’s assume that, at the end of the period, 2,675,000

were actually sold in the market during 2010, so Bob’s

actual market share was just under 1%. We’ve added this

calculation to the other variances on our Sales Variances

tab in Excel (see Figure 6).

By subtracting the estimated sales from the actual sales,

42 S T R AT E G IC F I N A N C E I Au g u s t 2 0 1 1

BUDGETING

Figure 5: Reconciliation of Variances

Figure 6: Market Share and Market Size Variances

we see that the overall bicycle market in Bob’s area was

better than anticipated. Overall, 175,000 additional bicy-

cles were sold during the period. Yet if we subtract Bob’s

expected market share from Bob’s actual market share, we

see that Bob’s actually lost ground to its competitors. It

will take some dedicated market research to figure out

why the market went up while Bob’s share went down,

but for now we can use these figures to find out how each

of these differences affected Bob’s anticipated profits.

More specifically, we can calculate two additional vari-

ances that will help us better understand what caused

Bob’s Sales Volume Variance.

The first of these variances is the Market Size Variance.

To find this variance, multiply the 175,000 additional

units sold in the market by Bob’s expected market share.

This gives you the total number of additional units Bob’s

would have sold if it had maintained its budgeted market

share. Based on this calculation, Bob’s sales should have

been 1,700 units higher than it actually was. If we multiply

that number by the weighted average contribution mar-

gin, we get Bob’s Market Size Variance, our estimate of

how much the change in the overall market size should

have changed Bob’s net income. As you can see in Figure 6,

the larger market size should have increased Bob’s profits

by nearly $98,000! What went wrong?

To answer that question, we move on to another vari-

ance, the Market Share Variance. Our earlier calculation

showed that Bob’s market share dropped from 1% to

0.95% during the period. To estimate the net income

effect of that drop, we multiply the total actual sales in

the market (2,675,000) by the drop in market share

(-0.054%). This gives us the number of sales that Bob’s

missed. That result, 1,434 units, multiplied by Bob’s

weighted average contribution margin provides the Mar-

ket Share Variance—and that’s where we find Bob’s prob-

lem. Because Bob’s lost market share, it lost out on nearly

$75,000 of that $98,000 it could have made. As a final

note, the sum of these two market variances is $17,990,

which is Bob’s Sale Volume Variance.

Overall ResultsOur analysis so far has shown that Bob’s has two large

unfavorable variances that reduce its net income: the

$34,000 that Bob’s lost because of a shift in sales mix

toward its lower-end products and the $75,000 Bob’s lost

because it dropped market share. These two results give

the company something concrete it can analyze and

investigate. What kind of advertising does the company

need to do to gain back its market share? How can Bob’s

provide incentives to sell more high-end bikes? What

focus should the company have moving forward? How

should its sales mix change based on demand and its

need to regain market share? Should it consider price

changes to make the deluxe bike more competitive or to

make the basic bike more profitable? What changes did

the company make in its marketing, or what changes did

its competitors make in their marketing? Did the quality

of Bob’s deluxe bikes go down? Did the competitors’

quality go up? These questions will provide Bob’s man-

agement team with a starting place for gathering the

information it needs to regain market share and improve

its cash flows. And it all comes from the budgeting

process. Isn’t that cool?

Continuing the Variance AnalysisBy adding the Sales Variances tab, calculating the Contri-

bution Margin Volume Variance, and then breaking it

down into its component parts, we’ve been able to ana-

lyze and pinpoint some of the most important challenges

Bob’s Bicycles faced. But we’ve only just scratched the

surface of what a good benchmarking or variance analysis

can really do. With each step, we added more to what our

budgets do for us, more to what they provide to our com-

panies and managers. The Master Budget that we so care-

fully crafted last year is a powerful tool for planning the

future. Now we’re adding the tools that will allow it to

also be a powerful tool for examining the past and

improving the future. Next month we’ll be back to build

a Contribution Margin Income Statement that reflects

actual results and to discuss how to use that final piece of

the budget to dig into operating costs, finding out what

led to the increases and decreases in operating perfor-

mance. Until then, Happy Budgeting! SF

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.

Jason Porter, Ph.D., is assistant professor of accounting at

the University of Idaho and is a member of IMA’s Washing-

ton Tri-Cities Chapter. You can reach him at (208) 885-

7153 or jporter@uidaho.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.

Au g u s t 2 0 1 1 I S T R AT E G IC F I N A N C E 43