Let’s look at a simple example of how the plan vs. actual analysis works.

For the record, in accounting and financial analysis, they call the difference between plan and actual variance. It’s a good word to know. Furthermore, you can have positive or negative variance, as in good variance and bad variance.

## Positive Variance:

• It comes out as a positive number.
• If you sell more than planned, that’s good. If profits are higher than planned, that’s good too. So for sales and profits, variance is actual results less planned results (subtract plan from actual).
• For costs and expenses, spending less than planned is good, so positive variance is when the actual amount is less than the planned amount. To calculate subtract actual costs (or expenses) from planned costs.

## Negative Variance:

• The opposite. When sales or profits are less than plan, that’s bad. You calculate variance on sales and profits by subtracting plan from actual.
• When costs or expenses are more than planned, that’s also bad. Once again, you subtract actual results from the planned results.

I’d like to show you that with a simple example. Let’s start with a beginning sales plan, then look at variance, and explore what it means. This is a simple sales forecast table — a portion, showing just three months — from a standard sales forecast.

## Beginning Sales Plan

To set the scene, this illustration shows three months of the sales forecast as the business plan is finished.

## Actual Results for Sales

The next illustration shows the actual results for the same company during the same three months as in the previous illustration.

## Sales Variance

The illustration shows the sales variance for the same months. The red numbers represent the negative variances, which are sales amounts less than you forecasted.

## What Matters is the Management

Notice in this example that the variance analysis should be just the beginning of a discussion, not an end result. Take the case of the sales of new bicycles.

This business ended up selling fewer units than planned (31 instead of 36), which seems like a disappointment. But on the other hand, the units they sold had a higher price than planned (\$615 instead of \$500). So sales in dollars were \$1,053 higher than planned (\$19,053 instead of \$18,000).

That’s where the management begins. The variance leads to questions about pricing, marketing, promotions, and future projections. Do they worry about selling fewer units, at higher prices? Do they take that as a marketing or seasonal trend? Or a successful change of product variety to favor the higher-priced bikes?

What they do next is the question. Variance analysis helps frame the questions they should be asking. And provides insight to successfully answer or at least test possible solutions.

Tim Berry is the founder and chairman of Palo Alto Software and Bplans.com. Follow him on Twitter @Timberry.