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.
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.
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.
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.
So the calculations are simple enough. You calculate the variance in sales by subtracting the planned amount from the actual amount, which gives us the table shown below.
I use the classic accountant's red to indicate negative numbers, as in the phrase "in the red." The negatives are also in parentheses. For those cases, the actual sales were lower than planned. Positive numbers here mean actual sales were higher than planned.
You probably see some obvious conclusions. These are just numbers, but they are also indicating areas for more management.
The negative results for unit sales of systems are well below plan. And the per-unit revenue is down too.
Although units of service are disappointing, the price per unit was up, so sales were above plan.
There were pleasant surprises as well for software and training.
Given what's happened with the sales results, the plan-as-you-go planning process indicates in this example that systems sales are going badly, but there are other sales that can make up the problem.
Do you change the plan? That's where the management comes in. Get the people together and talk about it. Why are systems sales so much less than plan? Were the assumptions wrong? Was the plan too optimistic? Has something happened -- new competition, for example, or new technology, or something else -- to change the situation as it was planned.
What about the people? Here's where you have to manage expectations and follow up. Do you have metrics on sales presentations, leads, close rates? Have the people been performing, but just not getting the sales? Was your pipeline assumption wrong?
For this example, let's say we decide to adjust the sales forecast to absorb some changed assumptions. The next illustration shows the new sales forecast, after adjustments.
The illustration shows the revised plan in the April and May columns, even before they happen, to reflect the changes shown in the January-March period. Why would we work with an obsolete plan when the situation has changed.
Does this blow the plan vs. actual comparisons for future months? Not if you make the changes correctly, with everybody on the team being aware of them. You just keep moving your plan forward in time, revising for future months.
In the end, it's not a game. So what if you change the scoring in the middle. The point is managing the company better. Since the company knew systems sales would be down, it has planned on it and made a revised forecast in the actuals area. The same revision affects projected profits, balance sheet, and — most important — cash.
One of the more stubborn recurrent paradoxes in all business planning is the problem of consistency vs. the brick wall.
Consistency refers to a fact of life in small business strategy: it's better to have a mediocre strategy consistently applied over three or more years than a series of brilliant strategies, each applied for six months or so. This is frustrating, because people get bored with consistency, and almost always the people running a strategy are bored with it long before the market understands it.
For example, I was consulting with Apple Computer during the 1980s when the Macintosh platform became the foundation of what we now call "desktop publishing." We take it for granted today, but back in 1985 when the first laser printers came out, it was like magic. Suddenly a single person in a home office could produce documents that looked professional.
People might argue with this, but what I think I saw in Apple at that time was smart young managers getting bored with desktop publishing long before the market even understood what it was. They started looking at multimedia and other bright shiny new things, lost concentration on desktop publishing, and lost a lot of market potential as Windows vendors moved in with competitive products.
The brick wall, on the other hand, refers to the futility of trying to implement a flawed plan. You've probably run into this problem at times. People insist on doing something "because that's the plan" when in fact it just isn't working. That kind of thinking has something to do with why some Web companies survived the first dotcom boom and others didn't. It also explains why some business experts question the value of the business plan. That's sloppy thinking, in my opinion, confusing the value of the planning with the mistake of implementing a plan without change or review, just because it's the plan.
This consistency vs. revision paradox is one of the best and most obvious reasons for having people -- owners and managers -- run the business planning, rather than algorithms or artificial intelligence. It takes people to deal with this critical judgment.
One good way to deal with it is focusing on the assumptions. Identify the key assumptions and whether or not they've changed. When assumptions have changed there is no virtue whatsoever in sticking to the plan you built on top of them. Use your common sense. Were you wrong about the whole thing, or just about timing? Has something else happened, like market problems or disruptive technology, or competition, to change your basic assumptions?
Do not revise your plan glibly. Remember that some of the best strategies take longer to implement. Remember also that you're living with it every day; it is naturally going to seem old to you, and boring, long before the target audience gets it.
The next illustration shows the actual results recorded in that portion of the profit and loss, after the end of March. The actual results mean little without comparison with the original profit and loss table, shown previously. Unfortunately, many businesses also forget to compare the original plan to the actual results. Especially if business is going well -- the operation shows a profit, and cash flow is satisfactory -- comparisons with the original budget are made poorly or not at all.
The table shows actual results. Note how actual sales, costs, and expenses are different from the planned numbers. This is a portion of the full table.
So here's the significant view, the variance. Sales are below plan, but costs are also below plan, and let's stop there and make a point. You can see in the illustration how sales are negative and costs are positive. If you weren't careful, you could interpret that as sales are down and costs up, which would be a disaster. But variance analysis is fairly specific, defined by accountants and financial analysts, so the positive in the direct costs lines means less costs, not more. That can be tricky.
You can check on that by looking at the gross margin. The gross margin is disappointing, below plan, but not horribly so. It seems like the cost controls helped soften the blow of lower sales.
Then you start looking at the expense rows, and there are several interesting surprises.
This is where we go from the accounting details, the actual calculation, to the human details. What happened here? What should be changed? Does the plan need revision? Have assumptions changed. How have the people performed?