Testing a Decision Before You Make It

Short Answer: What-if analysis for a small business means copying your current numbers, freezing that copy as the baseline, changing one assumption, and comparing the two side by side. The comparison should show the change in profit and in cash over a full year, and the point at which the decision stops paying, such as how many customers a price increase can lose before it costs you money.

Most owners test decisions by living through them. They raise prices and wait to see who leaves, or hire and find out in three months whether the work was there. Some of those decisions can be undone. Many are expensive to reverse. A what-if test runs the decision on paper first, against the business you actually have.

The Method in Four Steps

1. Start from the real business. Use your own revenue and costs, not an industry template. A test built on someone else's margins answers someone else's question.

2. Freeze a copy of today. Save the current numbers as a baseline that doesn't move. Your live books will keep changing. The baseline has to stay put so the comparison means something.

3. Change one thing. A price, a hire, a payment term. Change two at once and you won't know which one produced the result.

4. Compare three columns. Current, the change, and the resulting scenario, stated over a full year so a seasonal business isn't judged on one good month.

A Worked Example: Raising the Mowing Price

Take a hypothetical landscaping company, Greenline Landscaping: about $520,000 a year in revenue, of which residential weekly mowing is 30%, or $156,000. A mowing visit sells for $55 and costs $42 in crew time, fuel and equipment, leaving $13 of gross profit. At that price, the $156,000 comes from about 2,836 visits a year.

The owner is considering $60 a visit. Nothing about the visit changes, so the direct cost stays at $42 and gross profit per visit rises from $13 to $18.

If every customer stays:

If 10% of visits are lost (some customers cancel, or skip weeks):

Revenue goes down and profit still goes up by about $9,100, because each lost visit also takes its $42 of cost with it. The crew hours freed up can go to installs, which carry a higher margin.

Where Does the Decision Stop Paying?

The most useful number in a what-if test is the break-even point. At $13 a visit, the current 2,836 visits earn $36,873. At $18 a visit, the business needs only $36,873 ÷ $18 = about 2,048 visits to earn the same. That's a loss of about 28% of visits before the price increase costs Greenline anything.

A 9% price increase that can survive losing more than a quarter of the volume is a strong decision. The owner can now judge it against what they know: in most local lawn-care markets, losing a quarter of weekly customers over $5 a visit would be unusual. Owners who never run this number tend to underprice for years, because the fear of losing customers has no size attached to it.

What About Cash?

Profit is one half of the test. A decision can raise profit and still strain the bank account for a while: a new hire is paid every two weeks from day one, while the revenue they bring in arrives on 30-day terms. The mowing price is the easy case, since residential clients pay on completion, so the extra profit arrives as cash in the same week. A good test states the cash effect next to the profit effect, so you can see a timing problem before it happens.

Why One Change at a Time?

Suppose the owner raises the mowing price and drops the local ad budget in the same season. Profit rises. Was it the price, the saved $1,500 a month in ads, or fewer new customers cancelling out both? With one change per scenario, each answer is clean. To try a variant, such as $58 instead of $60, copy the scenario and change that one number, so each version is measured against the same baseline.

What to Look For

• The break-even point, not just the expected result. "Profit rises $14,182 if nobody leaves" is a hope. "Profit rises unless more than 28% of visits leave" is a decision you can judge.
• A full year, not a month. Greenline earns most of its revenue from April to October. A test run on one July flatters any decision that adds volume.
• Cash timing next to profit. Anything paid now and earned later, like a hire or new equipment, needs both columns.

What a Finance Consultant Would Do Next

A consultant working with Greenline would run the same test on the other two revenue streams, see whether the crew hours freed from lost mowing visits can be filled with installs at a 42% margin, and turn the chosen price into a rollout plan: which customers hear first, and when.

That analysis is what Occam's Model runs on your own books. It makes a copy of your business with the current numbers frozen, lets you change one thing by hand or have AI suggest changes for pricing, costs, marketing, cash timing and more, then shows current, change and result over a year with a task list to carry it out. When you need extra help, an expert can review it with you.

Common Questions

What is what-if analysis for a small business?
Changing one assumption in a copy of your real numbers, like a price or a hire, and comparing the result with the business as it is today, before you make the change for real.

How is a scenario different from a forecast?
A forecast projects the business as it's heading. A scenario asks what happens if you change one thing. Most decisions need the scenario first.

How many scenarios should I compare?
Two or three per decision is usually enough: the change you're leaning toward, a milder version, and possibly a worst case.

Should I test a decision that's easy to undo?
Quick ones, yes. It takes minutes and it tells you where the decision stops paying, which you won't learn by trying it.