The Numbers Behind Good Business Plans
Credible data make or break investment decisions in any business plan. Here's how to better estimate the opportunity and financials.
This is the third in our series on using data to estimate the future. Each article can be read on its own, but if you’d like to start at the beginning, click here.
You need a loan to open your own restaurant chain. The bank asks for your business plan.
You want to build a new product or launch a new venture. Management asks for the business case and opportunity vs cost.
You want to become a solopreneur. But before you leave your job, you need to know: can I make a sustainable living at this?
All three situations are asking the same question:
Is this idea worth the investment?
A business plan helps you answer this and is an effective way to communicate your vision for something that you want to build. It paints a picture of the problem and proposed solution, the opportunity, and what it will take to make the idea a reality. It’s purpose is to secure resources like money, people, approval, or buy-in.
Most business plans will include:
Market trends and opportunity
The problem and proposed product or service
Competitors and how this product is different
How the product or service will reach customers
Resources, partners, and suppliers needed
Pricing and expected revenue
Expected costs
A business plan combines both story and data. The story explains why the problem is worth solving, why this idea is different, and why customers might choose it. The data outlines: the size of the opportunity, expected revenue, and expected costs.
No matter how compelling the story is, the investment decision ultimately comes down to these numbers. And each number depends on several assumptions that deserve close examination - whether you’re writing the business plan or evaluating someone else’s.
Let’s dive into each key number and the common assumptions to focus on.
#1 | How big is this opportunity?
The first number in a business plan sizes the potential market for this proposed product or service. This will feed the revenue estimate later, so it needs to be credible.
Base your estimate on credible external data. You may need to combine several sources and make reasonable assumptions, but document where the numbers came from and why you trust them.
Investors don’t expect certainty; they expect a well-supported estimate of the opportunity.
Look for information on:
Market size, market growth rates, and forces driving that growth
Market structure, including the number and type of potential customers
Competitors and current market share, when available
Pressure-test the assumptions:
Does the market definition match the geography and customer segment(s)?
Is the data recent enough for a fast-changing industry?
Are growth estimates based on an established trend?
Does the analysis include substitute products, not just direct competitors?
How credible are the sources for the market sizing estimate?
#2 | What is the expected revenue?
The potential revenue, how it builds over time, and the underlying assumptions will get much deserved scrutiny from potential investors.
At its simplest, the revenue forecast depends on three things:
The average price customers will actually pay
The number of customers you expect to win
How both change over time
Start with pricing: Use the average amount you realistically expect to collect, accounting for promotions, discounts, pilot pricing, or special terms.
Then estimate how many customers you can realistically win and how quickly. This is where many business plans get overly optimistic. A common shortcut is: “If we capture just 1% of the market…”
Be careful!
Even 1% of a large market can mean winning hundreds of customers, often from established competitors. Your forecast needs to reflect how long that will take and what it will require.
How much will customers pay, and how many customers can you realistically win? And by when?
Build your estimate from the bottom up. How will you win your first 10 customers? Your first 100? What changes as you scale? Use customer interviews, pilot results, comparable businesses, or sales capacity to support those assumptions. Then test a more conservative scenario.
Every assumption should be visible to the reader. Document it and include any sources you used.
Look for evidence that your customer estimates are realistic. This could come from customer interviews, early sales or pilot results, comparable businesses or competitive channels, or the capacity of your sales and marketing channels.
Pressure-test your assumptions:
Pricing - Will customers pay what you expect, including any discounts and promotions?
Customer growth - How many customers can you realistically win, and how quickly?
Sale - How long does it take to go from initial customer interest to a sale?
Retention - How many customers will stay, and will their spending change over time?
Evidence - What data or experience supports these assumptions?
#3 | Expected costs
Revenue gets a lot of attention, but costs determine whether the idea can survive.
Costs are easiest to evaluate when you think of them in buckets:
Startup costs: one-time expenses required to get your business up and running such as legal setup, equipment, initial inventory, or website development.
Operating expenses: ongoing costs of running the business, such as rent, software, insurance, marketing and administrative labor.
Cost of goods sold: direct costs of producing the product or delivering the service, such as materials, manufacturing, and labor related to production.
If you are an entrepreneur, do not forget to include your own time.
And unless you have a strong financial background, it is worth talking to an accountant to help build the model or at least review the cost categories. A small investment in advice can prevent a much larger mistake.
Pressure-test your assumptions:
Which costs rise with sales, and which stay fixed?
What new costs or investments will be required as the business grows?
Does the business still work if costs are higher than expected?
Using AI: The point is the model
A business plan is not just a document you use to convince someone else to give you money, people, or support. Before it does any of that, it is a tool for you.
The model helps you work through the ranges and assumptions behind the opportunity. Is the potential audience large enough? Is the pricing strong enough? How quickly could revenue grow? How much will it cost to deliver and scale?
A good model will help you understand what must be true for the business or product to be viable.
Where AI fits and where it doesn’t
Use AI to research industries, competitors, customer pain points, production methods, and potential costs. But don’t let it build the model for you. Creating the assumptions is part of the thinking. Once you have a model, AI is valuable for challenging assumptions, identifying missing risks or costs, and suggesting questions an investor might ask.
Bottom Line
A business plan is one of the best ways to pressure-test an idea before investing significant time, money, and energy.
Building the supporting model forces you to think through what must be true for the business to succeed - and often improves the idea in the process.
Next up in this series on using data to estimate the future: strategic plans.
And in case you missed earlier installments,
Business Plans
Coming Soon: Strategic Plans
Coming Soon: Budgets
More reading: Critically evaluate and communicate with data
There's something important about modelling here. The spreadsheet isn't just about producing an answer. The process of building it forces you to decide what you believe about the business.
How customers behave. What growth depends on. Where costs emerge. What has to remain true.
Hand that process to AI too early and you may get a "better" model while understanding your business less.
Use AI to challenge your assumptions, but don't outsource the very process that makes them visible.
The story creates confidence in the vision. The financial model tests whether that vision can become a sustainable business.