The Power of Forecasting

A big part of my job is helping startups take a great idea
and turn it into a viable business. In that role there are few tools I use as
often as financial forecasting or modeling. Mention financial forecasting and
most people just glaze over. Worse, many business owners never see the need for
building a financial forecast. They will establish sales targets and cost
budgets but going that extra step to build a comprehensive financial model is
seen as so much black magic reserved for SBA loan analysts and venture capital
gurus.

Another area often confused with financial modeling and
forecasting is business plans. You can jump online and find dozens of companies
willing to build a business plan for you, even though they know nothing about
your business. Don’t get me wrong I think a well written business plan is a
great asset. The problem is that most of them are a bunch of pie in the sky
narrative fluff that’s worth less than the paper it’s printed on. The fact that
SBA loans and soft credit lines are approved on the basis of these things is stupefying.

So what does a good forecast look like? It depends. I’m a
strong believer in customized solutions and for that reason forecasts often key
on different areas depending on the user’s needs or concerns. For instance,
startups are most concerned about the capital it will take to get an idea off
the ground. Investors in expanding businesses want to see forecasts of ROI and
payback periods. Banks are often looking for net margins and ratios compared against
industry norms. Each of these requires a different format, but they all have a
fundamental process in common. Every forecast has two basic elements.

1. An
analysis of currently available facts.

2. A
prediction of future events and conditions.

A model heavy on analysis with little or no focus on future
events is just a rehashing of what has already happened. By the same token a
prediction with no analysis or basis in facts is just hot air. To build a
meaningful, relevant forecast you must have both.

The first step I take when building a model is to understand
the source of revenue. What generates sales, what is the pricing rationale, is
it supported by current market conditions, what is the market size, are
assumptions about penetration or market capture reasonable….and on and on and
on. Building a good model involves questioning every assumption about revenue.
Closely associated with this, but not nearly as difficult is estimating the
cost of producing those revenues. These are the direct costs or cost of sales. How
much raw material and labor are required or how much will the product cost to
purchase from someone else?

The second step is to estimate the fixed costs of the
business. This requires leg work. If you assume $5,000 per month for rent where
is the space located, who did you talk to, is this a negotiated rate or an
initial offer from the landlord, is it a triple net or all inclusive lease, is
there an escalation clause, when was the last time CAM charges increased, etc,
etc. In a good model every expense is questioned, attacked and ultimately justified
on the basis of facts, not guesses.

It goes without saying that models are a lot of hard work
and can be expensive to build when you hire someone who knows what they’re
doing. The alternative, however, is to start spending your own money with only
a foggy notion of the eventual outcome. To most people that doesn’t sound like
a very smart way to do business.

View the Axiom Professional Group, P.A. web site  or return to the Axiom web site articles page (both links will exit the blog site).