Business Plan Math: The Numbers You Need to Grow

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Business Plan Math: The Numbers You Need to Grow

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Money In

My 26 Sep 2013 blog outlined my views on the importance of “doing the math” on any kind of deal, and especially in sizing up a plan or proposal for a new business venture, product addition, or expansion.  I’m now accustomed to looking at four sets of numbers in a business plan: [1] the $ that go “IN” (investment) [2] the profit and cash that come “OUT” [3] the timetable for each of these, and [4] the decisions that drive the numbers.   These are not mutually exclusive as each is influenced by the others.  For today, here are my views on $ IN.

My experience is that most business plans are done with fingers crossed.  The costly stuff (investment and time) are underestimated, and the fun stuff (profit and cash flow) are overestimated.  Here’s what we typically see:

  • Investment: 1/3 to 1/2 of what is realistically needed
  • Results: 2X the profit and cash flow in about 1/2 the time required

This is not a bad place to be in to start with.  It is human nature – and the strength of the entrepreneurial spirit – to see the rose among the thorns.  That is what the pros (advisors, VCs, professional investors, etc.) are there for: to apply their experience and know-how to more accurately see what the real picture is likely to resemble.

In my experience, there are two reasons business plans are over-optimistic: inadequate facts and benevolent assumptions

  • Hard facts and evidence – those that sing the truth because they are relevant, valid, reliable and verifiable – are the cornerstone of any good business plan.  Good facts (the hard kind) can be difficult to find.  We need to dig.  Sometimes the facts we find joyously support the outcome we seek.  At other times we come across facts that imply a rather unpleasant truth.  Embracing the former, while casually dismissing the latter, is a surefire way to set off on a vacation and have the money run out with a week remaining.  A good plan needs both kinds of facts by showing:
    • how the favorable facts make the going easy
    • how the potential impact of the unfavorable facts can be mitigated held at bay
  • Benevolent assumptions are akin to our own body image.  With few exceptions, we tend to see ourselves closer to college weight than our real weight.  Dress sizes for women, and waist sizes on men’s pants have in fact not shrunk over the past 20 years.  We like to see the glass half full.  I often see that in the face of not finding hard evidence – or, worse, finding unpleasant evidence and sweeping it under a carpet – opt for framing an assumption that is often 4 to 6 inches slimmer than the waist it must fit.

The good news is that there are two principles which, when conscientiously applied, result in business plans that are much closer to reality and, as a result, more attractive to potential investors.

  1. Margin of safety Simply put, none of us can predict future events with much certainty – especially not complex business events.  One of Warren Buffet’s firmly held investment principles is the margin of safety – he is not infallible and must allow for error, so he builds in a cushion.  Drawing assumptions that are conservative – rather that reflect best imaginable conditions – are a sure way to avoid over-optimism.
  2. Devil’s advocacy:  A few episodes of Shark Tank will give anyone a sense of how unpleasant it can be to have pros tear apart a business plan for heaving a weak foundation.  Short of appearing on the show, there is an alternative.  Identify someone you know, whose opinion you respect, and whom you consider tough.  Ask them to review your plan and do two things: [1] find solid yet unfavorable facts, and [2] tear apart your assumptions.  The more difficult time they have doing this, the more likely your plan is on a solid footing.  You may need 2 to 3 iterations (yes, these can be painful) to get there.

Money Out

Two things are certain about the time to achieve profitability (of a venture, product introduction, market expansion) and positive cash flow.  The longer it takes to achieve them (in my experience it ends up being longer than 95% of Rev 1 plans predict) the harder it is to attract capital in the beginning, and keep investor confidence along the way.    Anyone who has been in the position of having to explain to investors why a few more pages of the calendar must be flipped over before the light turns “green” knows what I mean.  It is painful, and can be debilitating.

In my experience, two principles tend to hold true  – not guaranteed, but generally typical – to avoid such pain:

  1. Under-promise and over-deliver: That is a big reason for the advice regarding $ IN, i.e. build a margin of safety and have a tightwad scrutinize your facts, numbers and assumptions.  I cannot recall an investor being upset with being ahead of plan (unless the plan was so conservative as to miss opportunity’s low-hanging fruit – a story for another day).
  2. Connect the dots between $ IN and $ OUT: The latter is a function of the former.  When a business plan is converted to a spreadsheet it is easy to lose sight of the forest for the trees.  A faithful, explainable and reconcilable relationship between input and output – and the time lag between them – is critical to ensuring that a plan has legs.  My advice: if your devil’s advocate from the first go-around did his/her job and held you to account for your facts and assumptions, give that same person your spreadsheet and ask them to do the same thing.  Don’t, however, provide them with a list of the underlying decisions that drove the numbers and the schedule.  If they are dong their job, their doubts and questions will speak to the underlying decisions.


This is pretty simple.  If you have taken care to follow the advice given regarding Investment $ IN and profit and positive cash flow $ OUT, you will have had no choice but to forecast the results against a dimension of time.  Such is the beauty of spreadsheets.

In doing so, the question becomes: what are the appropriate intervals of time – and long term horizon – to use?

My answer: that depends on the length of the selling cycle.  Unless you are selling aircraft or nuclear reactors, quarterly intervals are pretty much useless.  Annual intervals are useless.   They hide too much.  Typically, the shorter the time interval, the easier it is to scrutinize the inputs, outputs and decisions of a plan … and the more challenging it becomes to defend them.  But that is the whole point – soft testing with the jury of expert opinion rather than with precious capital.

My advice:

  • If your expected selling cycle is:
    • 60 – 180 days, use months
    • less than 60 days, use weeks
  • When in doubt or as a test of the soundness of your plan – use weeks.  Converting monthly intervals to weekly intervals is much more than adding 4X the number of columns.  Assessing your plan on weekly expenditures and returns will force a high level of scrutiny of the relationship between input and output.


It is not the numbers that drive a business plan.  It’s the decisions – production, marketing, sales, financing and operating decisions – that drive a plan.  A spreadsheet most certainly does not drive a  business plan – it merely models the interplay of the decisions.  Gauging the impact of changes to decision inputs (i.e. “what if we did more of this, or less of that?”) is easily done via spreadsheets.  It is easy to fall in love with a neatly organized and extensive spreadsheet – especially if revenue and margin exceed expenses, and leave a healthy profit.  The adage holds true, however: garbage in; garbage out.

A couple of years back I reviewed a 60-page business plan written by four MBA students from a prestigious business school to satisfy the requirements for completing their degree.  They prepared it for a small offshore software firm that, after 8 years in business, had yet to achieve $1 million revenue in its home market, and was seeking to enter the US.  And what a glorious plan it was!  In return for injecting $7.5 million in capital, within 5 years the firm would be cash positive within 24 months, achieve $55 million in revenue, and earn profits of 22% on revenue.

The plan was very detailed, with all the usual goodies in place – pricing, quota ramp for sales people, and all the typical spreadsheet entries one would expect.  Yet, there was one major problem with it.  It was very difficult – and in cases impossible – to connect the dots between the assumptions and facts the students had respectively made and collected, and the outputs that resulted from the decisions modeled in the spreadsheets.  This airplane was largely flying on faith, not fuel.

It took no more than a few weeks of market testing to determine that the plan was neither realistic nor feasible.   However, the company’s investors had all purchased first class tickets on that airplane, and they did not want to hear that vacation plans might have to be curtailed.  Such is the problem when is sold on the bottom row that appears in a spreadsheet.

What would have made for a better plan?  What would have enabled the underpinnings of the plan to be better scrutinized?  Three things:

  1. A clear and separate articulation of the major decisions (those that drive revenue, cost, expense and productivity) and the underlying basis (research, facts and assumptions) for making those decisions.
  2. A quantitative modeling of each decision, i.e. the relationship between input (typically a cost item), output (typically revenue or productivity) and timeframe (the rate at which the output responds to a change in input)
  3. A clear listing of interdependencies, e.g. the impact of specific marketing activities on sales productivity.

In my experience, there are rarely more than a handful of “key” decisions – those that really make a difference.  It is easier – and safer – to visualize them collectively on a single page than to start pulling together lengthy spreadsheets.  A simple table does the trick.

  1. List each key decision in the left-hand column
  2. Beside each label five columns:
    • “Why” – list the evidence supporting the decision
    • “How” – specify how the decision will be implemented and put in motion
    • “How much” – quantitatively describe the expected impact – or range – on outputs and results
    • “When” – similarly list the corresponding timeframe(s) to see those effects
    • “Dependencies” – list any other decisions or assumption which, if altered, will appreciably affect anything appearing in the previous four columns

Just attempting to complete the table is a task in itself as anything “shaky” usually becomes apparent.  It’s a pretty good test.  If you can get things to work and make sense at this level, you’ll not only be able to build a spreadsheet, but you – and others – will know exactly what has gone into the mix.

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Written by Michael

Michael Douglas has held senior positions in sales, marketing and general management since 1980, and spent 20 years at Sun Microsystems, most recently as VP, Global Marketing. His experience includes start-ups, mid-market and enterprises. He's currently VP Enterprise Go-to-Market for NVIDIA.

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