Your Numbers Might Be Off A Bit

By August 17, 2010Finance

This is the seventh post in a series about selling with Finance, the Universal Language of Business.


The examples used throughout this series of “Selling With Finance” posts show a five year time horizon.  Does anyone actually think a financial projection stretching out that far could possibly be accurate?  Frankly, even financial professionals find making accurate one-year forecasts to be a challenge.  As sales reps, therefore, we need to be careful about implications regarding precision.

Fortunately, there’s a very simple technique that can further polish your image as a financially savvy rep, generate more conversations regarding your recommendations (which crowd out customer time wasted on conversations about your competitors) and create yet more differentiation.  Just multiply your financial analysis by three.

To illustrate, consider one of the sets of numbers from Part 2.  The post doesn’t explicitly say so, but the following chart shows the “Most Likely” scenario that will result from following your recommendations.

“Multiply by three” means create not one, but three scenarios.

  • Worst Case
  • Best Case
  • Most Likely Case

Think of it this way…  Assume one of the expense items in the analysis is contracting for professional services, and right now it’s $100K annually.  It would be reasonable to use $100K for each of years 1 through 5 in the Best Case.  In other words, holding that expense steady is the best that can happen.  It would also be reasonable to assume at most a 5% annual increase.  In other words, I’ll use $100K, $105K,$110K,$116K and $122K for my Worst Case.  Most Likely falls somewhere in between.

Bracketing the highs and the lows has very powerful intuitive appeal.  Think about the difference between the following value propositions:

  1. The team’s analysis shows an Internal Rate of Return of 67% for the recommended investment
  2. The team’s analysis shows a worst case IRR of 59% for the recommended investment.  Best case is 74%, and 67% is most likely

Doesn’t it seem like a LOT more work went into the detailed analysis for the 2nd?  You get a sense of thoroughness and rigor from it, don’t you?  It also conveys the fact that living, breathing humans are behind all numbers doesn’t it?

All true except for the “lot more work” part.  The hard part is building the spreadsheet model.  After that it’s only a matter of plugging in different numbers.

How are you doing with your Universal Language of Business lessons?

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