How to Build an Accurate Sales Forecast

I gave my two cents earlier this week on why sales and earnings forecasts fail.   They fail because of lack culture NOT because of lack of smarts.

Chris Waldron called out culture in his comment on the post.  I think Chris is right.

There are only 3 things needed to build an accurate forecast; data, interpretation and culture.  That’s it.

If building an accurate forecast is important to your business, start with building a culture of reality.  Reality is at the core.  An organization that confronts reality accepts what the information is telling them and plans accordingly.  There is no King James bible interpretation going on.  Their is no discarding of the data because someone doesn’t like it. It is what it is.  If the data is telling you business is going to slide, accept it, build an accurate forecast around it, figure out away to minimize and move on.

If forecasting is an exercise to support a predetermined number, it’s not forecasting and a culture of reality doesn’t exist.  Don’t waste anyones time, just give out the numbers and move on.

A culture of reality is critical to accurate forecasting.  Allowing the organization to accurately interpret the data to arrive at the most accurate representation of future revenue is key.

That brings us to the data.  I’m a gut guy, so this is hard for me.  However, I accept it and dig in.  An accurate forecast needs data.  It needs:

  1. Historical information
  2. Editorial dialog
  3. Customer data
  4. Competitive data
  5. Trend analysis
  6. Industry analysis
  7. Company data:
    1. Support analysis
    2. resource availability
    3. Product availability
    4. New product development
    5. New product availability
    6. Marketing plans
    7. Customer satisfaction
    8. etc
  8. Expected Macro Economic Data
    1. Consumer Spending
    2. GDP Growth
    3. Consumer Confidence
    4. Interest Rates
    5. Inflation
    6. Housing prices
    7. Government regulations/intervention
    8. etc

All of this info and more can influence the numbers.  Building a forecast without all the data, internal and external, marco and micro is a hollow effort.

Use the data, it’s the foundation.

If the culture is there and the data is there, interpretation is the special sauce.  It’s what differentiates the professionals from the amateurs.  Interpreting the data to create an accurate forecast is an art.  There is no science to it.  The best people I’ve ever seen can look at the data and with an amazing accuracy determine the impact to the forecast from the data.   It’s a little bit experience, it’s good data, it’s knowledge of their world and it’s a little bit gut.

I purposely chose not to be perscriptive in this post, because I don’t think forecasting is all that hard.  It’s only hard when the culture allowing for good ones doesn’t exist.  Build a culture of reality, get good data and learn to interpret it.  The forecast will come out fine — and by that I mean ACCURATE!

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  • http://www.partnersinexcellenceblog.com Dave Brock

    Nice article Jim. As you point out, there are two sides to forecasting, or what a call a process of developing “Informed Guesses.” The informed side is the data driven side. Past history, run rates, win rates with specific customers, win rates against specific competitors, much of the data you suggest help in developing informed data driven approach to forecasting. Depending on the business, this in itself can be very accurate. For example businesses in which there are very high number of transactions on a weekly, monthly, annual basis can develop very good models (and there are a lot of analytic tools that can help) Businesses that have far fewer transactions, where the business is lumpier, will have some challenge.

    The judgement side, or as you call it, the special sauce is where the greatest challenge is. This is where you tweak the data driven side up or down. The biggest challenge with this is the variability in the process–both between people involved and from period to period. Here it is critical to develop common processes, definitions, and standards to reduce this variability.

    Great articles–as usual!

  • http://twitter.com/bernardlunn bernardlunn

    The technique I use most naturally is to track the forecasting accuracy of individual sales executives. This is hard to do accurately without good systems support. But most sales managers know who is accurate and who is not. If Bob says $500k in Sept and his accuracy has been great, well then you can rely pretty well on that. If Fred has always been wildly optimistic you may discount the $800k he is forecasting quite steeply. And for Jim, the veteran sandbagger, you might even add something to his $300k. Methinks this is how enterprises work in practice ie the sales managers boss makes the same calculation on the sales manager and the CEO makes that same call on his direct reports.