Comments on: Sales Forecasting Accuracy http://www.feld.com/wp/archives/2006/06/sales-forecasting-accuracy.html Mon, 13 Feb 2012 23:12:00 +0000 hourly 1 http://wordpress.org/?v=3.3.1 By: P. Roales http://www.feld.com/wp/archives/2006/06/sales-forecasting-accuracy.html/comment-page-1#comment-3223 P. Roales Sat, 01 Jul 2006 00:43:30 +0000 http://www.feld.com/wp/?p=1122#comment-3223 A good counterpoint to Harverd Business Review's current issue focusing on Sales. Good Post. A good counterpoint to Harverd Business Review’s current issue focusing on Sales. Good Post.

]]> By: PaulSweeney http://www.feld.com/wp/archives/2006/06/sales-forecasting-accuracy.html/comment-page-1#comment-3222 PaulSweeney Fri, 30 Jun 2006 22:54:15 +0000 http://www.feld.com/wp/?p=1122#comment-3222 Perhaps it would be instructive to hear about those "ah-ha" moments when you knew that the process was showing up other underlying issues? Perhaps it would be instructive to hear about those “ah-ha” moments when you knew that the process was showing up other underlying issues?

]]> By: Jim Pollock http://www.feld.com/wp/archives/2006/06/sales-forecasting-accuracy.html/comment-page-1#comment-3221 Jim Pollock Fri, 30 Jun 2006 21:38:56 +0000 http://www.feld.com/wp/?p=1122#comment-3221 "Just say NO" is exactly the right action to the specific example Will uses of multiplying the "stage of the order" by the order size. That is a case of taking two perfectly good numbers and RUINING them by doing the unnatural act of multiplying them and applying the wrong definition to the result. Every company I have been with from Hewlett-Packard to mid-size to startups has tried to come up with a method of forecasting. And for darn good reasons, as Will points out. The "best" I have seen and used TRIES to take into account the "gut feel" that a sales person has for a deal and the account. The parameters we captured was the order-size, percent chance that the order would be placed at all, percent chance that MY company would get it (competition), and the month expected. The 1st percentage boils into a single number the sales person's gut feel for knowledge of the customer, buying habits, funding, and stage of the deal. Much more information than simply the stage of the deal. The 2nd percentage represents the compeition. So, a typical deal would be reflected as: Company A $100K 90% 50% 8 Meaning a $100K deal that I have 90% confidence will be ordered and I have 50% confidence that I'll beat the competitors. And, knowing my customer and everything else, I think it will book in August (month 8) The trick is in interpreting these numers. Each number provides a valuable piece of information. And if multiplied together and THOUGHTFULLY reviewed, gives you interesting insight. This information for one sales person and one deal is WRONG. Either a 100K order will or will not be placed. A 45K order will not be placed. However, if I am working 10 deals, the sums start getting a bit more useful. If there are 50 reps with 10 deals each, even better. The tendencies of some reps being overly optimistic start merging with the overly conservative. You end up with numbers that CAREFULLY can be used to plan cashflow and production against. Weighted average sales forecasting can be an invaluable tool. You gotta capture info that reflects the right metrics, and only interpret what is possible to interpret. And, you gotta keep it simple enough that the sales team will use it. Put 40 metrics out there for each deal and you get ONE forecast in January. And that's it. Jim “Just say NO” is exactly the right action to the specific example Will uses of multiplying the “stage of the order” by the order size. That is a case of taking two perfectly good numbers and RUINING them by doing the unnatural act of multiplying them and applying the wrong definition to the result.

Every company I have been with from Hewlett-Packard to mid-size to startups has tried to come up with a method of forecasting. And for darn good reasons, as Will points out.

The “best” I have seen and used TRIES to take into account the “gut feel” that a sales person has for a deal and the account.

The parameters we captured was the order-size, percent chance that the order would be placed at all, percent chance that MY company would get it (competition), and the month expected.

The 1st percentage boils into a single number the sales person’s gut feel for knowledge of the customer, buying habits, funding, and stage of the deal. Much more information than simply the stage of the deal.

The 2nd percentage represents the compeition. So, a typical deal would be reflected as:

Company A $100K 90% 50% 8

Meaning a $100K deal that I have 90% confidence will be ordered and I have 50% confidence that I’ll beat the competitors. And, knowing my customer and everything else, I think it will book in August (month 8)
The trick is in interpreting these numers. Each number provides a valuable piece of information. And if multiplied together and THOUGHTFULLY reviewed, gives you interesting insight.

This information for one sales person and one deal is WRONG. Either a 100K order will or will not be placed. A 45K order will not be placed. However, if I am working 10 deals, the sums start getting a bit more useful. If there are 50 reps with 10 deals each, even better. The tendencies of some reps being overly optimistic start merging with the overly conservative.

You end up with numbers that CAREFULLY can be used to plan cashflow and production against.

Weighted average sales forecasting can be an invaluable tool. You gotta capture info that reflects the right metrics, and only interpret what is possible to interpret. And, you gotta keep it simple enough that the sales team will use it. Put 40 metrics out there for each deal and you get ONE forecast in January. And that’s it.

Jim

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