mercredi 30 juillet 2014

Weighted Pipelines And Forecasts

I have to admit, I’ve never been able to figure out the value or meaning of the weighted pipeline and forecast. It’s one of those things that is embedded in every CRM system, it’s one of those things that I see in all sorts of reports, but I have yet to figure out what it means.


I suppose the weighted pipeline is supposed to be some sort of indicator of overall pipeline health, but most processes for assessing probability are hugely flawed. Take a look at virtually every CRM system and the default methodology for determining probability. It’s based on where we are in our selling process. As we move from qualifying to discovering, to proposing, and finally to closing, our probabilities increase. So while we are measuring progress through the sales cycle (e.g. 25%, 50%, 75%….), we have no indication of the propensity to buy.


Sure, I’ve seen companies with sales processes that include increasing customer commitment as they progress an opportunity through the process, but most of these criteria are either loosely enforced or still don’t measure a customer propensity to buy—-just because a customer has committed to a demo or benchmark, just because they like our proposal, just because they say our proposal meets their requirements, or even if they say we are the preferred vendor, we don’t know the customer will buy or whether they will select our solution. The numbers become meaningless in terms of a commitment to buy.


Then anyone who remembers freshman statistics knows the sum of probabilities can’t exceed 1 (100%). That is, if we are competing against two other organizations, they are moving the same deal through their selling process–pretty soon each of the three competitors is in the closing process–each projecting a probability of something like 85% or more. Somehow, this doesn’t align with my understanding of statistics–if each is projecting 85% probability of winning, the aggregate is 255%????????


So as a pipeline measure, I’ve never really gotten it–what does 45%, 55%, 75% or whatever really mean? What does the aggregate of these weighted deals really mean? How does it tell me whether I have a sufficient number of opportunities in the pipeline? How does it tell me that there is sufficient flow or velocity in the pipeline? It seems to me, looking at the pipeline based on historical performance of winning/losing and sales cycle time give a much better indicator of pipeline/funnel health.


Then we move to the weighted forecast. What does it really mean to the business to say, “I have a $1 M deal that I’m projecting at a 75% level, so I’m committing $750K to the forecast.” If we win the deal, we’ll get $1M, so why are we forecasting $750K? What meaning does the 75% provide? When I sit down with people committing deals to the forecast, we review each deal. We talk about competitive positioning, the attitudes customers have toward our solution and the alternatives, the urgency of the need and business case, and a whole number of other things. Based on the assessment–deal by deal–we determine whether we are prepared to commit the deal to the forecast–and we commit $1M.


Some people think the weighted forecast gains greater weight in larger organizations. Frankly, I don’t buy that. Regardless the size of the organization, the forecast is a roll-up from first line managers. If you aren’t training and coaching managers, at all levels, in forecasting and pipeline management–then you have bigger problems than forecast accuracy. So the roll-up should have reasonable accuracy–naturally, each level of management is going to want to have serious discussions about the commitment to forecast.


In some organizations, particularly those with subscription businesses, run rate businesses, or something similar, analytics and trend analysis may provide a more accurate forecast. The base forecast may be based on these, with the forecast adjusted for major deals.


What do you think of weighted pipeline and forecasts? Where have you found them to be useful?






Weighted Pipelines And Forecasts

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