For years I’ve been amazed by the number of very smart sales people and leaders who have a blind spot in forecasting with Salesforce.com. One of the top issues CEO’s, CFO’s, and even Chief Sales Officers have is forecast accuracy. One of the most used forecasting methodologies based on a “weighted revenue” approach.
This approach takes the sum of all opportunities in the pipeline, multiplying the revenue for each opportunity by a probability factor. This makes sense statistically, it’s called expected revenue. For example, if you have a $100,000 sale and a 70% probability, the expected value of the sale is $70K — we know this from statistics. So what’s the problem?
It’s Not Salesforce’s fault
The root of the problem is really in the way most organizations assess the probability factor. For most organizations, the probability assigned is based on where you are in the sales process. For example, if you have qualified the opportunity, you might have a 25% probability; after you have completed discovery, you have 50%; after you have submitted a proposal, you have 75%; and after you have closed, you have 100%. Makes sense, as you go through the sales process, presumably you are improving your chances of winning the business. All perfectly logical—all perfectly meaningless. Yet, Salesforce.com, in fact, virtually every forecasting methodology relies on this approach.
Now you say, “So, who are you to say this is meaningless, after all it’s been the cornerstone of our forecasting systems for years. How could all these smart people be so wrong?” Well, I really don’t know the answer to this, but it is still perfectly meaningless. The way we assign the probability factor is completely wrong. At best, we are measuring progress through the sales cycle (though I tend to doubt this), but we aren’t measuring the likelihood of a customer making a decision to choose our solution over the competition.
Consider this argument
Let’s assume we are competing against two other companies. Each company uses Salesforce.com, and they haven’t modified the “out of the box defaults. All assign probabilities based on progress through the sales process. Let’s assume we’re all completing our proposals to the customers and Salesforce.com tells us that we are now at a 75% probability of winning this $1 Million deal. Each of us (we and our 2 competitors) are committing to our managers and they are committing to their managers the expected value of the deal at $750,000—we are all saying that we have a 75% probability of winning. Now I have to admit, I struggled through freshman statistics, but I did learn that 3 competitors can’t each forecast a 75% probability of winning a single event. I learned that, if it was evenly weighted, each had a 33.33333% chance of winning. I learned the sum of all the probabilities could never be over 1 or 100%.
Many sales executives call me asking for help in improving sales performance. We talk about lots of things, I generally ask to look at their sales process and pipelines. I see they are using the same methodology (let’s stick with our 25-50-75-100% example–you can substitute your own numbers if you want). At some point in our conversation they say, we aren’t winning enough business. I generally ask, “What’s your win rate—what percentage of the proposals you submit do you win?” They are always embarrassed, they always say, it’s too low–I push for an answer, they give me a number. It might be 60%, it might be 50%, or it might be 40%. Generally, I believe them, even if it is just a “feeling” they have. The point, however, they are using a 75% win rate at the way they are forecasting to the business. See, if their Salesforce.com says their weighting factor for all proposals presented is 75%–implicitly they are saying, “We win 75% of the opportunities we submit proposals on.”
And here’s another…
Let me use one final example to show how meaningless this approach is, at the same time providing clues for an alternative approach that is more relevant. Let’s say we are pursuing two different sales opportunities. With both, we have completed proposals, both for $100K. One is with a long time customer. This customer likes us a lot, we are bidding a capacity upgrade–one that he really needs, one he has budget for and had planned spending the money. There are no problems, the customer has said he wants to do business with us. The second is with a prospect we have never done business with–well we did years ago, until we made him so unhappy that he chose our competitor in the last deal. He reluctantly agreed to let us propose, though he far favors the competition. Our solution doesn’t provide the performance levels of the competition and we are only 25% more expensive than the competitor he is currently doing business with. Our forecasting system would require us to forecast both of those at the same probability–75%–or expected revenue of 75K for each opportunity. On paper, both look exactly the same, and exactly as likely to produce business.
But in reality, we know the probability of winning the first deal is significantly higher than that of the second deal. We have a justified solution that fits the customer requirements better than any others, and a customer that is very biased to doing business with us. In the second case, we have everything going against us–at least from a customer perspective. Yet our “weighting” process causes us to look at these as the same, presenting the same likelihood of winning the business to management and others. This forecast, because it is so late in the cycle (after all we are 75% of the way through) sets all sorts of wheels in motion. Procurement may be starting to buy parts for both sales, manufacturing might be scheduling the products into their manufacturing cycle, the CEO is presenting these shareholders as pieces of business we are likely to book—-OK, I went off the deep end and exaggerated a little, but you get the point.
In reality, most sales people would probably say we are only going to win the first one and are highly unlikely to win the second deal. Most sales people would “assign” a very high probability to the first deal and a low one to the second deal. Their rationale would take into account things like the solution fit, the urgency of the customer, the business justification, the past relationship with the customer, and several other factors—things that are relevant to how customers make decisions, not based how far we are through the sales process.
The Fatal Flaw
This is the fatal flaw with the way we assign probabilities and do weighting currently. We make an assignment, virtually independent of any consideration of what the customer thinks of our competition and us. Instead, we use an artificial measure of what activities we have completed–regardless of whether they have had a positive or negative impact on the customer’s perception of us.
It’s no wonder why our forecasting is so poor, we are using criteria that are irrelevant to the customer and the decision they are making. Yet virtually every organization I have encountered has used this approach in their forecasting, and sadly, Salesforce.com, out of the box, encourages the same strategic error in the way they have set up their systems. The approach and the metric is not only meaningless, it is misleading.
It’s time we change the approach to assigning probabilities and weighting our forecasts. Weighted forecasting can be very good, but it has to be built on valid assumptions and strong foundations. What if we changed the way we looked are assigning probabilities to consider things like urgency of customer need, our solution fit, the business justification, our current and past relationships with the account, the process the customer will use to make a buying decision or several other things. If we considered these, we’d have a much more accurate view of what our business will be–opportunity by opportunity and across the entire pipeline. We’d have a set of numbers, our management team would have more confidence in, and that we believe we can deliver.
It’s an easy shift that can have a profound impact. I’ve touched on only a few items here, but the real secrets are in a short white paper, Forecasting—Beyond The Crystal Ball, Increasing Your Odds Of Winning. Send me an email firstname.lastname@example.org with your name and conact information. Ask me, “How can I increase my odds of winning?” I’d be delighted to send you the white paper.
Article originally published by David Brock on July 16th, 2010. Dave is President and CEO of Partners In EXCELLENCE, a global consulting company focused on Sales Performance Excellence. Partners In EXCELLENCE works with it’s clients to help assure they achieve the highest levels of sales performance anc value creation. Follow Dave’s blog: Making A Difference or contact Dave at email@example.com or phone him at +1-949-305-7146.
SalesForce Training & Consulting is a professional coaching and training firm that specializes in helping companies navigate their way in a Salesforce.com environment. SalesForce Training is based in Toronto, with trainers in Boston and Chicago, providing sales coaching, sales management consulting, Salesforce.com training and Salesforce.com Admin support, sales training and sales personnel assessments.