Fans of the Fox television series “House,” a medical drama starring cynical but effective Dr. Gregory House, will recognize his catchphrase, “Everybody lies.” Like other good one-liners, it rings true beyond its original context. One area where it has particular resonance for me is in sales forecasting.
Sales forecasting is serious business. Financial markets expect public companies to deliver a smooth revenue ramp. A missed sales forecast carries dire consequences. Wall Street will punish “your miss” by hammering your company’s stock. Of course, enterprises need to get their sales forecasts right for their own reasons. If done well, a sales forecast helps assure that there is sufficient capacity to process orders and ship products on time. Get that wrong and you’re saddled with either expensive inventory or lost sales.
Extrapolation versus forecasting
Forecasting remains more of an art than a science. Even in large companies, sales forecasts are often based on the opinions of individual sales reps. Therein lies a problem. Only rarely do reps know without a doubt whether a particular deal will close in the designated time frame. There is a great deal of unpredictability that accompanies the purchase of consumer goods, and it’s worse in sales to businesses. Most business-to-business transactions involve multiple influential decision makers and a decision process in which group dynamics play an important part. Under those circumstances, a sales rep’s capacity to predict an outcome is often not much better than relying on the law of averages.
A good substitute for individual deal forecasting is extrapolation. Something like, “Last quarter, I had $1 million worth of opportunities and $500,000 came in. This quarter, I have $1.2 million worth of opportunities so, hmm, let’s say $600,000 will be the forecast.”
Hopefully, if you have 100 sales reps, the statistics all come out in the wash. But the sad fact is, statistics are only as good as the data on which they are based. Follow them blindly and the result will be no better than a simple guess.
Sales managers: Get involved
Companies are under tremendous pressure to meet their sales targets. This pressure gets transmitted directly to the sales force in the shape of both the carrot of huge commissions and the stick of dismissal. The thinking is that this approach will lead to better forecasts. However, this is not the case. In particular, the threat of termination, coupled with the inherent uncertainty of forecasting, turns what should be a tightly controlled and transparent business process into an opaque game of hide-and-seek.
The problem is that if sales reps were to forecast anything less than say, 70 percent of their quota, they would put themselves at risk of being terminated. On the other hand, if reps forecast numbers over 130 percent, they risk having their territory reduced. So, it should be no huge surprise that all reps feel the need to forecast in a tight range, along the lines of 80 to 110 percent of quota. Everybody lies.
Over-allocating quota is common practice
Experienced sales vice presidents understand this and attempt to compensate by over-allocating quota. This way, at each level in the sales management chain, you can still commit to 100 percent-even with your reps committing an average of 95 percent all the way up to the executive suite. Most of the time, this method makes the numbers balance out.
In this scenario, it is the sales manager’s job to peer through all the fog and try to build a picture of which deals are really likely to happen and which are not. This will be done via a process of cross-examination: “Do you know the name of the decision maker?” “When was the last time you visited the customer?” “Show me the most recent e-mail reply from the prospect.” “Can you set up a meeting for me to meet with the customer?” The cycle repeats itself, since the same logic forces the sales manager into delivering a forecast bounded to 80 to 110 percent of quota to his or her immediate superior, and so forth, all the way to the top.
Why SFA Doesnt Work, and What Does
Sales force automation: a good idea that doesn’t work
Hopefully, it is now clear that sales forecasting is not an exercise in tabulation. It is more like an exercise in psychology and political maneuvering to which no software can add any value.
Unfortunately, this was not something that was given much consideration when SFA (sales force automation) first came to market. Siebel’s original sales pitches played to a deep-seated longing by the vice president of sales for a full automation of this onerous forecasting process, with a system that would cut out the middle management and instead roll up every individual forecast into a companywide forecast, an ??ber-dashboard. All a VP of sales would need to do is sit behind a mahogany desk and monitor a display showing a needle inexorably moving toward “goal.” With omniscience would come omnipotence, quotas would be met, and all would be well with the world.
The dream proved elusive
First, aggregating many small piles of rubbish just creates a big pile of rubbish, not a forecast. Second, sales reps know that their most precious resource is time, so no self-respecting sales rep is going to spend an hour per day typing updates in the system-particularly one as onerous as the early Siebel system. The rainmakers simply refused (and had the clout not to be called to account). The midlevel players took their cue from the rainmakers, which only left the struggling sales reps to fill in the multiple fields, in the hope that their servitude would buy another quarter of employment.
Siebel was aware of this. I recall a particular presentation where the speakers advised my company that, for success, one must take up the spirit of Fernando Cortez, who conquered Mexico in 1518 and ordered his men to burn their ships. This sent a message that there was no turning back. Siebel understood that implementation would be far from straightforward, so it adopted a “call to arms” mentality that would not brook compromise. Over time, statistics bore out the company’s trepidation, as SFA became a watchword for disaster-with project failure rates in excess of 50 percent.
An exercise in management communication
In recent years, things have gotten better. First, CRM has moved to a SAAS (software as a service) delivery model. With instant user provisioning and annual subscriptions, the hassles of setup have been diminished and success rates are much improved. Current systems present a much more user-friendly environment, which makes it more efficient for the user.
Equally important, many organizations are giving up on the pipe dream of forecasting as an automated process, and are accepting it for what it really is: an exercise in management communication.
Select SAAS over on-premises CRMsolutions
What is notable is that Salesforce.com, the market leader, focuses its messaging not on forecasting, but on the bread-and-butter customer database as its core value proposition. What is probably most important for the success of Salesforce.com is that it is a true SAAS company. With that comes a host of business model advantages that put it in a better position than on-premises solutions.
The reason why I am optimistic about SAAS is that the transparency and immediacy mean it’s not possible for an unused, or even onerous, application to survive more than a billing cycle. Sure there will be mistakes, but these will be quickly rectified.
The problem with on-premises CRM is that this is not the case. Projects get tied up in implementation, or users will boycott the system because it is so onerous. Nevertheless, the system survives for years. Many companies really did follow the advice of Fernando Cortez and ploughed on regardless. Doubling down, their prize was not Mexico, but the biggest slump in IT spending in recent times.
Joe Ruck is President and CEO of BoardVantage. He has led many high-technology companies through successful growth to IPO or acquisition. Prior to joining BoardVantage, Joe was senior vice president of marketing at Interwoven and part of the team that drove the company through one of the most successful IPOs of 1999. Previously, he held sales, marketing and executive positions at Sun Microsystems, Network Appliance and Genesys Telecommunications (subsequently acquired by Alcatel).
Joe holds a B.S. in engineering from Oregon State University and an MBA from Santa Clara University. He can be reached at firstname.lastname@example.org.