Sales operations leaders typically set sales quota based on historical performance, and a rough estimate of expected incremental growth. More advanced approaches might also utilize some factored value from each person’s sales funnel. Add to these basic approaches a little bit of stretch goal (because we all know those sales guys are sandbagging us), and voila: sales quotas. It’s a disarmingly crude approach.
But sales operations practitioners rarely characterize the quota setting process in such simple terms – especially when describing it to sales leadership or the sales force. It’s more likely described as a state of the art algorithm combining sales information from a reliable CRM system, a vast store of historical data and extensive market knowledge. Sounds pretty good huh? Few challenge this – Sales Operations is, after all, “experts” in quota setting, and understand better than anyone else the complex mix of data required for setting quotas. After all who else can do better?
The truth is, even crude quota setting approaches usually work pretty well; most of the sales team falls within 10% or 15% of the assigned quota. The problem is, quota setting methodologies that rely heavily on historical performance fail to recognize the inherent inequities in sales territories. For example, the sales person in an opportunity-rich territory may be bringing in big numbers but is actually grossly underperforming based on the enormous additional opportunity that is available. Or the chronic low performer who is actually overachieving in an opportunity-poor territory. Your superstar may not be such a star; your dud might actually be one of your best people!
So what’s a sales operations person to do? The answer lies in quotas based on objectively defined market opportunity. If you are a Fortune 500 company, or active in a mature industry, you probably have access to decent market data on real sales opportunities in each territory. In most cases your biggest challenge will be finding out who owns the data and how to make sense of it. If (like me) you work in a smaller organization you may have to get creative. I’ve used third-party data providers like Hoovers, InsideView, and Jigsaw; all can provide customer data based on industry and location. When you do find valid data to work with, don’t go overboard – simply search on an industry and see how many potential targets are in each territory. If there are half as many targets in your poor performers’ territories or twice as many in your high performers’ territories, you’re likely on to something. Depending on your business you may also have access to industry-specific data through publications, user groups or trade associations. Often you are already paying for these services but not really utilizing them so make sure you take full advantage!
One last word of caution: if after doing all your research you decide to challenge the status quo, be prepared! It is very counter intuitive to suddenly learn you stars don’t measure up or that your low performers may really be doing a pretty good job. Be prepared to even be challenged personally; you’re likely to be asked “Why are you telling us this now?” or “Why didn’t you tell us this before?” Though introducing market opportunity into the quota setting process can be painful, it represents best practice and the most effective approach for allocating goals. For Sales Operations departments stuck using historical performance, making the change to market based quotas provides an opportunity to demonstrate value and drive higher performance.