A lot of companies manage quota out of a spread sheet. They will collect some market data for what similar companies assign for quota, look at the revenue targets they want to hit for the year, and do some basic math to determine how many sales people to hire.
Lets walk through an example. Say industry average quota is $750,000 Annual Recurring Revenue (ARR) per sales person. If the company wants add $6 million in new ARR, 8 sales people carrying $750,000 will get them to the number. But, most companies assume that some reps will not get to 100% of their quota. To account for this, the model adds a buffer to get to $6 million. If every sales person reaches 80% of their quota, they will sell only $600,000 ARR. This means you need 10 sales people instead of 8 to be “assured” of reaching the $6 million target.
Mathematically this all makes sense but the model has some major flaws and is potentially setting the company up for major attrition from the sales team.
A large gap between frontline quota and management quota creates a culture problem. When senior leaders hit their targets but frontline sales people do not, resentment and distrust will start to emerge. The bigger the gap, the less skin in the game leadership has with sales people.
In the example, our company selects individual quota based on industry average. Again, this sounds well and good, but what if your product has an average selling price of $10,000? Is it realistic for a sales person at your company to sell 75 deals in one year? What about win rate and demand? If you win 1 in 4 deals and need to close 75 deals, you will need 300 deals in your pipeline. Is it reasonable to add 300 deals per sales person? Is there enough demand? Where is that pipeline coming from?
Sales people tend to be financially driven, and while great on target earning (OTE) packages can be enticing, the astute sales person cares most about how realistic it is to hit their quota. You could be paying the highest salary and commission packages in the market, but if quotas don’t match the market realities of the business, sales people will leave in droves.
The last piece of the puzzle is collective quota. When companies pick ARR targets and reverse engineer head count, they commit the same errors as when they use comparable companies to set individual quota.
Multiple data points are needed to produce a three dimensional view of a realistic target. What did the company do the prior year? How much demand are we generating in marketing? How does our product perform against competitors? Do we have major product releases or pricing changes this year? Each of these questions will give data points that should inform company ARR targets.
In sum, best practice for setting quotas is to start with what you did last year, gather information to determine what % increase to last years performance is possible, and then stretch a bit beyond that. Once done, determine individual sales person quota based on win rate, average deal size, sales velocity, and pipeline generation. When all of these factors align, you can finally reverse engineer headcount for the next year.
Taking the time to get quota and compensation right will save you a lot of headache recruiting, interviewing, and onboarding backfills for sales people that leave your company in search of greener pastures. This is a foundational block in building a scalable sales & marketing engine.
The Ferment 