When I have headed up sales, everyone would poke their head in my office and ask: “How we doing?” As the quarter progressed, these visits became more frequent, and it was often the boss coming by. Sometimes the CFO would come by and he often had his own spreadsheet or graph about “How we are doing?”
Every time this happened, other sales leaders and I gave evasive answers, and employed tactics that would move focus away from the question. Here are a few of the most interesting things we said: “We are doing fine, but the jury is still out”; “Looking good, but it all depends on the final month”; “It’s a challenge, but if we can just land X deal(s), we will be ok.” Any seasoned sales leader would then take an “urgent” call from a customer, and show the person asking the question out of their office before they ask for any real data.
It is incredible in a world driven by data, that we in sales leadership often do not have precise answers to “where we are in the quarter”. People are still reasonably tolerant of the myth that we cannot predict future sales, but they are increasingly miffed that sales leaders can’t give data driven answers to where we are in quarter based on actual closed deals to date. Our CRM tells us how much we have booked quarter to date, but it is harder to answer the question as to whether the number is good or bad. We’re still left to ask: “Are we ahead or behind where we need to be?”
We are often using amazingly simple data rules to measure this. We often have simple rules such as the 20/30/50 rule. This rule means that we will likely sell 20% of the number in month one, 30% in month two, and 50% in month three. The problem with the rule is that the numbers are often pulled out of thin air, and can only be applied at a macro level. But we know that enterprise markets tend to be more back end loaded, mid-market segments are less lumpy and SMB markets behave much different than other markets. We also know that seasonality is a factor, but our simple rules rarely capture that so we rely on old tribal knowledge like “Q1 is always light” or “Q4 is back loaded because of budget dumps” or “Europe sells nothing in the summer.”
In a data driven world, we can’t afford to not know exactly where we are. It’s simply unacceptable. We should be able to use algorithms to create accurate “deal pacing graphs at each level of our organization or product hierarchy so that we can give exact answer about where we are according to a data driven “pacing plan”.
The next time someone pops into your office to ask how the quarter is going, you should be able to answer in exact terms like: “We are 1.9% ahead of the expected closure pacing on a worldwide level.” You should be going into detail like: “We are performing ahead of pace to meet quota. This is being by secular strength in product line one, and business segment A. The strong performance in those sectors is offset by headwinds we are facing in product line 3 and below pacing performance in Europe, which we attribute to an unexpected weakness in Countries X and Y.”
That would be a lot better than the crap I have been saying to those casual drive-by visits to my office over the past 30 years. A lot better.