“I know my salespeople.”
On the surface this simple four word sentence sounds pretty innocuous, doesn’t it? It certainly doesn’t sound like something that should cause alarm.
But that’s exactly what it does for us. When our account leaders hear this from a sales manager that they are tasked with serving, we know that we are in for a bumpy start to our relationship. When we hear this during a sales call with prospective clients, we instantly know that our own sales job just got a lot harder.
We recognize that the nature of our company likely causes knee-jerk reactions for some managers. Our company systemically dissects companies’ sales data to find the most impactful drivers of success and failure in their sales organizations. Individual rep skills, tendencies and biases always factor into our calculus. Absent a deeper understanding of our mathematical approach and our mission to truly complement their skills as managers, natural defense mechanisms kick in for a few managers. For these managers, “I know my sales reps” is just a more dignified way of saying “Bugger off eggheads! I have worked hard to get my team this far and your team of math geeks will never know more about my reps than I do.”
We take no offense to the characterization and some managers quickly drop their defenses. Others dig their heels in.
Our technical output allows sales managers to see very clearly all of the factors that make individual opportunities more likely or less likely to close. The factors might include things like the price of the deal, a buyer’s history, the product or products being sold, age of the opportunity, velocity at which the deal progressed through various stages, activities, or engagement data that has been captured by other technologies. For tenured reps, the output is heavily influenced by the individual rep’s historical performance in each of the areas. It also includes a recorded history of how the rep feels about a deal’s likelihood to close.
We have come to learn that this last point – the rep’s feelings – are usually what sales managers are attaching to when they say “I know my salespeople.” Tenured managers develop this sense over time on their periodic pipeline reviews or forecast calls. After these calls, the manager will speak with a Sales V.P. and say things like:
“Bob is perpetually optimistic, so I am highly doubtful that he is going to land this whale.”
“Diane is a sandbagger. All her deals are showing that they are in early stages, but she always comes through in the end, so I will just put her at quota.”
“Ed’s committed deals never seem to be on time, but they always come in, so I will put half of them this month and half next month”
As it turns out, many of these managers are often directionally correct. So what’s the big deal then?
These generalizations, based on solid observations over time, in all likelihood will help achieve marginally better sales forecasts. Sales forecasting is an important component of many sales managers’ jobs. However, it is never the primary role for which managers were hired. Sales managers’ first responsibility must be to help drive sales for their organizations. We find that most managers who continue to express some form of “I know my salespeople” inhibit their own ability to drive sales.
Let’s use the above example of “Bob the Optimist” to illustrate this point:
For argument’s sake, let’s say that we can quantifiably prove that Bob aggressively counts his chickens before they hatch. That doesn’t make him a bad sales rep. It makes him a bad forecaster. Presumably, he still wins contracts or we would be talking about an ex-employee named Bob instead of his forecast. So all we really know about Bob is that he is good enough to not get fired and that he regularly has disappointing surprise losses.
Bob doesn’t know why he is losing these deals. Bob is doing the sales equivalent of spiking the football on the 1-yard line when he embarrassingly commits deals that he doesn’t win. His manager, who presumably was hired to help Bob ensure Bob’s success, doesn’t know why these deals are losing or he would have saved Bob some embarrassment and ensured that Bob understood the obstacles that are reducing the likelihood of this deal closing.
Instead of patting himself on the back for his grasp of the obvious trend that Bob overcommits deals, the sales manager would better serve his company by striving to understand where Bob’s disconnect lies. Bob does win some of his committed deals. Both Bob and his manager need to understand the fundamental differences between the deals that win and the deals that end in surprise losses. Is there a price point where Bob begins to struggle? Are there certain products that Bob is less effective selling? Are there certain types of prospects that Bob can’t seem to close? Are there certain activity metrics that might foreshadow success or failure? Are there seasonal buying habits that Bob is oblivious to? Is Bob using the wrong content or the wrong communications tools for certain types of deals? What other stories are hidden in the sales data?
Bob’s manager – who says he knows his reps – rarely knows any of these answers. And he certainly can’t conceptualize that all of these elements (and more) come into play on every deal. Nor does he understand that the signals may have different levels of strength on each deal, since no two deals are identical and no two reps capture sales data identically.
In many cases, while Bob was celebrating the win that never happened, his manager could have helped him shore up weaknesses in the deal. Maybe this deal had three or four specific and addressable weaknesses. Perhaps there was data that would have shown that our prospect wasn’t as engaged as Bob might have thought. Bob’s manager could have asked pointed questions to truly assess the prospect’s position. Maybe Bob struggles selling to a certain industry. The manager could have paired Bob with a colleague to serve as an industry expert or ensure that proven industry-specific content was made available to Bob. Maybe Bob is our best sales rep for small deals, but simply can’t close a deal over a certain price threshold. His manager should insert himself into negotiations so Bob can learn how to ask for more money. Maybe Bob is not seeing as much benefit in a new sales technology as his peers. The company spent a lot of money on the technology and has every interest in ensuring reps understand best practices for extracting maximum value.
In other cases, poor Bob will spend months chasing an opportunity as his top priority that was virtually doomed from the beginning. He will work day and night to close a deal that has hidden roadblocks. He will give the manager enthusiastic reasons for exerting so much energy on these deals. Those reasons may be totally valid. Bob may even be leaning on mathematically provable deal predictors that have been present in other deals that he won. But Bob’s inability to understand all the predictors of win and loss prevented him from understanding the deal’s inherent weaknesses. The time that Bob wastes on these deals comes at the direct expense of other deals in his pipeline that were mathematically more likely to win.
Unfortunately for Bob and his manager, it’s almost never just one data point that predicts whether a deal will win or lose. Bob happens to be a human being who makes decisions partly based on emotion or gut feelings. We all do. We all have blinders and biases that prevent us from making the right decision. When this happens, we need someone to get us back on track. In sales organizations, that job belongs to sales managers.
When sales managers – who also happen to be a human beings– can’t acknowledge their own blind spots, it renders them totally incapable of helping their teams achieve the best possible results. By failing to understand what drives some of Bob’s deals to succeed and others to fail, Bob’s manager can’t give tailored coaching. The end result is that Bob’s will never achieve his full potential and our company will lose deals that it should have won. But Bob is only one rep. If a company has 10 or 100 or 1000 salespeople, the aggregate impact of arrogantly “knowing our sales people” is catastrophic.
Jim Dries is the CEO of piLYTIX.
piLYTIX regularly receives calls from business leaders in desperate need of forecasting help. The calls typically spike right after corporate earnings are announced. Panic has already set in at companies that recently posted disappointing results. Our original business offering – simple as it was – provided detailed sales forecasts for large companies who needed forecasting help because of missed targets or disconnects between sales, marketing, operations and finance.
In analyzing client data to assist with forecasting, we quickly learned that missed sales targets are largely symptoms of crippling diseases. Like a doctor who only treats a patient’s symptoms, we found that companies that did not address their underlying challenges would always be at risk of missing forecasts. .
These challenges broadly align to four core competencies. Companies that understand these four competencies are better positioned to hit their forecasts. More importantly, they are better positioned to close more business and save time, effort and money in the process.
Opportunity Management: Most organizations struggle to understand the driving forces that make deals more or less likely to close or they lack the mechanisms to enable their sales talent to recognize these forces. Missed sales forecasts are usually accompanied by pipelines that yield many disappointing surprises. Companies that can analytically interpret the data about their opportunities without relying on rep intuition will have fewer surprises. Likewise, when reps’ blinders are removed and they can see their deals’ underlying weaknesses, they are much better positioned to take corrective measures. In some cases, they may choose to focus their energies on opportunities that are statistically more likely to close and spend less time on deals that have little chance to close.
Talent Management: Coaching and training programs tend to be based on average profiles or a couple traits of past top performers rather than quantifiable strengths and weaknesses of each individual rep. As a result, too many organizations rely on a “star system” in which tenured reps receive better opportunities or more territory. Simply stated, too many tenured reps are successful simply because they are tenured. This often comes at the expense of more recent hires who might be more capable of closing specific types of opportunities than the tenured reps. The outcome: lost revenue or, at a minimum, significant inefficiencies in the sale organization.
Data Quality: Too many companies blindly accept as fact that more data equals better data. They mistake quantity for quality. These organizations often attempt to implement major data capture policies where enforcement causes friction; reps want to be selling, not acting as data entry clerks. Other companies are paralyzed by the “garbage in, garbage out” mantra. They assume that if it’s not great, then it must be garbage. If it’s garbage it will take time and money to fix it. Time and budget tend to be in short supply, so they kick the can down the road. Presumably, they are waiting for the day when they won’t have short term sales emergencies or when their reps magically begin uniformly entering data. Neither of these situations is ideal but managers often don’t have the time, resources or know-how to properly address data collection and quality. Consequently, bad habits persist making long term predictability (and sales success!) challenging.
Pipeline Health: Traditional metrics of pipeline health are directionally helpful, but too many organizations over-rely on these metrics and struggle when conditions change. For example, some managers will assume that if they hit their target last year and this year’s target increases by a certain percentage, they just need to ensure that the number of opportunities in their pipeline this year increases by the same percentage. Without a firm understanding of the quality of the opportunities in the pipeline and the capabilities of the individual reps that make specific deals more or less likely to close, relying on this type of oversimplified metric tees these organizations up for disappointments.
Poor opportunity management, mismanaged and misaligned talent, poor data quality and an unhealthy pipeline all are underlying diseases that should be cured to heal forecasting accuracy. The solution to all of these challenges begins with a dedicated organizational focus to capture, interpret and act on the stories in your sales data.
Jim Dries is the sales rep in chief and head data geek for piLYTIX.
It happened again last week. The financial world held its collective breath in the minutes leading up to Apple’s release of its quarterly earnings statement. Shortly after 4:00 EDT on Tuesday afternoon, the announcement came. Five minutes and a couple disappointing numbers later, Apple’s stock dropped 9% in after-hours trading. It only took these five minutes for more than 52 billion U.S. dollars of market cap to disappear.