What Every Sales Manager Should Know About Forecasting

In Sales, asking questions will get you answers. Just not the ones you need.

A focus group was held for a new $100 electronic gadget. The response was fantastic. Everyone loved the gadget and excitedly discussed its features. When the session was over, the moderator thanked everyone and offered, as a gift, a choice of the gadget or $25.

Seth Godin told this story on his blog recently.

The punchline: “Everyone took the cash.”

Godin’s point: “It doesn’t matter what people say. Watch what they do.”

Watching, it turns out, isn’t always easy.

Consider election polling, the practice of asking people about their thoughts and intentions in order to, like that focus group, accurately predict an outcome. In the case of a presidential election, accurate predictions are hugely valuable, as the outcome will impact global economies, corporate budgets and industries from healthcare to utilities.

“It doesn’t matter what people say. Watch what they do.” — Seth Godin

Polling companies live in fear of the discrepancy between what people say and what they do and have “types” that stand as caution flags. “The Shy Tory,” for example, was coined after a British general election during which a group of voters declined to state their positions, even in exit polling, and so were dramatically under-represented by pollsters, who failed spectacularly in their predictions.

Sales managers, responsible for generating millions of dollars of revenue, likewise spend incredible amounts of time asking people questions: during hours-long Monday morning team meetings, during one-on-ones, during Friday follow-ups. Asking questions — What does the prospect need? Who has buying power? What are our next steps?— is their primary tactic for understanding deals and ultimately forecasting revenue.

So consider this: Focus groups ask direct questions of consumers and routinely fail, and polling companies ask direct questions of voters and routinely fail. And still Sales, the department most directly responsible for generating revenue — for paying salaries and funding innovation and keeping shareholders happy and the lights on — relies on the even-more-flawed process of managers asking team members about what they think buyers think and plan to do.

That 46.5 percent of forecasted deals close — worse odds than winning at a casino craps table — starts to seem more like a miracle than an accuracy ratio that none of us, in our consumer lives, would find remotely acceptable.

That 46.5 percent of forecasted deals close — worse odds than winning at a casino craps table — starts to seem like a miracle.

There are simply things that sales professionals don’t know about a prospect. There are conversations, motivations and protocols they aren’t privy to. They can only research, guess and trust the assurances of their contacts.

Then, added to that Swiss cheese of knowledge, is the format of asking humans questions in order to determine an outcome—the format frowned on by Godin and scientifically proven to be flawed.

There are the quirks of human nature that make us humans inclined to navigate even low-stress interactions with small fibs. (A University of Virginia study found that most of us lie about as often as we snack from the refrigerator, and that we tend to deceive 30 percent of the people we interact with one-on-one.)

Personality also plays a part. How easily might a person who’s naturally disposed to please others, or nervous to disappoint a manager, or intimidated by a superior, gently adjust facts to serve a purpose?

Further, there are the dozens of cognitive biases that prevent us, daily, from reaching accurate conclusions or making the best decisions. These range from the tendency to agree with people who agree with us (confirmation bias) to the belief that something seemingly unlikely, like flipping a coin to heads five times in a row, becomes less likely to happen again (gambler’s fallacy), though the odds haven’t changed.

The incentive structure of sales departments, and a selling culture that prizes determination and confidence, also skew outcomes. And the combined effects of jobs and salaries that directly depend on the most optimistic outcome, and the natural tendency of humans to hope for the best, make us even more prone to miscalculation.

Salaries that directly depend on the most optimistic outcome … make us even more prone to miscalculation.

And still additionally, the number of involved details and variables makes sales forecasting simply a task of big-data proportions, more appropriate for algorithms that can consider the habits of both sellers and buyers, and “if this than that” scenarios, and discover patterns or outliers that make certain outcomes more likely, than it is a reasonable task for even the most intelligent and organized people.

That anyone should arrive at an accurate forecast by asking questions of a team is the stuff of Vegas longshots, not something a person with a family and a mortgage should be expected to tie his salary to.

The key to accurate forecasting, it turns out, isn’t asking a sales team what they think but using data to understand what buyers do.

Sales practices don’t work more often than they do because they rely on a flawed premise. They rely on listening to people — and the wrong people, at that — instead of understanding buyers by learning from their actions.

The key to accurate forecasting, it turns out, isn’t asking a sales team what they think but using data to understand what buyers do.

Predictive analytics has been around for a while now and still hasn’t moved the needle. Because while the technology can eliminate the human biases, it can’t fill in a company’s inevitable knowledge gaps or create a context for understanding buyers. To do that, companies need far larger and more varied datasets.

Collective[i] is the first company bringing together information, from numerous sources, so enterprises can understand buyers — not what they say, but what they do, based on their past interactions with other sellers.

Godin advises: “Watch what they do.” We wonder, how soon will it be before B2B sellers routinely and accurately anticipate what buyers will do, without ever asking them? •

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Collective[i] provides real-time buyer intelligence, smart forecasting and other data-driven analyses based on one of the world’s largest networks of enterprise data, all to dramatically improve the performance of the world’s leading Sales teams. To learn more, visit @Collectivei or www.collectivei.com.