How great would it be to have an analyst pressure test every commit before it hits your desk?
A better forecast plus more time selling would be a win-win. But is it possible?
You'll sometimes hear me talk about selling by “gut and golf” — a sales approach grounded in years of experience (gut) and deep, trusted relationships forged on the links (golf).
This past week, I sat in a large networking company’s conference room listening to an irritated sales rep and his sales manager discuss challenges in their current sales process (as an aside, being able to listen in on these sorts of conversations is what makes being a product manager such an awesome job!).
Inaccurate, incomplete sales data is a major headache for any sales team. Sales reps, managers, and executives use CRM data every day to set selling priorities, make program investment decisions, and forecast revenue. And the revenue forecast, in particular, can affect departments all over the company. So poor data leads to poor decisions that keep companies from reaching their goals. At the same time, every sales veteran knows it’s not practical to improve data quality at the expense of revenue.
Sales managers have a tough job.
For decades, Sales Managers have forecasted revenue with two things: CRM systems and spreadsheets.
CRM has been the mighty, immortal warrior for 3 decades. As a newborn in the ‘80s it was metaphorically dipped into the waters of invulnerability, a shield that would protect its position of power well into the foreseeable future.
I work with sales managers every day and I don’t know one who likes uncertainty. Every sales manager I know wants to understand exactly how deals are progressing and especially when they are not.
Plenty of companies I know struggle with how data science can give them a competitive edge. There are two areas where data science can help almost every company — improving the sales forecast and improving the effectiveness of the sales team. I'm going to touch on the first of these today.