Sales analytics is the bridge to the digital sales organization of the future. While analogue human interactions will always inject a degree of variability into the equation, the insights analytics provides cannot be ignored. However, introducing new analytic data must be accompanied by a change management strategy that allows sales people, managers and management to incorporate productivity-improving insights. It must not be treated as a new weapon to challenge their forecasts.
Introducing analytics to the sales organization offers fresh insights into the business, provided the sales team uses it. With pipeline integrity already in question, analytics threatens to dissolve the status quo of the semi-secretive yet effective manual forecast process. Simply pushing new reports at the sales team, or worse, ambushing them with a deeper level of scrutiny will ensure that new data is met with mistrust and challenges to its validity – or simply ignored.
When new analytic data is introduced, opportunity, pipeline and forecast data is shown in a new light. Sales people, managers and leaders are naturally suspicious, wondering how this new data might be used against them; casting the shadow of doubt on their current sales process or exposing flaws in their business they didn’t see or chose to ignore. For sales managers, putting analytics in the hands of financial analysts who are far from day-to-day customer interactions represents more risk than value because it limits the manager’s ability to respond to new questions or to defend forecasts based on old school theories. This new “science” of sales may be perceived as a threat to those who believe sales is more art than science.
Analytics Power
Business intelligence (BI) applications generate new insights into business performance and productivity. BI tools connect, sort and assemble multiple data points to create a new perspective. In sales, analytics are used to track forecast volatility, project customer propensity for cross sell – up sell and measure opportunity conversion and cycle length by sales phase.
Analytics track forecast and pipeline shift and changes over the course of the month or quarter. Opportunity data snapshots based on anticipated close date allow for the comparison of movement to updates. Analytics dashboards display current bookings and project forecasted revenue based on opportunity movement. For sales management, this information illuminates, in real time, the path to obtaining forecast.
Analytics can also identify cross sell and up sell opportunities by comparing existing customer product usage against potential. If 75% of customers who use product A and B also use C, then targeting customers who have purchased A and B but not C is easy.
Sales cycle data is especially powerful. Monitoring qualified opportunities as they move through the sales cycle gives sales management a new way to predict opportunity outcomes. Measuring conversion rates by sales stage as opportunities advance or fall out develops a pipeline profile based on number of opportunities and their degree of movement. Adding the dimension of time in each sales phase and using the demographics of the opportunity like customer type, product mix or price creates an even deeper profile of the opportunity. The result is a multi-dimensional view of the pipeline that can be used to predict and improve pipeline and revenue performance.
Manage Change
As with any new initiative, a change management strategy must accompany the launch of analytics. As new data comes online, sales management, managers and sales people must be introduced to new data in ways that allow them to accept and absorb how this fresh insight helps them. If pipeline analytics are introduced, they must be presented in the context of how an analytical perspective can help the manager better understand and manage his business as compared to his current method of forecasting. For example, if the data shows opportunities that spend more than 90 days in a given sales phase are 50% less likely to close, sales managers may need to be taught how to use this data to improve pipeline integrity, factor or eliminate stalled deals and coach their sales reps to adjust their focus.
While analytics represents the future of the digital sales force, how it is introduced is as important as the data it generates. For sales leaders to embrace analytics, data must be presented as a new tool, providing perspectives and insights into their business and leading to a more productive sales force. When sales leaders and managers are given the data with instructions for incorporating it into their existing process, a beachhead can be established from which increasingly detailed and introspective data can be introduced.
Believe in Data
In 1927, when Charles Lindberg became the first man to fly solo across the Atlantic to Paris, it wasn’t the durability or the fuel range of his airplane, the Spirit of St Louis, that was questioned. Rather, skeptics wondered whether he could interpret and execute the 36 precise navigational data points needed to fly the great circle route to Europe using newly introduced compass technology. New data, when trusted and understood, can open incredible new possibilities. For sales leaders, trust of new data is a hurdle they must overcome before data can be the vehicle that takes their business to the next level.