A recent article by McKinsey & Company looks at big data sales programs from a no-go angle. Most companies are inundated with customer data, know how they would like to use it, yet can’t get it to work. Why not? It turns out that getting the big data train rolling hinges on how well you can read and react to your salespeople's emotions.
Here are three of the most common behavioral obstacles standing in the way of big data analytics effectiveness, and some thoughts about minimizing their impact.
Many salespeople believe these analytics are too complicated and won’t provide enough benefit for the effort required to understand how to use them. They have “tool fatigue,” having seen one too many "new and improved" approach come and go. Sales leadership is going to have to work hard to convince reps that the analytics aren’t complicated and that it’s worth adopting.
Many sales reps think more of their own instincts and experience than they do sales analytics. Yet well-implemented analytics can provide better, more relevant answers than all but the very best salespeople. Sales leaders need to show their folks how analytics can help them do their job better and, critically, make them more money.
This one is probably the toughest issue to overcome: the psychological concern that machines are replacing humans. Automation has eliminated some low-value and repetitive tasks, and technology can be more efficient at making recommendations directly to consumers (especially in digital channels). As a sales leader, you need to convince your sales organization that people still want to talk to people, and that they are more valuable than ever for understanding customer needs and more complex purchases, such as bundled product sales.
So for those of you who are charged with making big data programs work, your number one priority is to understand and acknowledge these obstacles, and develop specific approaches to build trust that overcomes the emotional resistance to them.
You can read the article in its entirety here.