One application of machine learning that should prove to be especially useful for businesses is the creation of a knowledge base of evidence-based insights that will carry over during times of transition, like a major change in management. No longer will decades of industry knowledge disappear when a valued employee retires, because machine learning can make sure it is kept and used to educate up-and-coming replacements.
But machine learning by itself can’t do much. It has to have large quantities of data to work with. Fortunately, that data doesn’t necessarily have to be organized and housed in rigid databases to be of use. When companies break down the walls that tend to grow up and create data “silos,” and create instead massive “lakes” of data, it can all feed into AI, potentially yielding insights that might never have been possible before.
You don’t have to worry about machines taking over the jobs of your pharma sales reps, however. What it is far more likely to do is things like analyze email marketing campaigns and make recommendations about how often to target which customers, and with what information, making marketing efforts increasingly easy to personalize. Another possibility within the field of pharmaceuticals is drug discovery, based on AI engines chewing through masses of data from different research projects, potentially over many years’ worth of information. Unexpected new uses of existing medicines may result.
Computers and algorithms can crunch data, but they can’t tell from his tone of voice that the physician is in an irritable mood and probably won’t want to set up a sales call today. We haven’t figured out the many ways humans learn and pick up on instantaneous cues, so AI can’t do everything people do. But it’s making progress.
In short, pharma sales trainers should think of machine learning as a co-pilot rather than an autopilot when it comes to sales training. Your judgment and the judgment and decision-making skills of the reps you train are still absolutely essential to successful sales training. There may come a point when your reps to use machine learning to improve their results. AI might for example, analyze what type of learning content is the most helpful (meaning the type that results in sales) so that they can tap into more of that type of content when dealing with customers.