A company I once covered as a journalist had an interesting hiring process for its sales staff. Possible new sales reps would be recruited, interviewed and reviewed by HR and the sales management. HR was particularly involved and sought out data on the candidate’s sales performance in the past. A candidate’s refusal to provide numbers earned a notation from HR warning that the data was unavailable and the candidate should be viewed with a jaundiced eye.
Then, after much evaluation… the CEO would speak to the candidate and if he liked him, primarily based on his assessment of the candidate’s “fire in the belly,” the candidate would be hired, regardless of the information collected on him.
The impact on the sales organization is about what you’d expect: sputtering results, non-stop churn among the sales staff and a company whose promise is far from being met.
Yes, your instincts about a person should play a role in whether they are hired for your sales team. But, in this day and age, willfully ignoring (or failing to collect or analyze) data is an inexcusable sin – for hiring, and for any other part of the sales management process.
Sales pros, for the most part, no longer wear loud sports jackets and matching white belts and shoes. If they can evolve their fashion sense, they can evolve in other ways, too. And they’re ready for data to play a bigger role. Sales pros were the ones who drove things like CRM and SFA into businesses. They were the troublemakers who caused IT departments to figure out how to make “Bring Your Own Device” work when they brought smart phones into the office. On a deeper level than they may admit, they trust data.
So it’s time to build data into sales management. Your reps can handle it, sales managers. They’re ready for it. You can handle it, too.
First, the aforementioned hiring scenario needs the reality check that data provides. Sales pros are great at selling, and that includes the art of selling themselves. We all know sales people who talk a great game and then fail to deliver. If you insist on data during the hiring process, they will no longer be thorns in your side.
But it goes deeper than that. The use of data drives territory and quota management already – if you aren’t using software to manage this, you’re flying blind, trusting on your instincts. Your instincts are probably pretty good, but the software can confirm what your gut is telling you. And, if your gut is steering you wrong, software will let you know before you take steps that damage your results and alienate your sales reps.
A more advanced application of data comes in the use of predictive analytics based on historical performance data. As predictive sales performance platforms arrive, it will become easier to forecast your sales organization’s performance, right down to the level of the individual sales rep. Suddenly, as a sales manager, you have the opportunity to coach your reps using a data-based model to illustrate how changes in behavior will result in better performance. You also have a chance to use it retroactively to see how reps performed against what the data suggested their performance would be.
Trying to get reps to use your sales tools like CPQ and CLM more regularly? The real story is in the data. Use reporting to see just how often reps use these tools, and how many quotes and contracts they’re really developing. If the data shows fewer uses of CPQ and CLM than the number of deals they develop, they need to be encouraged to use these technologies more often.
The point here is not that sales management functions will become fully automated and that managers, with their years of real-world talent, will become obsolete. The point is that managers no longer have to make decisions primarily based on their experience, and can avoid being blindsided by changing circumstances, by allowing data to provide a verification of their assumptions. Bad decisions and direction can be vetoed by data – as long as you appreciate what that veto power means.
If you could avoid unnecessary surprises that embarrass you and preserve your job, wouldn’t you do it? And if you could improve the performance of the reps you manage, wouldn’t you do it? If you answered yes, you’re headed down the path of greater reliance of data.