Faked Out by Data, Not Fake News. |
June 2017 |
The word data is a generic term and has many implications for us in the digital media, ad-tech, mar-tech, whatever-else-tech industry. As is appropriate for this regular column on sales and sales management issues, the focus here is on one specific lesson: how not to abuse and misuse data. (“Hi, I’m Michael…I’m a data-abuser.”)
Many years ago when VideoEgg/SAY Media was growing really fast, my partner in crime, CFO Lee Kirkpatrick, and I modified our CRM so we could examine the specific reasons why we lost a sale. This is standard practice for sales orgs who are churning through a high volume of proposals, opportunities and deals. Just as pro athletes state that the secret to winning is found in the dirt, our dirt was in the playground of lost deals. The secret to growing and getting smarter about shaping our offering and selling efforts was based on learning why we lost opportunities (deals). Setting this up in the CRM was (and is) quite easy. Every week, each of our 50+ reps had to update the status for each outstanding opportunity, and if a deal went south during the past seven days, they had to designate it as “closed-lost” and give the reason why we lost the deal. If a rep checked the box for “closed lost”, a screen was served with pre-determined answers that described the reason why the deal was dead. Easy peasy. Lee and I – and the sales managers – thought this was going to be great! We’d just sit back and watch the data come in which would lead us to the holy grail of learning. We would receive an auto-generated report each Friday morning on "closed-lost" deals, and in our weekly managers meeting later that day, we’d dissect each lost opportunity and assess it. Was it because of an offering weakness? A packaging problem? A buyer misperception? Price? ….did we lose because we were too expensive? Did the lost deal suggest there was a negotiation weakness by the rep? Did the rep give up and not push hard enough? While the data wouldn’t always be so clear, we could look at the data and make some calculated conclusions. The goal, of course, was to get the data sharp enough so there was no conjecture. "This was one of my most famous gaffes in my career and it landed me in the Sales Management Screw-Up Hall of Fame." For a few months, things went pretty well and we were learning good insights, until yours truly blew it all up and choked the golden goose. In one of our weekly sales meetings attended by sales executives, sales managers and other department players, I publicly presented the “closed-lost” percentage rates for all individuals on the sales team.
There was no blow-back during the meeting itself, but a fire-storm broke out in the following days. The second the reps saw the rankings, they concluded they were being judged on a sales skill that exposed them. Their brains even extrapolated that this data would be used against them in performance review protocol, and even compensation discussions (goal setting, salary, etc.). Even the top performers didn’t like the tactic. Of course I immediately saw the error of my ways. I couldn’t blame them. This was one of my most famous gaffes in my career that landed me in the Sales Management Screw-Up Hall of Fame. (Am still thinking of breaking in and tearing down my exhibit, but I’m kinda’ resigned by now.) I maintain that the error in judgment was easy to make. I saw the data from the angle that allowed us to learn: “hey look, 37% of our deals die because of xx….that means we can train against that.” That didn’t matter to the reps – all they saw was data that focused on a weakness, and the fact that it was publicized made it worse. The story has a happy ending. I publicly apologized for my stupidity and reinforced that I was merely trying to share data that would help us all. (They forgave…over time…a long time.) From there, I worked tirelessly with a select group of sales managers and sales executives to build a CRM feedback mechanism that worked for everyone. And off we went learning tons about our dead deals that helped the org for years after that. Sure, the sales managers and I had to constantly tweak and edit our process (and sometimes sell these changes to the team), but everyone bought in because they saw positive change happen in the organization as a result of our data analysis. The lessons from this episode are, of course, imprinted on my brain - this much is true about “data” in this sales operations context:
Peace / out (or whatever the cool kids say these days). |
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