A few years back, I was impressed with how much work EMC had done on customer tracking as part of its loyalty and quality programs. While you’d think these efforts would have pissed off the customers, these customers were lining up to ask EMC to share these tools. This was because EMC could, through its efforts, better determine which customers were the most valuable and which the least, and then resource these groups appropriately. That then had a very dramatic and positive outcome for the bottom line. Often, the most demanding customers are also the least profitable, and in this way EMC could not only reward positive customer behavior but increasingly assure that the really nasty customers ended up being one of its competitor’s problems.
I started thinking about this further when I received a pitch from a small company that builds a customer ranking program for the hospitality industry (mostly for bars). Bar Shield is designed mostly to make sure that those who abuse staff, behave really badly, and “dine and dash” are encouraged to take their bad business anyplace else.
What if we ranked everything based on value to the company?
Making Smart Decisions
We often make big decisions based on our gut, yet we live in a time when data has never been more accessible. We actually often can figure out the costs and benefits to a variety of complex decisions and thus make far better ones, yet we seem to avoid that approach like the plague. Take the app above, for example. You’d think the idea of identifying both good and bad bar patrons would be obvious, with clear benefits, because you want the folks who tip heavily, buy expensive bottles of wine, and behave well to be your most common customer, and you’d also want those who get into fights, abuse the staff, swipe tips, and leave without paying their bills to never come through your doors. We can certainly identify customers through everything from their credit cards and IDs to facial recognition, yet instead of being up to our armpits in programs that do what Bar Shield does, there seems to be little demand for the offering.
Bad Decisions Around Layoffs
Some of the hardest decisions we make aren’t accurately instrumented, like whether to do a layoff and whom to let go. This is why layoffs often are so catastrophic. We actually get rid of high-value people that the firm can’t run without. I first wondered at this while watching the first big layoff at Disney from inside the company. They laid off every manager who didn’t have a college degree. We lost some of the best managers I’d ever worked for, some who trained under Disney himself, and almost overnight the park seemed to lose a lot of what made it different from every other amusement park. Granted, I went back to school and got my college and university degrees, so the experience was a clear wakeup call, but it seemed so avoidably stupid both at the time and now.
It seemed so obvious that people who had managed successfully for 10 or 20 years would just be better at it than folks with business degrees who had really never successfully managed anything other than their own grades. Yet in a matter of days, the experienced people were replaced by lower-paid young managers and the economy-driven decline the firm was in deepened.
Sadly for those who knew the park before this happened, Disneyland changed. Watching something that was to me so magical die was a life-changing moment.
Gwyneth Paltrow and Marissa Mayer
The other day, when it was learned that Yahoo’s Marissa Mayer didn’t hire Academy Award winner Gwyneth Paltrow as a writer for Yahoo Food because she didn’t graduate from college, it seemed like this same kind of mistake. Successful performers aren’t measured by their degrees, but for purposes like this, by the power of their celebrity. Paltrow had a bestselling cookbook and a popular lifestyle blog and the job was consistent with her now-proven success in this area.
The reverse of this would be hiring a CEO who had no real CEO or media experience to run a media company based on the fact that they had successfully worked for a dominant search company. Oh wait…
By the way, as a side note, apparently Martha Stewart isn’t a Paltrow fan either, which does support the argument that Mayer made a mistake (because Stewart appears to see Paltrow as a threat).
In both cases, the problem results from not making it a priority to identify the key required skills and instead making the decision based on some set of metrics that are less well connected.
Wrapping Up: Why We Don’t Use Ranking
We have the capability to identify the key aspects of a decision, then rank and weight them so that we can then rank the choices we have against the model we have created. The reason we don’t do this more often, or at all really, is likely because this process would often give us answers we don’t like. We might find out that the employee we want to get rid of is more valuable than we are (which is often the case). We might find out that the person without the degree is more valuable than the one with. We might determine that we should hire the less attractive qualified candidate.
In the end, though, if we know what is valuable and what isn’t, we can likely make better choices as to what to keep and what to get rid of. The other day, someone argued with me that we should do this with our friends and acquaintances. We all have those who will give us the shirt off their backs and those who seem to consume time, create unnecessary drama, and provide little other value, yet we often spend more quality time on the latter than the former. He argued that we likely should rethink all of that.
By the way, let me make it clear that this isn’t a pitch for Forced Ranking, a horridly ineffective process of ranking employees artificially by pitting them against each other. I think you can rank employees, but only based on their value to the company. Since collaboration would be a highly valuable attribute, it would have to be a major component of the ranking, rather than something that was weeded out by the process.
Rob Enderle is President and Principal Analyst of the Enderle Group, a forward-looking emerging technology advisory firm. With over 30 years’ experience in emerging technologies, he has provided regional and global companies with guidance in how to better target customer needs; create new business opportunities; anticipate technology changes; select vendors and products; and present their products in the best possible light. Rob covers the technology industry broadly. Before founding the Enderle Group, Rob was the Senior Research Fellow for Forrester Research and the Giga Information Group, and held senior positions at IBM and ROLM. Follow Rob on Twitter @enderle, on Facebook and on Google+