Roger Martin is one of our favorite business thinkers, and not just because he’s ranked in the world’s Top 50 or because he’s a Rypple investor. It’s because he writes really insightful content like The Secret to Meaningful Customer Relationships on HBR Blogs. You should really go read the whole thing because it’s got some strong and very useful things to say about the value of qualitative performance assessment feedback over quantitative, something we all wrestle with. Here’s the cheat sheet if you haven’t got time.
His post was inspired by economist and agency theorist Michael Jensen, who made some observations about qual vs. quant:
…subordinates generally object to receiving qualitative performance feedback from their superior, especially if it is at all negative. They typically are dismissive of the qualitative feedback and ask for the feedback to be on a quantitative basis only.
This strikes right to the heart of why we built Rypple. Jensen’s advice to managers is to tell the subordinate that if he could actually be evaluated using purely quantitative measures, his job should be outsourced. That’s brilliant really — and very true. If I could measure your job entirely based on widget throughput or whatsits analyzed per hour, I could hire a robot or an outsourcing company far more cheaply.
There’s also much less value in quantative feedback from a future-looking perspective. Knowing that you managed to write 183 bug-free lines of code an hour for the last three months is interesting, but it’s not a predictor of future performance or a particularly useful piece of feedback for your manager to give you (unless it earns you a gold star — everyone loves gold stars). Marshall Goldsmith talks about this in his seminal Try Feedforward Instead of Feedback article. The real value in sharing feedforward is to improve the future, not focus on things that happened in the past and can’t be changed.
This isn’t limited to performance assessment data. Roger very insightfully relates it to customer relationships (I told you he was insightful!), making the point that:
If our understanding of customers is based entirely on quantitative analysis, we will have a shallow rather than deep relationship with them.
We see this all the time in our business. We try to be a very lean startup and base as much of our decision making on data as we possibly can. That’s a good practice — maybe even a great one — but can have serious ‘data blindness’ consequences. If you limit yourself to making decisions based on what you’re tracking, how do you ever discover the hidden value that doesn’t turn up in your analytics?
Case in point: we spend a lot of time optimizing our registration funnel to remove friction and make sure all of the people who want to sign up for Rypple can easily do so. We’ve got data up the wazoo about where they go on our site, what they click on, how long they spend there, etc. This is pretty standard stuff, and we mostly get it out of Google Analytics and a few custom tweaks we’ve built. It’s great for finding friction and knowing where to apply some grease, but it doesn’t answer the very fundamental question of motivation. We know that x% of people who hit our registration page don’t complete the form, but for everyone who doesn’t encounter an error (which we track), we have no idea why they didn’t. Maybe they decided not to provide their work email address. Could be that a colleague stopped by their desk to chat and they got distracted. Maybe they remembered they had a roast in the oven. It’s even possible that they were spontaneously abducted by aliens as their finger hovered over the mouse button, ready to submit. Looking at quantitative data will never tell us the answer.
Alien abduction photo by Thorsten Thees. Licensed under CC.