Thinking about that, I have a hypothesis about why the feeling “we need more information” persists:
- Even with information, hard decisions are still hard
- Information is of the wrong kind
- Thinking information costs too much
Even with information, hard decisions are still hard
This is really not very surprising, but there’s a common thread linking all hard decisions: they are hard. If they were easy, you wouldn’t be sitting there, thinking about the problem. No, you’d be back at home, or enjoying a run, or whatever. Decisions are hard for two main reasons: uncertainty and tradeoffs. Uncertainty makes decisions hard, but it can be mitigated with measurements. But what about those pesky cases when you can’t measure? Well, I’m going to say it flat out: there are no such cases. Sure, you can rarely get perfect certainty, but usually you can reduce uncertainty by a whole lot.
The second problem, that of tradeoffs, is the true culprit for hard decisions’ existence. Often we’re faced with situations, in which one option is more certain, but another has more potential profit. For example, when I run a race, I can start with a slower pace or harder pace. The slower pace is safer: I’ll definitely finish. The hard start pace, in contrast, is more risky: my reachable time at finish is better, but I run the risk of cramps and might not finish at all. Tradeoffs are annoying in the sense that there’s often nothing you can do about it, no measurement will save you. If you’re thinking between a cheap but ugly car, and an expensive but fancier one, what could you measure? No, you’ll just have to make up your mind about what you value.
According to a management joke, there are two kinds of information: what we need, and what we have. I think there’s some truth in this.
The highest-value measurements almost always are a bit of surprise to the client. Again and again, I found that clients used to spend a lot of time, effort, and money measuring things that just didn’t have a high information value while ignoring variables that could significantly affect real decisions.
It’s an honest mistake, thinking that if you have a lot of uncertainty, you need a lot of information to help you. But, in fact, the relationship is exactly the inverse. The more uncertainty you have, the less information you need to improve the situation. If you’re Jon Snow, just spending a moment looking around will improve things!
I think this mistake has to do with looking for perfect information. Sure, the gap to perfect information is much larger here. But the point is that if you know next to nothing, you get to pick the low-hanging fruit and improve the situation with those very cheap pieces of information, while in a more advanced situation with less uncertainty, you’d need more and more complex and expensive measurements.
For example, many startups face the following question in the beginning: Is there demand for our product? In the beginning, they know almost nothing. They probably feel good about the product, but that’s not really much data. An expensive way of getting data would be to hire a marketing research firm, do a study or two about the demand, burning tens of thousands in the process. A cheaper way: call a few potential customers, or go to the market and set up a stand. You won’t have perfect information, but you’ll know a lot more than you did just a while ago! It’s good to see that the entrepreneurship literature has taken this to heart, and guys like Eric Ries are teaching also bigger companies that more costly doesn’t always equal better. Or even if it would, maybe it’s still unnecessary. Simple measurements go a long way.