The Quarterly: What does that mean in practice for managers?
Hugh Courtney: Level four situations are, by definition, ones for which you can’t really bound the range of outcomes, because it’s anybody’s guess. I’m sure we’ve all felt a little bit of that in the last few months. So the question is, do you just have to wing it? Is that what strategic decision making comes down to? I don’t think that’s true at all, but level four does require a different mind-set. (He is basically telling us that those situations whose outcomes cannot be predicted even one bit requires a different mindset while analyzing!)
From level one to level three, the presumption is that you can do some bottom-up analysis. You can figure out what the value drivers are and do some market research and some competitive intelligence. All this may not give you a precise forecast, but you’ll be able to bound the outcomes somehow. That’s impossible in level four situations, by definition. There’s just stuff that’s fundamentally unknowable—truly an ambiguous world. (Wait - Isn't that the definition of Level-4 according to your theory?)
On the other hand, that doesn’t mean you can’t be rigorous in thinking through strategic decisions in level four. It just requires you to work backward from potential strategies to what you would have to believe about the future for those strategies to succeed. (What was that?)
The classic example would be biotech—early-stage biotech investments have always faced level four uncertainty, because you’re playing with therapies with an ultimate commercial viability that is unknown.
(You can read it again and see whether he has come even close to answering the question!)
The Quarterly: How does that play out?
Hugh Courtney: You could ask, “What’s the return on investment of starting up a lab in this particular therapy?” The answer would be, “Who knows?” Honestly, no amount of analysis would allow you to bound the ROI. But say you told me the following: “We’re thinking about investing in a lab to work on a therapy. The lab’s going to cost $10 million. Should we do it?” Of course, I could say, “Well, I don’t know.” But I could also work backward from that $10 million investment and reply along these lines: “Say you need a 15 percent return on that investment. I can develop a scenario about the conditions needed to achieve this—what you would have to believe about the probability of finding a viable treatment, the amount of time it would take to get to market, the physician uptake rate on that treatment, the compliance rate of patients over time, what you’d be able to price it at, for how long, and how long you’d have patent protection.” I could tell you all that. In fact, I could give you a range of scenarios, all of which will give you that 15 percent return.
Now, the reason that approach would be useful is that even though I can’t do any bottom-up analysis, I can look at analogies. (Wow! He is basically telling us that if we can make some assumptions about some numbers while analyzing an entirely random event, that may help - Voila!)
There’s a whole history of drug development, and I can at least place those scenarios within the range of other outcomes in the past. Then I could tell you, for example, “We know now that this project would have to be the most successful drug launch in history to earn the return you want on that $10 million. I can’t say whether it’s going to play out that way, but are you willing to roll the dice given those odds?” Alternatively, “Hey, it only has to be as successful as the median drug-discovery process.”
In other words, you can think about a level four problem in a very structured way. It’s just that your mind-set has to change from a bottom-up analysis based on the value drivers to one based on what we know from similar situations in the past. You don’t have to wing it.
(Yeah, right!)
