Say you have a strategic decision to make. And you have several experts giving you different expert opinions about how you should make that decision. And you are not an expert. What do you do?
This is hardly an academic question. In fact, it is a fairly good description of what top management has to do every day. Especially in this era of the Internet, experts can be found to disagree on everything from interest rates to global warming to whether it is raining outside.
Organizational leaders cannot possibly be experts in every major area of uncertainty facing their organization.
Each of the areas in which they are NOT experts, therefore, can be seen as “black boxes” to top management. They can’t know what’s inside the box; all they can know is the opinion of the expert about it. When there are multiple experts, they have multiple opinions to consider — and they cannot ordinarily come to an informed opinion themselves about which (if any) of the experts may be correct.
This is why top managers get paid the big bucks: they are forced to make decisions under conditions of radical uncertainty about subjects in which they are not experts. As one leader once told us: “I have a new definition of the word crisis: It’s when people suddenly stop giving you orders.”
So you are a former marketing manager suddenly made CEO. You have to make a decision about which technology, among several, your company should pursue. What do you do?
You could array the different technologies against one another and compare their attributes. That’s not entirely useless; it might even be necessary.
Of course, the factors that make one technology the right way to go do not ordinarily correspond directly to their technical or even cost attributes. If that were the case, Betamax and Netscape would be historic technological triumphs and Microsoft might be out of business.
You could array differing expert opinions against one another as “black boxes” and compare those; but you’re not an expert, and you can’t come to an informed opinion as to which is right. More important, you can’t be sure that the expert opinions you are aware of actually cover the entire waterfront of the plausible.
The answer we recommend is (surprise!) scenario planning. You have to form a background analytical framework for your decision upon which your expert opinions can be arrayed, to make sure that the full range of the plausible is covered. So instead of your decision space being a bipolar “Betamax/VHS” one-dimensional line, you have several dimensions, e.g. growth in market demand for home video in the 1970s, high or low; economic market concentration in the videotape industry, oligopolistic or diffuse; effect of standards in the industry, multiple standards possible or one standard dominant. Because these broader issues (or ones like them), and not the more narrow expert technical specs, are what usually drive market success or failure.
What you will often find once you array your expert opinions across such an analytical framework is that they tend to clump in one corner, or maybe two, with whole swaths of territory ignored; they do not cover the full range of the plausible. So you need to fill in the blank areas — with alternative scenarios of your own. The experts might give you two scenarios; your own non-expert analysis might give you two or three more that they could never have arrived at due to the tunnel vision that technical or subject-matter expertise necessarily produces.
Once you have fully fleshed out ALL your scenarios, you can play out what technology decisions make sense in each; then you can look across them and figure out where your risks and opportunities lie, and which bets you want to make. It’s all about better, more informed decision-making; and the cool thing about it is that you are essentially using your own lack of expertise to create a more sophisticated risk management tool than any one expert ever could.
Naturally, we suggest you get some help in this endeavor, and that we be the ones to do the helping. We’ve helped NASA, the intelligence community, IBM, Pfizer, Ford, the United States Coast Guard, and many other organizations to improve the quality of their decisions in just this way.
You could say that, in the area of non-expert, dilettante decisionmaking…we are the experts.