But this is too simplified for decisions related to business development. It's difficult to identify all options…it's difficult to rate them because of information asymmetry (the known vs the unknown)…even when ratings are possible their rating isn't objective.
The standard view of uncertainty
It can be summarized as follows:
- Figure out all possible states
- Enumerate possible actions
- Figure out the consequences of actions for all possible states
- Attach values to consequences
- Select actions that maximize values
Problems with this approach are easy to see: state space uncertainty - if you identify risk as cost you may not see a possible growth…option uncertainty - it's rarely that we can predict consequences of enterprise transformations programs (especially if innovations is involved)…preference uncertainty - we usually lack factual information of possible future outcomes and consequences.
The standard approach to managing uncertainty assumes that all possible states, actions and consequences can be determined (or boiled down into single probability distributions). But this is rarely so.
This part was inspired by this post of the Eight to Late blog - that I read frequently.
It explains why enterprise risk management is a management risk. The poles of the dilemma are predictability vs adaptability or control vs agility on the positive side and bureaucracy vs lack of control on the negative side.
But what about optimizing risk? It needs learning from turbulences, adaptability and agility.
Is a kind of trial and error insight gain possible? Yes, people make progress using things without knowing exactly how they work. And this is great.
Manage an enterprise under uncertainty?
In risk of the jungle I pointed out that uncertainty is not risk and that you may still be able to optimize risk in the "uncertain" zone - by using (real) options to name one…
Changing the game rules of competition
In real options enable antifragility I've outlined that real options can maximize the value of a project. Real option valuation tools apply proven mathematical, statistical and corporate finance concepts based on option theory to value future decisions…emphasizing on investment projects they give answers on the Net Present Value, odds on special losses and wins…prices of call or put options and their exercise probabilities…informations that are definitely valuable for top managers.
But there's one more thing beyond making better decisions to become better: use the what-if capabilities of a good real-option valuation tool to simulate businesses in order to get insight into possible new market behaviors in order to define the game rules of competition.
Remember, by 1987 the option traders played the (simple) Black-Scholes formula game. But then the far-out-of-the-money options were introduced and the game rules changed drastically (models needed the volatility smile and stochastic volatility extension…dynamic hedging became much more difficult...).
I know, this is simple, compared to real businesses, but still…top managers, using the simulation capabilities of a comprehensive real options valuation tool (rov) may get the insight to apply new types of in- and out licensing, business development partnerships…game rules...
IMO, this is the killer application of rov.