Measuring the Risk Associated With Decision-Making

 

Every day each of us must make a decision based on information coming from different sources. The level of fragility of the information on which the decisions are based on is one of the key issues for any decision maker. In particular, the knowledge of the level of the fragility becomes more and more important in an uncertain a turbulent environment where the expected results might not be what one wished to pursue.  Unfortunately, when someone is going to execute an action, he/she assumes to have control over the risks related with a particular choice or strategy and a clear idea of the robustness of the information used to implement it. However, in reality, very rarely is the real degree of interdependency between multiple parameters known. This interdependency, however, may have relevant impacts on the decision-making process.

Complexity is a natural property of every system. It is also a characteristic of any decision and contains a wealth of information about a given set of parameters used to make that decision, beyond what conventional techniques are unable to produce. Through the quantification of this complexity one is able to understand the fragility of his decision as well as the level of controllability over a particular system. The Complexity & Risk Map in particular, defined as a map reflecting the structure of relationships between system variables, holds useful information which allows one to quantify the controllability of his system.

The “distance from full controllability” of a system is a factor one should measure in order to have a tangible idea as to the risks associated with decisions. As one moves away from complete controllability the risk associated with a particular decision increases. The main reason is because the decision in question is being made based on a small number of manageable rules. Since the decision and the resulting actions are consequence of the interactions between the different sources of information, the predominance of interactions that are out of the control of the decision maker decreases the reliability of the decision itself. This does not mean that the decision cannot be pursued. What it means is that greater care and a contingency plan are needed in order to counter the unexpected.

On the other end, the closer one is to complete control of a given system or situation the number of possible alternatives, which allow one to put in place the correct actions, is lower. In this situation, one is faced with a "locked" system, in which all parameters are strongly interconnected and, consequently, leave very little room for maneouver.

Let us see how it is possible to measure the level controllability of the GDP structure of a country. Two Eurozone countries are used for the purpose. Both plots portray the evolution of controllability over time. A fully controllable system has a controllability index of 100%.

Case 1.


Case 2

In both cases one sees an increased incidence of chaotic relationships (unmanageable relationships). This has a serious impact on the governance and management of the main macroeconomic GDP components. It is evident, how after the subprime crisis, the incidence of unmanageable relationships assumes significant proportions. At the end of 2011 about 70% of the possible relationships are out of control of both Governments. This means that any kind of actions will require more effort and control due to the low predictability and reliability of the excepted results. 

However, the two countries show diverse evolution patterns. In the first case the predominance of governable relationships (blue area) is evident, while in the second case the incidence of relationships associated with the independent parameters (green area) is quite relevant and tends to increase during 2011. Indeed, six of the GDP parameters are independent. This means that any actions on these parameters cannot be expected to produce any effect on the final results.

Measuring controllability provides a useful global picture of the level of manageability of a system and helps quantify the level of accuracy, efficiency and fragility of decisions made in relation with that system. In a turbulent economy this new “KPI” constitutes new and crucial information which managers should take into account when making crucial business decisions.

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