What Makes Decision Making Hard

We make decisions all the time, some of them we call easy, hard and not so hard. What makes a decision hard?
The following looks at some conditions of a hard decision, and some of the tools available to help us.

Broadly, there are three categories of reasons why decision making can be hard.

Firstly, there is uncertainty.

This includes non-determinism as well as insufficiency of knowledge and information. It also includes complexity of the computing resources to obtain information.
For example, risk of a stock is associated with standard deviation, which is a statistical parameter of a probabilistic variable. However, the standard deviation is only approximated by looking at the historical data of the stock. Data may not be available, and computing resources may limit what can be calculated.
We have already seen this in relation to bounded rationality .
Another aspect of uncertainty is volatility, the uncertainty with respect to changes associated with the passage of time. Historical data may be useless if the system is changing very fast.

Secondly, structural complexity.

Structural complexity refers to the degree of entanglement of the situation. Structural complexity may imply computational complexity as well.
Many cases involve quantitative as well as non-quantitative relations among variables. One variable is likely to influence another, e.g. decrease in one variable will increase the other, but the relation cannot be quantified (see systems thinking and systems dynamics).
The number of variables and the relation and interactions among variables determine structural complexity.
We have seen how in Buddhist Economics , many more considerations such as Ethics and Ecology must be considered in addition to traditional Economics. This increases the structural complexity of the problem.

Finally, conflict.

Conflict refers to conflicting goals, interests and opinions.
Decision making with multiple goals is easy if the different goals can be weighted numerically and thus reduced to a single goal. In general, conflicting goals cannot be so treated.
Conflict can come from internal as well as external sources. It is interesting, that according to Minsky's "society of minds" theory , there are multiple minds inside us, including thinking and emotional minds, beliefs and desires, mostly in conflict with each other.

People found that our decisions are not rational, but instead we make decisions according to which mind happens to be strongest, and afterwards construct narrative rationalizations around them.

The combination of uncertainty, structural complexity and conflict makes decision making hard.
Some tools have been developed to assist us. For example Robert Clemens in his book Making Hard Decisions: An Introduction to Decision Analysis (Business Statistics) listed decision trees, cash flow discounting, probability and statistics, sensitivity analysis, Monte Carlo simulation, and utility theory.
These are useful, but often inadequate.

Systems Dynamics would be good for modeling, if everything is numerical. The system could be run under various what-if settings to produce simulations.
When numerical values are not available, Systems Thinking can be used for modeling. But the model cannot be "executed" by a computer program.
An alternative is FCM (fuzzy cognitive maps ), which uses fuzzy logic to express relations. Fuzzy logic has a natural way of resolving conflicts, allowing various "expert" opinions to be combined.
All three modeling methods have disadvantages. What is needed is perhaps a modeling method where the relations are can be partly numerical, partly fuzzy, and partly qualitative.
The model must be executable, at least for some of the sub-models.
Models must also be decomposable into top-down hierarchies to allow different levels of details.