MONTE-CARLO SIMULATIONS
The consequences of resource allocation options, connected with a high level of uncertainty, are usually difficult to estimate directly. An agricultural company, deciding to plant weed or soja, for example, could have difficulties to estimate the probabilities for different level of profits of these two options directly. With a Monte-Carlo Analysis this profit estimation can be separated into smaller parts, so that the decision-makers feel more comfortable and capable of making these assessments.
Instead of profits, the company could therefore assess the probabilities of different levels of sales, prices, fixed and variable costs. A computer model then provides two comparable probability distributions for the profits of the weed and the soja planting options as a basis for the resource allocation decision. A possible probability distribution of profits could be: probability of 5% of $1m or less profits, 20% probability of profits between $1m and $2m, 50% probability of profits between $2m and $4m and 25 % probability of $4m or more profits.
Monte-Carlo Analyses can be used for a variety of risk assessments within companies, NGOs or governmental organisations. Evaluation of project impacts or assessment of organisational strategies, for example, in the areas of marketing, sales or distribution can be preformed with these analyses. With this methodology a static, deterministic spread sheet model can be turned into a probabilistic, dynamic model.
Conditions to use Monte-Carlo Simulations to allocate resources:
- Resource allocation is mainly dominated by risk/uncertainty
- Possibility to separate components of risk
- Probabilities distribution of the different components can be estimated or calculated
