Skip to main content

DECISION ANALYSIS BY ANALYTICAL MODELLING

Decisions needs to be analyzed for conditions and assumptions considered in the decision model. The process is executed through analytical modeling of problem and solution. The model is analyzed in four ways:

  1. What if analysis – Decisions are made using a model of the problem for developing various solution alternatives & testing them for best choice. The model is built with some variables and relationship between variables . in reality, the considered values of variables and relationships may not hold good and therefore solution needs to be tested for an outcome, if considered values of variables or relationship change. This method of analysis is called ‘what if analysis’.
  2. Sensitivity analysis – It is a special case of what if analysis in which only one variable is changed and rest are kept unchanged. It helps to understand the significance of variable in decision making and improves the quality of decision making.
  3. Goal achieving analysis – in this, the problem is analyzed in exactly reverse way as that of what if analysis or sensitivity analysis. In goal seeking analysis, the goal is fixed and the variables and values are analyzed, which would help to seek that goal. The work is done backward from the goal.
  4. Goal seeking analysis - in this, the goal is not fixed but the decision maker tries to achieve a goal of an optimum value arrived at after satisfying all constraints operating in the problem. The decision maker can use this analysis to work on constraints and resources and find ways to improve upon solution to seek highest goal.

Labels:

Comments

Post a Comment

Popular posts from this blog

Advantages and Disadvantages of EIS Advantages of EIS Easy for upper-level executives to use, extensive computer experience is not required in operations Provides timely delivery of company summary information Information that is provided is better understood Filters data for management Improves to tracking information Offers efficiency to decision makers Disadvantages of EIS System dependent Limited functionality, by design Information overload for some managers Benefits hard to quantify High implementation costs System may become slow, large, and hard to manage Need good internal processes for data management May lead to less reliable and less secure data
1 comment
Read more

Inter-Organizational Value Chain

The value chain of   a company is part of over all value chain. The over all competitive advantage of an organization is not just dependent on the quality and efficiency of the company and quality of products but also upon the that of its suppliers and wholesalers and retailers it may use. The analysis of overall supply chain is called the value system. Different parts of the value chain 1.  Supplier     2.  Firm       3.   Channel 4 .   Buyer
Post a Comment
Read more

Big-M Method and Two-Phase Method

Big-M Method The Big-M method of handling instances with artificial  variables is the “commonsense approach”. Essentially, the notion is to make the artificial variables, through their coefficients in the objective function, so costly or unprofitable that any feasible solution to the real problem would be preferred, unless the original instance possessed no feasible solutions at all. But this means that we need to assign, in the objective function, coefficients to the artificial variables that are either very small (maximization problem) or very large (minimization problem); whatever this value,let us call it Big M . In fact, this notion is an old trick in optimization in general; we  simply associate a penalty value with variables that we do not want to be part of an ultimate solution(unless such an outcome is unavoidable). Indeed, the penalty is so costly that unless any of the  respective variables' inclusion is warranted algorithmically, such variables will ...
Post a Comment
Read more