Decision models are used to model a decision being made once as well as to model a repeatable decision-making approach that will be used over and over again. Development of decision model follows in various steps i.e. formulating, evaluating, appraising and refining a model.
The various steps are listed as
- Firstly Formulation – This is the first and fore-most most challenging stage. To develop a formal model of the given decision is the objective of this formulation stage.
- Secondly Evaluation –e. for a decision being made once, the objective of the evaluation stage is to produce a formal recommendation and its associated sensitivities from a formal model of the decision situation.
- Next Appraisal – The objective of the appraisal stage is for the decision maker to develop insight into the decision and determine a clear course of action. Much of the insight developed in this stage results from exploring the implications of the formal decision model developed during the formulation stage (i.e., from mining the model).
- Subsequently Refinement – The refinement stage responds to the insights obtained during the Appraisal stage. Effective refinement activities include opportunities to test possible decision model changes to see their implications and suggest better ways to modify the decision model.
Various approaches for problem solving are used, which includes
They graphically depict the various elements of the problem and their relationships as with the usage of influence diagrams. An influence diagram (ID) is a compact graphical and mathematical representation of a decision situation. It is a generalization of a Bayesian network, in which not only probabilistic inference problems but also decision-making problems can be modeled and solved.
Closely related to decision trees and often used in conjunction, influence diagrams are a summary of information contained in a decision tree. They involve 4 variable types for notation: a decision (a rectangle), chance (an oval), objective (a hexagon), and function (a rounded rectangle). Influence diagrams also use solid lines to denote influence. Their appearance is very similar to a flowchart.
An algebraic model takes a real-world situation described in words and describes that situation using algebra.
Some processes are so simple that they can be described in terms of algebraic equations, either explicitly, or implicitly as the solution to a differential equation. Algebraic equations are usually defined by applying some law of physics like conservation of mass or a time or space dependent equation describing the temporal movement of something. For example this is an explicit algebraic model: age = x – date of birth, where x is today’s date.
Spreadsheet formulae are used to relate various data values instead of algebraic equations or graphical representation. As spreadsheets are more widespread amongst business users, it is used for day to day decision making and modeling.
4Problem Solving and Decision Making
Uncertainty and an overwhelming number of alternatives are two key factors that make decision making difficult. Business analytics approaches can assist by identifying and mitigating uncertainty and by prescribing the best course of action from a very large number of alternatives.
Business analytics involves tools as simple as reports and graphs, as well as some that are as sophisticated as optimization, data mining, and simulation.
It consists of using generic or ad hoc methods, in an orderly manner, for finding solutions to problems. Some of the problem-solving techniques developed and used in artificial intelligence, computer science, engineering or mathematics
Problem-solving is used in many disciplines, with different perspectives, and often with different terminologies. For instance, it is a mental process in psychology and a computerized process in computer science. Problems can also be classified into two different types ill-defined and well-defined, from which appropriate solutions are to be made.
Being able to solve problems sometimes involves dealing with pragmatics (logic) and semantics (interpretation of the problem). The ability to understand what the goal of the problem is and what rules could be applied represents the key to solving the problem. Sometimes the problem requires some abstract thinking and coming up with a creative solution.
Problem-solving strategies are the steps that one would use to find the problem(s) that are in the way to getting to one’s own goal. Some would refer to this as the ‘problem-solving cycle’. In this cycle one will recognize the problem, define the problem, develop a strategy to fix the problem, organize the knowledge of the problem cycle, figure-out the resources at the user’s disposal, monitor one’s progress, and evaluate the solution for accuracy. The reason it is called a cycle is that once one is completed with a problem another usually will pop up.
The following techniques are usually called problem-solving strategies’
- Abstraction: solving the problem in a model of the system before applying it to the real system
- Analogy: using a solution that solves an analogous problem
- Brainstorming: (especially among groups of people) suggesting a large number of solutions or ideas and combining and developing them until an optimum solution is found
- Divide and conquer: breaking down a large, complex problem into smaller, solvable problems
- Hypothesis testing: assuming a possible explanation to the problem and trying to prove (or, in some contexts, disprove) the assumption
- Lateral thinking: approaching solutions indirectly and creatively
- Means-ends analysis: choosing an action at each step to move closer to the goal
- Method of focal objects: synthesizing seemingly non-matching characteristics of different objects into something new
- Morphological analysis: assessing the output and interactions of an entire system
- Proof: Try to prove that problem has got no solution. The point where the proof fails will be the starting point for solving it
- Reduction: Then transform the problem into another problem for which solutions exist
- Research: secondly employing existing ideas or adapting existing solutions to similar problems
- Root cause analysis: Next identifying the cause of a problem
- Trial-and-error: subsequently testing possible solutions until the right one is found
This is directly associated with selecting one course of action among two or more possible alternatives. Driven by a desire to solve problems or exploit opportunities. A problem refers to some type of event that requires a response to avoid a negative consequence. Conversely an opportunity is an event or situation where a response is required to make something desirable happen.
Therefore, it can be regarded as a problem-solving activity terminated by a solution deemed to be satisfactory. It is, therefore, a process which can be more or less rational or irrational and can be based on explicit knowledge or tacit knowledge.
Human performance with regard to decisions has been the subject of active research from several perspectives:
- Firstly Psychological: examining individual decisions in the context of a set of needs, preferences and values the individual has or seeks.
- Secondly Cognitive: the decision-making process regarded as a continuous process integrated in the interaction with the environment.
- Next Normative: the analysis of individual decisions concerned with the logic of decision-making and rationality and the invariant choice it leads to.
A finite set of alternatives described in terms of evaluative criteria is involved in the major part of decision making. Then when all the criteria are considered simultaneously the task might be to rank these alternatives in terms of how attractive they are to the decision-maker(s). Another task might be to find the best alternative or to determine the relative total priority of each alternative
Decision making is the process of making choices by setting goals, gathering information, and assessing alternative occupations. There are seven steps in effective decision making, which are
- Firstly Identify the decision to be made. You realize that a decision must be made. Then you go through an internal process of trying to define clearly the nature of the decision you must make. This first step is a very important one.
- Secondly Gather relevant information. Most decisions require collecting pertinent information. The real trick in this step is to know what information is needed, the best sources of this information, and how to go about getting it.
- Next Identify alternatives. You will probably identify several possible paths of action, or alternatives, through the process of collecting information
- Subsequently Weigh evidence. This step draws on your information and emotions to imagine what it would be like if you carried out each of the alternatives to the end. So, you must evaluate whether the need identified in Step 1 would be helped or solved through the use of each alternative.
- Then Choose among alternatives. Now once you have weighed all the evidence, you are ready to select the alternative which seems to be best suited to you. You may even choose a combination of alternatives.
- Later Take action. You now take some positive action which begins to implement the alternative you chose in the Step5.
- Also Review decision and consequences. In the last step you experience the results of your decision and evaluate whether or not it has “solved” the need you identified in Step 1.
Biases usually creep into decision-making processes, like
- Selective search for proof or confirmation bias
- Premature termination of search for proof
- Cognitive inertia in the face of new circumstances, it is unwillingness to change existing thought patterns.
- Selective perception
- Wishful thinking is a tendency to want to see things in a certain – usually positive – light, which can distort perception and thinking.
- Choice-supportive bias occurs when people distort their memories of chosen and rejected options to make the chosen options seem more attractive.
- Recency: People tend to place more attention on more recent information and either ignore or forget more distant information.
- Repetition bias is a willingness to believe what one has been told most often and by the greatest number of different sources.
- Anchoring and adjustment: Decisions are unduly influenced by initial information that shapes our view of subsequent information.