Components of the decision are collected both for the aspects that are in favor and against the problem, in order to define its limitations. If the decision maker has knowledge of either the circumstances surrounding the problem or a similar situation, then these can be used to select a favorable course of action.
application-of-the-technique-trees-of-decisionWhen an individual solves a particular problem, either with good or bad results, this experience provides information for solving the next similar problem. You cannot speak of a particular method to analyze a problem, there must be a supplement, but not a replacement for the other ingredients. In the absence of a method to mathematically analyze a problem it is possible to study it with other different methods. If these other methods also fail, then intuition must be trusted.
Judgment is necessary to combine information, knowledge, experience, and analysis in order to select the appropriate course of action. There are no substitutes for good judgment. The future effects have to do with the extent to which the commitments related to the decision will affect the future. A decision that has long-term influence can be considered a high-level decision, while a decision with short-term effects can be made at a much lower level. Reversibility refers to the speed with which a decision can be reversed and the difficulty of making this change. If reversing is difficult, it is recommended to make the decision at a high level; But if reversing is easy, you need to make the decision at a low level.The impact of this characteristic refers to the extent to which other areas or activities are affected. If the impact is extensive, it is indicated to make the decision at a high level; a single impact is associated with a decision made at a low level.
Quality This factor refers to labor relations, ethical values, legal considerations, basic principles of conduct, company image, etc. If many of these factors are involved, you need to make the decision at a high level; if only some factors are relevant, it is recommended to make the decision at a low level. The periodicity of this element answers the question of whether a decision is made frequently or exceptionally. An exceptional decision is a high-level decision, while a decision that is made frequently is a low-level decision.
SUMMARY
Components of the decision these are collected both aspects that are for and against the issue, in order to define their limitations. If the decision maker has knowledge either of the circumstances surrounding the problem or a similar situation, then these can be used to select a course of action favorable. When a person solves a problem in a particular way, either good or bad results, this experience provides information for solving the next similar problem. One can not speak of a particular method to analyze a problem, there should be a complement, not a replacement of the other ingredients. In the absence of a method for analyzing a problem it is mathematically possible to study alternative methods. If these other methods also fail, then you must rely on intuition. The judgment is necessary to combine information, knowledge,experience and analysis, in order to select the appropriate course of action. There is no substitute for good judgment. The future effects has to do with the extent to which the commitments relating to the decision will affect the future. A decision that has a long-term influence, can be considered a high-level decision, while a decision to short-term effects can be taken at a much lower level Reversibility it refers to the speed with which a decision can be reversed and the difficulty of making this change. If reverse is difficult, it is recommended to make the decision at a high level; but if reverse is easy, it is required to make the decision at a low level. The impact this feature relates to the extent that other areas or activities are affected. If the impact is extensive, it is indicated the decision to a higher level;a single impact is associated with a decision made at a low level. Quality This factor relates to labor relations, ethical, legal considerations, basic principles of conduct, company image, etc. If many of these factors are involved, it is required to make the decision at a high level; if only some factors are relevant, you should decide at a low level. Periodicity this element answers the question of whether a decision is frequently or rarely. An exceptional decision is a high-level decision, while a decision is made is often a low-level decision.you should decide at a low level. Periodicity this element answers the question of whether a decision is frequently or rarely. An exceptional decision is a high-level decision, while a decision is made is often a low-level decision.you should decide at a low level. Periodicity this element answers the question of whether a decision is frequently or rarely. An exceptional decision is a high-level decision, while a decision is made is often a low-level decision.
INTRODUCTION
In today's world dynamics, the success or failure of a company is largely determined by the ability of its managers to make the right decision, in the right place and at the right time. Due to the complexity of many decisions, taking an accurate course of action exceeds the capacity that our common sense or our intuition can offer us, no matter how acute it is, and then the need appears to rely on a set of tools that allow us to find a rational argument. to them.
In conjunction with the development of science or administrative art, whatever you want to call it, a series of quantitative models and methods have been developed, which, based on the rational approach, are capable of evaluating various alternatives taking into account the existing circumstances and limitations and find the solution that most effectively meets the achievement of the objectives.
Searching for the context of problems and opportunities, obtaining the necessary information, identifying the available alternatives, reflecting carefully on them, making a personal decision and moving on, constitutes the daily routine of many specialists.
Important developments were made in the early 20th century in terms of mathematical modeling, especially for inventory control, waiting line analysis, quality control, and production scheduling. In the field of mathematics there was another important development also at this time: that of statistics as a method for data analysis and decision making. But all of these developments were individual isolated applications. It was not until World War II that joint efforts were made to attack large-scale problems quantitatively.
In the 1950s the American industry became interested in operations research, and this interest grew in the second half of the decade and even more with the advent of computers.
Today, quantitative methods in management can be called in several ways: operations research, management science, systems analysis, cost-benefit analysis, statistics. Either way, the essence is the same: to be rational and scientific when solving administrative problems.
In the context of the Cuban economy, there are, perhaps more than in other countries, multiple factors in the framework of business activity that prevent decisions from being made rationally, such as excessive centralization of powers, poor preparation of personal together with the ignorance of this set of methods. Although these tools are not in themselves capable of providing a magic solution to all problems, they can serve as a guide and as an aid to avoid making mistakes that are often decisive in the business environment.
Processes in which the decision-maker must adopt a sequence of decisions (subsequent decisions dependent on the initial decision) are very frequent in companies, since a decision at the present time may condition and demand other decisions at later moments of time. In these cases a technique called decision tree can be applied.
A decision tree is a system of representation of the decision-making process that reflects the possible alternatives that can be chosen and the results that correspond to each alternative depending on the state of nature that is presented.
Hence, the present work has as a scientific problem:
Need to increase the quality of the decision-making process in the Cuban business environment.
Once the problem is exposed, the research has the following objective:
Apply the decision trees technique as a scientific tool, thus raising the quality of the decision-making process in the Cuban business environment.
The following hypothesis constitutes the partial solution of this objective:
If the decision trees technique is applied as a scientific tool, the quality of the decision-making process in the Cuban business environment will be raised.
DEVELOPING
Quantitative Analysis and the Decision-Making Process
Decision making can be defined as the selection of an alternative from a set of them. However, when the administration relies on the scientific method, the selection of an alternative constitutes almost the last step of a whole process that is called by many precisely as follows: Decision-making process.
This process is defined by different authors in different ways, but they all have common features in terms of their fundamental aspects.
The objective of the scientific method applied to business sciences is to provide the administration with a methodological guide that allows solving problems, which begins with its definition and continues with the collection of information, the formulation of a hypothesis, hypothesis testing, evaluation of the results and culminates in the drawing of conclusions.
The use of quantitative models and methods is provided by one of the broader approaches to decision making: Operations research.
This approach is the result of applying the scientific method to the study of alternatives to a problem, in order to obtain a quantitative base that supports decision-making. In other words, it rests on the use of mathematical models and methods.
Quantitative methods can be used in three ways:
- As a guide in decision making: The use of methods and models to handle administrative problems in a quantitative way, give practice and experience in rational thinking since they are based on the scientific method. As an aid in decision making: The Second application of quantitative methods contributes to the decision-making process. Many times there is no model to provide a solution, but there may be useful information that can be obtained quantitatively. To automate decision making: If a specific problem can be accurately modeled, then a formula or set of formulas can be developed for your solution. If the problem does not change, the formulas remain valid and can be programmed on a computer. The computer then "makes the decision." So,decision making has been automated.
The advent of computers has been important to the development and application of quantitative methods in administration.
The efficiency in the calculation has made the application of certain techniques such as linear programming economical. In addition, computers have encouraged continued research into new methods, especially simulation. But, in essence, it is the specialist who delves into these large-scale applications.
In general, a model is a representation of some aspect of reality. Equations, concepts, and theories are also models. In each case there is an attempt to represent or explain something that is part of the real world using less than that object of interest.
Decision making under conditions of certainty, uncertainty and risk
To make a decision it is necessary to know, understand and analyze the problem in order to be able to give it a solution. There are cases in which the consequences of a bad or good choice can have repercussions on the success or failure of the company, therefore it is necessary to carry out a more structured process that can provide more security and information to resolve the problem.
Currently there are decision models, implementing various criteria, which are useful in the decision-making process such as: the decision-making model under conditions of certainty, uncertainty or risk, which are explained below:
- Decision-making model in conditions of certainty:
Decision-making in conditions of certainty is when you have complete information about a certain situation, you know alternative solutions and the result of each one of them.
- Breakeven analysis.
The equilibrium point is where the total income and costs are equalized, so at that moment the economic result of a company in neutral, that is, there are no losses or profits. There are several methods to determine the equilibrium point, these are: Equation method, contribution margin method and the graphical method.
- Linear programming:
Linear programming is a deterministic method of analysis, to choose the best among many alternatives. When the best alternative includes a coordinated set of activities, it can be called a plan or program integrating several criteria at the same time. These criteria can be divided into two categories restrictions and objective. Constraints are the conditions that a solution under consideration must satisfy. If more than one alternative satisfies all the constraints, the objective is used to select from all feasible alternatives.
- Inventory control:
An inventory system is a set of policies and controls that monitor inventory levels and establish what levels should be maintained, when to order an order, and what size should be placed. We can refer to ABC method, economic order quantity and reorder point.
- Decision-making model in conditions of uncertainty:
A situation of uncertainty is one in which a subject makes the decision without fully knowing the situation and there are several results for each strategy. They can be non-competitive and competitive decisions.
To decide there are a series of selection criteria:
- Laplace
It states that if absolutely no information is available on the probabilities associated with future outcomes then equal probabilities should be assigned to each of the possible outcomes and these probabilities should be used to calculate the expected value of each of the possible courses of action. It is determined by summing the probabilities of each state by its value in the prize matrix. The best prizes are chosen.
- Maximax criteria:
It establishes that for each course of action the best result is defined (maximum profit or minimum loss) and the maximum is selected from among these best.
- Maximin criterion or Wald criterion:
It establishes that for each possible alternative, the executive determines which is the worst of the possible results, that is, the one that produces maximum damages or minimum benefits. Then select from among the latter the one that maximizes your profits or minimizes your losses.
- Minimax criterion or Savage criterion:
It deals with the opportunity cost of a wrong decision. From the payment matrix, a new matrix is built called the repentance matrix.
The idea under this approach is to protect the executive against excessive opportunity costs. To protect himself, the executive applies the Minimax criteria to the repentance matrix. The maximum loss in each line is identified and the alternative whose line has the least regret is selected by the executive. The main deficiency of this criterion is to ignore all the elements of the regret matrix except the largest, wasting a lot of information.
- Hurwicz criteria:
This criterion constitutes a compromise between the optimistic and pessimistic criteria, by introducing an optimism coefficient that we denote by α, comprised between 0 and 1, and its complement to the unit that is the so-called pessimism coefficient (1-α).
The best of the results of each strategy is weighted with the optimism coefficient, while the worst of the results is weighted with the pessimistic coefficient (1α).
If the results are favorable, the decision you would make with this criterion is the greatest. If the results were unfavorable, the decision that would be taken would be the least.
Example. Decision in conditions of uncertainty
Saleswoman Phyllis Pauley sells newspapers at the corner of Kirkwood Avenue and Indiana Street, and every day she must determine how many newspapers to order. Phyllis pays the company $ 20 for each copy and sells them for $ 25 each. Newspapers that don't sell at the end of the day are worthless. Phyllis knows that each day she can sell between 6 and 10 copies, each with an equiprobable possibility. Using the decision criteria, determine how many newspapers to buy.
Reply:
- Reward Matrix Development
Newspaper Profit = Sale Price - Purchase Cost
Profit per newspaper = 25 - 20 = 5
- Development of decision criteria under uncertainty:
Maximin
The worst of the results of each action must be determined, to choose the best: the "best" worst.
R / $ 30 is the most you can earn in the worst case.
Maximax
The action is determined with the best of the results of each action, to choose the best: the best of the best.
R / $ 50 is the most you can win at the best of the best of times.
Minimum Repentance or Savage Criterion:
- The best result of each state in the world is chosen to assemble the repentance matrix. Each value of the matrix is determined by: the best - what was given. The action is determined with the best result of each action. the worst of the best is chosen.
A / You must buy 6 or 7 newspapers.
Laplace's criterion:
It is determined by summing the probabilities of each state by its value in the prize matrix. The best prizes are chosen.
A / You must buy 6 or 7 newspapers.
Hurwicz criteria:
The optimism coefficient α = 3/4 and the pessimism coefficient 1-α are determined, the best of each strategy is weighted with the optimism coefficient and the worst with the pessimism coefficient.
30 * 3/4 + 30 * 1/4 = 30
35 * 3/4 + 10 * 1/4 = 28.75
40 * 3/4 + (- 10) * 1/4 = 27.5
45 * 3/4 + (- 5) * 1/4 = 32.5
50 * 3/4 + (-50) * 1/4 = 25
- Low risk decisions:
A risk situation is characterized in that a probability of occurrence can be associated with each state of nature, probabilities that are known or can be estimated by the decision-maker before the decision-making process. The different decision criteria under risk conditions are based on statistics associated with the probability distribution of the results. Some of these criteria are applied to the totality of the alternatives, while others only take into account a subset of them, considering the remaining worst, so they are not present in the decision-making process.
The main decision criteria used on decision tables in a risk environment are:
- Criterion of the expected value Criterion of the maximum probability Criterion of the dispersion Criterion of the mean with limited variance Criterion of minimum variance with limited mean
Qualitative and quantitative bases for decision making
The analysis phase of the decision-making process can take two basic forms: quantitative and qualitative.
Qualitative bases:
Qualitative bases are useful, not only for problems that relate to objectives, but also for problems that deal with the means of achieving objectives.
In application, qualitative bases are highly personal, widely known and considered by many to be the natural way to make a decision; There are four basic qualities: experience, intuition, facts, and creativity.
Experience: It is logical to assume that a manager's ability to make decisions grows with experience. The concept of seniority in an organization with those individuals who have the longest service, is based on the value of experience. When selecting a candidate for a position in the organization, experience is a chapter of great importance when it comes to decision. Past successes or mistakes form the basis for future action; Previous errors are assumed to be potential for fewer future errors. Likewise, we assume that the successes achieved in previous times will be repeated.
Experience has a very important role in decision-making, be it for poorly structured or new situations.
Good judgment and intuition: The term judgment is used to refer to the ability to evaluate information intelligently. It is made up of common sense, maturity, reasoning ability and the experience of the decision maker, in addition to the fact that the latter improves with age and experience. Intuition-based decision making is characterized by the use of internal hunches. The suggestions, influences, preferences and psychological format of the deciding individual plays a very important part; the subjective element is vital.
Good judgment is demonstrated through certain skills to perceive important information, weigh its importance and evaluate them, it is very likely that the decision maker is unconsciously influenced by past knowledge, training and background.
Usually the decision maker by intuition or good judgment is an activist, does not maintain a fixed pattern of decisions, moves very fast, incisively questions situations and finds unique solutions to difficult problems.
Facts: A decision must be based on adequate facts, it is widely accepted. When facts are used the decision has its roots, so to speak, in objective data, this implies that the premises on which the decision is based are solid and intensely applicable to the particular situation.
Information as a tool of the administration has acquired a high status. Activities in this area are well defined and use sophisticated techniques and equipment to a great extent.
Imagination, experience and convictions are usually required to interpret the facts from your own perspective and use them to your advantage.
Creativity: Creativity designates the decision maker's ability to uniquely combine or associate ideas to achieve a new and useful result. The creative decision maker is able to grasp and understand the problem more broadly, even to see the consequences that others overlook, however the greatest value of creativity is in the development of alternatives.
Quantitative bases:
This is the ability to employ techniques presented as quantitative methods or operations research, such as linear programming, waiting line theory, and inventory models. This tool helps managers to make effective decisions, but it is very important not to forget that quantitative skills should not and cannot replace good judgment in the decision-making process.
When using the quantitative approach, the analyst concentrates on the facts or quantitative data associated with the problem and develops mathematical expressions that describe the objectives, constraints, and relationships in the problem. Then, using one or more quantitative methods, the analyst offers a recommendation based on the quantitative aspects of the problem.
Reasons for the use of the quantitative method in the decision-making process.
- The problem is complex and the administrator cannot come up with a good solution without the help of quantitative analysis.
- The presence of a considerable number of variables. That the problem involves not only an individual, but a group or several. That the problem is subject to a high dynamic of changes. That there are many alternatives.
- The problem is very important, for example it is a large amount of money, and the administrator wants a full analysis before trying to make the decision. The problem is new and the administrator has no experience to build on. It is repetitive and the administrator saves time and effort by relying on quantitative procedures to make routine decisions.
Stages for the application of the quantitative analysis process.
The problem definition stage is the crucial component in determining the success or failure of any quantitative approach to decision making. It usually takes imagination, teamwork, and considerable effort to turn a somewhat general description of a problem into a well-defined problem that can be addressed quantitatively. For example, an overly defined excess inventory problem needs to be clearly defined in terms of specific objectives and operating constraints before the analyst can begin the quantitative analysis process.
To be successful in applying the quantitative method in decision making, the management scientist must work closely with the manager or administrator, or the user of the results. When the management scientist as the manager agrees that the problem has been adequately defined, the management scientist begins her work of developing a model that can be used to represent the problem in mathematical terms. Then you can develop solution procedures for the model in order to choose the decision that solves the problem in the "best way."
- First Step: Model Development.
This step implies the representation of the problem by means of a model, in the subject of study that concerns us, quantitative analysis, mainly mathematical modeling is used.
- Second Step: Data Preparation.
This step involves preparing the data required by the model. By data we mean the values of the uncontrollable inputs of the model. All uncontrollable inputs or data have to be specified before we can analyze the model and select a recommended decision or solution for the problem.
- Third Step: Solution of the Model.
Once the model has been developed and its data has been prepared, you can proceed to the model solution step. In this step, the analyst will try to identify the values of the decision variables that provide the best output for the model, which is called the optimal solution.
- Step Four: Report Generation.
The final step is the preparation of management reports based on the solution of the model that can be easily understood by the decision maker. It should include the recommended decision and any other information that is relevant to the results of the model and can therefore help the decision maker.
Classification of quantitative models for Decision Making
There are three model forms: representation through physical replicas of real objects known as iconic models, the second type are those that also have a physical form, but do not have the same appearance as a modeled object and are known as analog models, and the third form of models are those that represent a problem by a set of symbols and mathematical relations or expressions. These types of models are called mathematicians.
Almost all applications of quantitative methods take place in the context of mathematical models.
These models help to evaluate the cause-effect relationship, as well as to predict the relative effects of the different courses of action with measurable precision.
Some mathematical models are used to explain or predict the behavior of systems or administrative decisions. The challenge in constructing a useful model is to include what is relevant, to omit the irrelevant and to make this difference without excluding any important factor, that is, without making an "annihilating division."
An important classification of mathematical models is as follows:
Normative or prescriptive model: Indicates the course of action to be followed by the decision maker to reach the goal.
These models are mostly made up of three basic sets of elements:
- Decision variables and parameters Constraints Objective function
Descriptive model: This does not indicate the course of action to be followed but merely describes reality. An example of these are the queue and simulation models.
Mathematical models can be found in specialized literature classified as: deterministic, probabilistic, static, dynamic, continuous, discrete, linear, nonlinear, etc.
If it is regarding the type of application, you can find optimization models for production, transportation, location models, inventory, maintenance and replacement models, etc.
The following diagram shows a possible classification of quantitative models for decision making.
| Completely true | Risk | Extreme Uncertainty |
(All the information)
|
(Some information)
|
(No information)
|
Group decision making, advantages and disadvantages
Decision-making in modern organizations is carried out in groups or working committees, they are individualized at the time they become part of the well-structured or standard. These individual or group decisions each have their advantages and disadvantages, which have a decisive influence on the management role of our organizations.
Advantages of group work:
- More complete information and knowledge: Logically a group manages to collect more information, having access to more information sources than a single individual, independent of their education and experience. Therefore groups can offer greater contributions, both in quantity and diversity for Decision Making. Increase the acceptance of a solution or the variety of points of view: Many decisions fail after an opinion is chosen, due to that a sector of people does not accept it as a possible solution, each of its members has its own point of view that differs, to some extent, from the others, as a result, the number and types of options are greater than those of the individual who works alone. Group participation facilitates broad discussion and more participatory acceptance,It is possible that there are divergences in the agreements, but it arises and allows its discussion for when it is accepted, it is a commitment of a whole group.
It is difficult for discussion group attendees to attack or hinder a decision that they helped develop. Group decisions increase the acceptance of the final solution and facilitate its implementation.
- Increase legitimacy: Democratic methods are accepted by all components of society. When the process is group-based, all the elements of democratic ideals intervene. If the decision maker does not consult others before making one of them, the fact of his power does not exempt him from remaining as an authoritarian and arbitrary person. Group decisions do not have the magic wand of perfection, but they are undoubtedly the least dangerous and therefore the ones with the lowest level of error.Reduction of communication problems: Since the group participates in making decision, all its members are aware of the situation, in general the implementation of the solution is carried out smoothly. The questions,The objections and obstacles normally faced with the implementation of a decision often disappear when the latter is the result of group participation.
Disadvantages of group work :
- They require a lot of time: It takes time to gather the group, but with a good organization, the meetings will be scheduled in advance in a timely space (it varies according to the organization and should not be less than two weeks). The result is that groups consume more time to reach a decision than a single individual. Acceptance pressures: Although all group members are supposed to feel free to express their opinions, suggestions and recommendations, it is still Admittedly, there is sometimes some pressure for everyone to come together and abide by the general consensus, often called "group thinking." This pressure may cause the group to ignore positive advice or suggestion from some of those present.Nonconformists are pressured to conform and adhere to the majority opinion.
There are social pressures in the groups. The desire of the members of the group to be accepted and therefore to be protagonists, can result in an exchange of opinions conditioned to desires for a demonstration of leadership. Finally, the same result will be reached, which must necessarily be accepted by all to be valid.
- Ambiguous responsibility: The members of a group have to share the responsibility, therefore the individuality is diluted, giving great value to the results. The Commitment: On certain occasions the group stagnates and is unable to reach an agreement on what solutions to recommend. Forced to make a decision, members are encouraged to compromise or give up, accepting a different version of their solution. This drawback is very common when the group is subdivided into smaller groups, each of which supports a different solution.
How to make group decision making work?
Group decision making can be used very efficiently if the supervisor handles the situation as it should. One of the most important factors is winning the support of group members; pointing out the value of their contributions in solving the problem. A second very useful approach is to give each member of the group specific elements to think about and work on, so that they can recognize their contributions; also create an environment where people can express themselves openly and frankly and that encourages both creative input and discussions about any failures or mistakes that might be made. The latter is of special importance to prevent the emergence of Group Thought.
Decision trees. Structure. Solution methods
Decision Trees
A decision tree is a graphical and analytical way of representing all the events (events) that can arise from a decision made at a certain moment. They help us make the “most accurate” decision, from a probabilistic point of view, in the face of a range of possible decisions, and it also allows us to visually display a problem and organize the calculation work to be done.
Components and structure
- Decision alternatives at each decision point Events that can occur as a result of each decision alternative. They are also called states of nature. Chances of possible events occurring. Results of possible interactions between decision alternatives and events. They are also known by the name of
Decision trees have:
- Decision nodes - Uncertainty or probabilistic nodes - Branches (represented by lines)
Construction of a Decision Tree
- Nodes:
- Of Decision …………….. Of Events ……………..
They indicate the existence of events subject to uncertainty associated with investment alternatives.
- Branches:
- Those that start from the decision nodes represent investment alternatives or courses of action: The branches that start from the event nodes represent situations subject to uncertainty that have been quantified through the use of probabilities.
Steps for Decision Tree Analysis
- Define the problem Draw the decision tree Assign probabilities to random events Estimate the results for every possible combination of alternatives Solve the problem by obtaining as a solution the path that provides the optimal policy.
Purpose of the Decision Tree
- Show all the information about a problem graphically. Draw the schematic representation of the problem, making the information easier to understand. Simplify very complex probability calculations.
Important point
The most important part is usually to identify the different alternatives, the possible events that may influence the results and the probability of occurrence of these events.
summarizing
- Define the problem to be solved, that is, determine the set of alternatives and possible events and the sequence of decisions to be made. From this information, build the decision tree, which collects the decision process schematically and in a Gradually. Calculate for each terminal branch the monetary value associated with each result, which are based on the available economic data. Carry out the analysis of the tree following the corresponding methodology.
Advantage
- They pose the problem so that all options are analyzed. They allow to fully analyze the possible consequences of making a decision. They provide a scheme to quantify the cost of an outcome and the probability of it happening. It helps to make the best decisions based on the Existing information and best assumptions. Provides a highly effective structure within which you can estimate what the options are and investigate the possible consequences of selecting each one. It helps us make the best decisions based on existing information. and of the best assumptions.
Disadvantages
- It is only recommended for when the number of actions is small and not all combinations are possible. In choosing a model, there is a very limited number and makes it difficult to choose the optimal tree. It presents drawbacks when the number of alternatives is large and how much decisions are not rational. Lacking clarity of objectives, it is difficult to organize ideas.
Decision Tree Types
In case of certainty:
- The expected results for each option are known with certainty.
- There are no nodes of the states of nature.
In case of risk:
- The possible results are presented according to a probability since it cannot be stated with certainty.
Example in case of Risk:
A business owner wants to expand his production plant.
Currently he is analyzing two options: a large plant and a small one.
- The data you are considering for the analysis are:
| Demand Level Probabilities |
| High 0.40 |
| Moderate 0.35 |
| Low 0.25 |
Estimated costs
- Large Plant: $ 1,200,000 Small Plant: $ 500,000
Present value
| Demand Large Plant Small Plant |
| High $ 2,400,000 1,005,000 |
| Moderate 1,400,000 1,000,000 |
| Low 700,000 700,000 |
Potential return on investment (taking into account construction costs)
| Demand Large Plant Small Plant |
| High $ 1,200,000 505,000 |
| Moderate 200,000 500,000 |
| Low (500,000) 200,000 |
Approach
VME calculation
The Expected Monetary Value (VME) is calculated by multiplying, for each option, the Expected Benefit by its respective probability as shown in the following table.
| Demand Probability Large Plant Small Plant |
| High 0.40 $ 1,200,000 505,000 |
| Moderate 0.35 200,000 500,000 |
| Low 0.25 (500,000) 200,000 |
| MEV = 425,000 42,700 |
(Decision tree with results)
CONCLUSIONS
- Within the current economic environment, organizations are obliged to improve their decision-making processes day by day in order to strengthen their competitiveness, which is why they must support their analysis in mathematical methods and techniques which allow rational information processing to de In this way, the possibility of success in its decisions is increased. The construction and use of models allows the administration to reduce the complexity of a given problem and, based on the simulation of the models developed, the possible results can be foreseen in the event of variations in its components, allowing the decision maker to reasonably predict the possible results and to choose the alternative that optimizes the results.The application of quantitative techniques such as the Decision Tree can be very useful in the conditions of the Cuban economy to make scientific decisions, which raise the quality of the Decision-Making Process.
BIBLIOGRAPHY
- Analysis of Risky Decisions http://home.ubalt.edu/ntsbarsh/opre640S/SpanishP.htmCOHEN ASÍN, Information Systems for business. Third edition. Mc Graw Hill, SA México. Decisions under uncertainty risk analysis and Monte Carlo simulation. DICHTER ERNESTE, Are you a good manager? McGraw Hill Publishing. Latinoamericana, SAGIBSON IVANCEVICH DONELY, The Organizations. Eighth edition. McGraw Hill. Barcelona (Spain).GOMEZ CEJA GUILLERMO, Business Planning and Organization. Eighth Edition McGraw Hill. México.HALL RICHRD H., Organizations. Editorial Prentice-Hall Hispanoamérica, SA México.LEON ORFELIO, Making difficult decisions. Second edition. McGraw Hill Publishing. Madrid (Spain).MOODY PAUL E., Management decision making. McGraw Hill Publishing. Latin American, SAMURDICCK ROBERT,Administrative information systems. Prentice-Hall Publishing House. Hispanoamérica, SA México.TERRY & FRANKLIN, Principles of Administration. Editorial Pañazo SRL,
Caracas Venezuela.
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