MANAGEMENT PROCESS
H Ramasubramanian
Managerial decision making
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Managerial decision making -
Introduction
Managerial skill – Decision making
– the kinds of decisions you will face as a manager
– how to make “rational” decisions
– the pitfalls you should avoid when making decisions
– the pros and cons of using a group to make decisions
– the procedures to use in leading a decision-making group
– how to encourage creative decisions
– the processes by which decisions are made in organisations
– how to make decisions in a crisis
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Managerial decision making -
Introduction
Significance and limitations of rational decision making
• Decision-making is a common aspect of everyone's life.
• We are all making decisions and solving problems everyday.
• Rational decision-making is an essential aspect of management and managerial skills.
Importance of Rational Decision-Making
• Using rational decision-making and systematic approach enables managers to find superior quality
solutions to all problems.
• Rational decision-making provides clear idea of alternate means to attain a goal under a complex
situation.
• Under rational decision-making, managers use the available information to find solutions and
alternative means to achieve goals.
• The aim of rational decision-making is to find the best alternative solution that is highly effective in goal
attainment.
Limitations to Rational Decision-Making
• Future is uncertain and hence, managers cannot always use rational approach to decision-making.
• They need to take decisions keeping in mind the future trends.
• However, no one can predict the future rationally.
• It is also an extremely tough task to consider all possible alternative actions for goal accomplishment.
• When venturing into new markets and businesses, taking rational decisions is almost impossible.
• It many cases, one may not be able to assess all possible alternatives despite having computers,
internet and modern technology.
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Managerial decision making -
Introduction
Significance and limitations of rational decision making
• It is possible to overlook some methods and make mistakes while taking decisions.
• Even when managers try their best to make very rational decisions, they have limitations and face
restrictions of time, money and information.
• These limitations restrict the manager's ability of rational decision-making.
• Sometimes, risk-elimination strategies also interrupt rational decision-making ability.
• Most of the times, managers tend to settle with decisio ns that meet the purpose and fail to search for
all possible alternatives.
• An organisation's success largely depends on decision-making capability of the managers and top
management.
• Good decisions about planning, budgeting and organising are key aspects of success for any
organisation.
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Managerial decision making -
Managers as decision makers:
Managers as decision makers:
• Depends on the manager’s personal preference
• Whether the decision is programmed or non- programmed
• Extent to which the decision is characterised by risk, uncertainty, or ambiguity
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Rational
model
proposes that managers use a rational four-step approach to decision making.
Non rational
models
Attempt to explain how decisions are actually made
Decision making is uncertain
Decision makers do not possess complete information
Difficult for managers to make optimal decisions
Satisfying
model
rather than conducting an exhaustive search for the best possible alternative, decision
makers tend to search only until they identify an alternative that meets some minimum
Incremental
model
major decisions arise through a series of smaller decisions
piecemeal approach to larger solutions
Garbage can
model
decision making is sloppy and haphazard
decisions result from complex interaction of four independent streams of events:
problems, solutions, participants and choice opportunities
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Managerial decision making –
Decision making process
Decision making process:
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Choose among alternatives
Recognise the need for a
decision:
Managers must first realise that a decision must be made.
Sparked by an event such as environment changes.
Identify problem;
discrepancy between current state and:
past performance
currentperformance of other organisations
futureexpected performance
decision maker must want to resolve the problem and have the resources
to do so
Identify resources and
constraints;
The resources required to solve the problem
The availability of them
The time available to take a decision to solve the problem.
Generate alternative
solutions;
Managers must develop feasible alternative courses of action.
If good alternatives are missed, the resulting decision is poor.
It is hard to develop creative alternatives, so managers need to look for
new ideas.
•ready-made solutions- ideas that have been tried before
may follow the advice of others who have faced similar problem
•custom-made solutions- combining new ideas into solutions
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Managerial decision making -
Decision making process
Decision making process:
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Choose among alternatives
Evaluating alternatives;
• What are the advantages and disadvantages of each alternative?
• Managers should specify criteria, then evaluate.
• Determining the value or adequacy of the alternatives
• Predict the consequences that will occur if the various options are put
into effect
• Managers should consider several types of consequences
• Success or failure of the decision will affect the track record of the
decision maker
•Contingency plans- alternative courses of action that can be
implemented based on how the future unfolds
• Contingency plans are necessary to prepare for different scenarios
Selecting preferred
alternative;
•Maximise- a decision realising the best possible outcome requires
searching thoroughly for a complete range of alternatives
• Each alternative is carefully assessed
• Compare one alternative to another
•Satisfies- choose an option that is acceptable although not necessarily
the best or perfect
• Compare the choice with the goal, not against other options
• Search for alternatives ends when an okay solution is found
•Optimising- achieving the best possible balance among several goals
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Managerial decision making -
Decision making process
Decision making process:
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Implementing decision;
Those who implement the decision must:
•understandthe choice and why it was made
• be committedto its successful implementation
• can’t assume that things will go smoothly during implementation
•identify potential problems
•identify potential opportunities
• always expect the unexpected
Monitoring the decision.
• managers should consider what went right and wrong with the
decision and learn for the future.
• Without feedback, managers never learn from experience and
make the same mistake over.
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Managerial decision making –
Types of managerial decisions
Characteristics of managerial decisions:
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Lack of structure
• the usual state of affairs in managerial
decision making
programmed decisions–
• decisions that have been encountered and
made in the past
• have objectively correct answers
• are solvable by using simple rules, policies,
or numerical computations
nonprogrammer decisions–
• new, novel, complex decisions having no
proven answers
• decision maker must create or impose a
method for making the decision
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Managerial decision making –
Types of managerial decisions
Characteristics of managerial decisions:
• Uncertainty and risk
–certainty- have sufficient information to predict precisely the consequences of one’s actions
–uncertainty- have insufficient information to know the consequences of different actions
• cannot estimate the likelihood of various consequences of their actions
–risk- available information permits estimation of the likelihood of various consequences
• probability of an action being successful is less than 100 percent, and losses may occur
• good managers prefer to managerisk
Decisions and levels of management
• Decisions are made at all levels of the firm.
• Some decisions are very common and routine, but exceptionally valuable.
• Although the value of improving any single one of these decisions may be small, improving
hundreds of thousands of these small decisions adds up to a large annual value.
• There are four different decision-making constituencies in a firm:
• (1) senior management;
• (2) middle management and project teams;
• (3) operational management and project teams; and
• (4) individual employees.
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Managerial decision making –
Decisions and levels of management
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General, Broad scope,
Interactive, External,
Internal,
Real-time, Ad-hoc
Focused, Specified,
Interactive, Internal,
Real-time, Scheduled
Focused, Specified,
Interactive, Internal,
Real-time, Scheduled
Senior
Management
Middle
Management
Operational Management
Individual Employees and
teams
Unstructured Semi-structured StructuredDecision
Characteristics
Information Requirements
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Managerial decision making –
Decisions and levels of management
• Various levels of management in the firm have differing information requirements for decision
support because of their different job responsibilities and the nature of the decisions made at each
level.
• There are different types of decision-making at different levels.
• Decisions can be classified as structured, semi-structured, and unstructured.
•Unstructured decisionsare those in which the decision maker must provide judgment, evaluation,
and insights into the problem definition.
•Structured decisions, by contrast, are repetitive and routine, and decision makers can follow a
definite procedure for handling them to be efficient.
•Semi-structured decisionsare those in which only part of the problem has a clear-cut answer
provided by an accepted procedure. In general, structured decisions are more prevalent at lower
organisational levels, and unstructured decision making is more common at higher levels.
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Managerial decision making
- Decision making under certainly, risk, and uncertainty
• Decision making under certainty;
• Decision under risk;
• Decision under uncertainly:
Approaches:
• Risk analysis: All intelligent decision making dealing with uncertainty like to know the size and nature
of the risk they are taking in choosing of action.
– Identify and Quantify Uncertainty
– Compute the Impact of Uncertainty
– Complete a Risk Analysis Model
– Explore the Model with Simulation
– Analyse the Model Results
– Make Decisions to Better Manage Risk
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Weather changes
Different productivity
(Sub)contractors are
Unreliable
Lack capacity to do work
Lack availability to do work
Financially unstable
Late materials delivery
Lawsuits
Labor difficulties
Unexpected manufacturing costs
Failure to find sufficient tenants
Community opposition
Infighting & acrimonious relationships
Unrealistically low bid
Late-stage design changes
Unexpected subsurface conditions
Soil type
Groundwater
Unexpected Obstacles
Settlement of adjacent structures
High lifecycle costs
Permitting problems
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Managerial decision making
- Decision making under certainly, risk, and uncertainty
Preference/utility theory:
• Preference Theory or Utility theory is based on the notion that individual attitudes toward risk will
vary. Some individual are willing to take only sm aller risk than those indicated by probabilities and
others are willing to take greater risks.
• When individuals are faced with uncertainty they ma ke choices as is they are maximising a given
criterion: the expected utility.
• Expected utility is a measure of the individual's implicit preference, for each policy in the risk
environment.
• It is represented by a numerical value associated wit h each monetary gain or loss in order to indicate
the utility of these monetary values to the decision-maker.
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Managerial decision making
- Systems approach to decision making
Systems approach to decision making:
• There are four kinds of systems used to support the different levels and types of decisions:
• Specialised systems such as MIS, DSS, and ESS
• Work with these systems and technologies for data mining and online analytical processing (OLAP)
to focus on the specific decision needs of managers and employees
- Management Information Systems (MIS),
- Decision-Support Systems (DSS);
- Executive Support Systems (ESS); And
- Group Decision-Support Systems (GDSS).
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Managerial decision making
- Systems approach to decision making
Management Information System
Functional Perspectives of MIS:
• Help managers monitor and control a business
• Produce regular reports on performance, such as monthly or annual sales
• Sometimes highlight exceptional conditions
• Reports often available online
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Financial MIS
• Will integrate information from multiple sources
• Functions
- Costing
- P&L reporting
- Auditing
- Funds management
Manufacturing MIS
• Design and Engineering
• Master Production Scheduling
• Inventory Control
• Materials Planning
• Manufacturing and Process Control
• Quality Control
Marketing MIS • Market research
- Web-based market research
•Pricing
Transportation and Logistics MIS • Route and schedule optimisation
• Human Resources
• Accounting
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Managerial decision making
- Systems approach to decision making
Decision-Support Systems (DSS);
• Support semi-structured and unstructured problem analysis
• Characteristics
– Data from multiple sources internal and external to organisation
– Presentation flexibility
– Simulation and what-if capability
– Support for multiple decision approaches
– Statistical analysis
• Components of DSS
– DSS database
– DSS software system
– Models
– Sensitivity analysis
– DSS user interface
• Examples of DSS
– DSS for pricing decisions in FMCG & Pharma Companies.
– DSS for customer relationship management in Banks
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Managerial decision making
- Systems approach to decision making
Executive Support Systems (ESS);
• What information does a chief executive of board member require?
• High level with drill down
• Key business and industry data
• Structured and unstructured information
– Structured: orders
– Unstructured: Industry newsfeed
• Graphical
• Give senior executives a picture of the overall performance of an organisation
• Enable an executive to zoom in on details or zoom out for a broader view
• Drill down capability
• Digital dashboard
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Managerial decision making
– Group Decision Making
Group Decision-Support Systems (GDSS).
• Very interesting field
• How can information technology improve how decisions are made by groups?
• Interactive, computer-based systems that facilitates solving of unstructured problems by a set of
decision makers
Technical developments in electronic communication, computing, and decision support, coupled with
new interest on the part of organisations to improve meeting effectiveness, are spurring research in the
area of group decision support systems (GDSS).
• Used in conference rooms with special hardware and software
• Support increased meeting sizes with increased productivity
• Applications
– Where time is critical
– Where participants are geographically dispersed
– Where authority obstructs communication
– Military
– Business
– Government
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Managerial decision making
- Group Decision Making
• Common characteristics
– Meeting moderation/facilitation
– Signed and anonymous comments
– Structured deliberations
• Presentation period
• Comment period
• Automated collation of comments
• “Voting”
– Face-to-face and remote
• Some of the more common co-ordination methods:
1. Nominal Group technique
2. Delphi Technique
3. Arbitration
4. Issue-based information system
5. Nemawashi
Nominal Group technique
Works for group and committee structures and follow 4 step procedure
1. Each participant writes down ideas about what the decision should be.
2. In turn, each participant presents his or her ideas, which are recorded on a whiteboard.
3. No discussion occurs here. After all ideas are presented, participants may question others.
4. Each participant votes on each idea.
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Managerial decision making
- Group Decision Making
Delphi technique
• Essentially the same as nominal group technique except the participants never meet.
• Follow 5 steps
1. Assemble members
2. A survey instrument is used to collect initial input from members
3. Collect and analyse the results
4. A second survey is sent with a summary of the collective results. Members must respond.
• Step 1-4 are repeated until a consensus or majority view is reached.
Arbitration
• Most appropriate when the members represent opposing factors
• Participants agree that if mutually agreeable alternatives are not found, an outside arbitrator will get
involved.
• The arbitrator then selects the alternative he or she deems most appropriate.
– Could be a final single offer from each member submitted for arbitration.
Issue based information system
• A structured argumentation method
• An IBIS is represented as a graph with nodes and links.
• The IBIS begins with selection of a root issue node, then the various position nodes are linked to the
root.
• These position nodes are then evaluated based on the arguments attached to them.
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Managerial decision making
- Group Decision Making
Nemawashi (Widely used in Japan)
A 5 step approach
1. One or more members are designated as coordinators. The coordinators then select remaining
participants.
2. Coordinators construct a choice set and then experts rate the choices.
3. Coordinators selects a choice based on results in 2.
4. The alternative is circulated; the coordinator seeks consensus through persuasion and
negotiation.
5. If consensus is reached, coordinators circulate a document that member signs off on.
Significant research supports the following advantagesof GDSS:
- Adapting human factors for these technologies,
- Facilitating interdisciplinary collaboration, and
- Promoting effective organisational learning.
- More participation
- Group synergy
- Automated record keeping
- More structure in the meeting
- Higher group satisfaction with the meeting process.
- The new technology has enabled larger groups to meet, resulting in more information, knowledge,
and skills that are brought to bear to the task at hand.
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- Group Decision Making
Disadvantagesof GDSS:
- Slow Communication: Most people speak much faster than they type, and thus would usually prefer
a verbal environment
- Not all Tasks are Amenable to GDSSs: Group meetings which involve "one-to-many" communication
(for example, a leader lecturing to t he group) would not benefit from a GDSS.
- Only those tasks which require group members to exchange ideas or preferences efficiently ("many-
to-many") would benefit.
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– Decision Making Techniques
Marginal analysis;
• Optimising Behaviour on the part of a decision maker involves trying to maximise or minimise an
objective function.
• For a manager of a firm, the objective functionis usually profit, which is to be maximised.
• For a consumer, the objective function is the satisfaction derived from consumption of goods, which is
to be maximised.
• For a city manager seeking to provide adequate law
enforcement services, the objective function might be cost,
which is to be minimised. For the manager of the marketing
division of a large corporation, the objective function is usually
sales, which are to be maximised. The objective function
measures whatever it is that the particular decision maker
wishes to either maximise or minimise.
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- Decision Making Techniques
Breakeven analysis;
It is necessary for a firm to plan its profit.
So it should understand the relationship of Cost, Price, and Profit.
The most important method of determining is Break-Even Analysis.
• Break Even Point = Total Revenue – Total Cost i.e No – Profit -- No loss Point
Assumptions of Break-Even Analysis
• Fixed costs are constant, only variable costs change.
• The Firm produces only one product.
• Selling price remains constant, does not change with volume of scale.
• Constant-technology
• Costs and revenue change with changes in sales volume
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Formula:-
BEP=
Fixed costs
Selling Price - Variable Costs per unit
Example:
If
Fixed costs = Rs10,000
Selling Price = Rs 5 P.U
Variable Costs = Rs 3 P.U
10,000
BEP= ----------
5 -- 3
BEP = 5000 units
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- Decision Making Techniques
Ratio analysis;
• Many of the things you can count, don’t count. Many of the things you can’t count, really count.” –
Albert Einstein
• Ratio Analysis is used by YOU the manager, as a tool for analysing and judging the financial
performance of a business.
• You do this by calculating financial ratios from a company’s final accounts (the balance sheet and the
P&L account.)
– How the business is performing based on the ratios.
– How the business has performed over the years.
– What else needs to be considered that is not presented in the data.
• Has several purposes:
– To analyse short and long term liquidity.
– To asses a firm's ability to control expenses.
– To compare actual figures with projected ones.
– To help in the decision making process.
• Should investors risk their money in the business.
• Ratios can be compared in two ways:
– 1. Historical comparisons
– 2. Inter-firm comparisons (In the same industry; McDonald’s should compare their ratios with
rivals of similar size, like Burger King.)
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- Decision Making Techniques
• Five types of ratios: • 1. Profitability ratios:
– Assess the financial performance of a business.
– Will show how well a firm has performed.
• 2. Liquidity ratios:
– Looks at the ability of a firm to pay its short-term liabilities.
– The firm’s ability to repay its debts.
• 3. Efficiency ratios:
– Shows how well a firm’s resources are being used.
• 4. Shareholder ratios:
– Measures the returns to shareholders in a company.
– Shareholders will be interested in earnings per share.
• 5. Gearing ratio:
– Looks at the long-term liquidity position of a firm.
• A high degree of gearing could mean a inadequate long-term liquidity because the firm
must repay its loans.
• If a firm is highly geared it will be considered a risky business.
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- Decision Making Techniques
O.R. techniques:
• An operation may be defined as the set of acts required for the achievements of a desired
outcomes.
• O.R. Is an aid for the executive in making his decisions by providing him with the needed
quantitative information based on the scientific method of analysis
• Characteristics of OR
– Its system oriented – Use of interdisciplinary team – Application of scientific methods
– Uncovering of new problems
– Improve the quality of decisions
– Use of computers
– Quantitative solution
– Human factors
• Difficulty in O.R.
– Problem formulation
– Data collection
– Study based on observation or old laws
– Time factor
– Human factor
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- Decision Making Techniques
O.R. techniques:
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Optimal allocation of limited resources such as men, machine, and material.
Location and size of warehouses, distribution centre, retail depot etc.
Distribution policy.
Selection, location and design of production plant.
Project scheduling & allocation of resources.
Forecasting.
Maintenance policy.
Scheduling & sequencing.
What, when and how to purchase at minimum procurement cost
Bidding and replacement policies.
Product selection, timing & competitive action
Selection of advertising media.
Demand forecast and stock level.
Customer’s preference for size, colour & packaging of various products.
Capital requirement, cash flow analysis.
Credit policies, credit risks etc.
Profit plan of the company.
Determination of optimum replacement policies.
Selection of personnel, determination of retirement age and skills
Recruitment of policies & assignments of jobs.
Determination of areas of research and development
Reliability & control of development of projects.
Selection of projects & preparation of their budgets.
Vii. Research and
development:
Scope of Operation Research
I. Allocation and
distribution:
Ii. Production and
facility planning:
Iii. Procurement:
Iv. Marketing:
V. Finance:
Vi. Personnel:
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Decision Making Techniques
Linear programming
• LP is a mathematical method for determining a way to achieve the best outcome (such as maximum
profit or lowest cost) in a given mathematical model for some list of requirements represented as
linear relationships.
• Linear programming is a specific case of mathematical programming (mathematical optimisation).
• More formally, linear programming is a technique for the optimisation of a linear objective function,
subject to linear equality and linear inequality constraints.
• Standard form
•Standard formis the usual and most intuitive form of describing a linear programming problem. It
consists of the following three parts:
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The
problem is usually expressed in matrix form,
and then becomes:
A linear function to be maximized
Problem constraints of the following form
Non-negative variables
e.g.
e.g.
e.g.
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Decision Making Techniques
Queuing theory:
•Queuing theoryis the mathematical study of waiting lines, or queues.
• In queuing theory a model is constructed so that queue lengths and waiting times can be predicted.
• Queuing theory is generally considered a branch of operations research because the results are
often used when making business decisions about the resources needed to provide a service.
• Various scheduling policies can be used at queuing nodes
• First in first out
– This principle states that customers are serv ed one at a time and that the customer that has
been waiting the longest is served first.
• Last in first out
– This principle also serves customers one at a time, however the customer with the shortest
waiting time will be served first
• Processor sharing
– Service capacity is shared equally between customers
•Priority
– Customers with high priority are served first.
– Priority queues can be of two types,
• non-preemptive (where a job in service cannot be interrupted) and
• preemptive (where a job in service can be interrupted by a higher priority job).
• No work is lost in either model.
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Queuing,
• Shortest job first
– The next job to be served is the one with the smallest size
• Preemptive shortest job first
– The next job to be served is the one with the original smallest size
• Shortest remaining processing time
– The next job to serve is the one with the smallest remaining processing requirement.
Game theory:
•It is a study of strategic decision making.
• More formally, it is "the study of mathematical models of conflict and cooperation between intelligent
rational decision-makers".
• An alternative term suggested "as a more descriptive name for the discipline" is interactive decision
theory.
• Game theory is mainly used in economics, political science, and psychology, as well as logic and
biology.
• The subject first addressed zero-sum games, such that one person's gains exactly equal net losses
of the other participant(s).
• Today, however, game theory applies to a wide range of behavioural relations, and has developed
into an umbrella term for the logical side of decision science, to include both human and non-
humans, like computers.
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Game theory,
• Theory of expected utility, which allowed mathematical statisticians and economists to treat
decision-making under uncertainty.
• This theory was developed extensively in the 1950s by many scholars.
• Game theory was later explicitly applied to biology in the 1970s, although similar developments go
back at least as far as the 1930s.
• Game theory has been widely recognized as an important tool in many fields.
• Eight game-theorists have won the Nobel Memorial Prize in Economic Sciences, and John Maynard
Smith was awarded the Crawford Prize for his application of game theory to biology.
•Representation of games
• The games studied in game theory are well-defined mathematical objects.
• To be fully defined, a game must specify the following elements: the playersof the game, the
informationand actionsavailable to each player at each decision point, and the payoffsfor each
outcome. (Rasmusen refers to these four "essential elements" by the acronym PAPI.)
• A game theorist typically uses these elements, along with a solution concept of his choosing, to
deduce a set of equilibrium strategies for each player such that, when these strategies are
employed, no player can profit by unilaterally deviating from his strategy. These equilibrium
strategies determine an equilibrium to the game—a stable state in which either one outcome occurs
or a set of outcomes occur with known probability.
• Most cooperative games are presented in the characteristic function form, while the extensive and
the normal forms are used to define non-cooperative games.
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Game theory,
Extensive form
• The extensive form can be used to formalize games with a time sequencing of moves.
• Games here are played on trees
• Here each vertex (or node) represents a point of choice for a player.
• The player is specified by a number listed by the vertex.
• The lines out of the vertex represent a possible action for that player.
• The payoffs are specified at the bottom of the tree.
• The extensive form can be viewed as a multi-player generalization of a decision tree.
• In the game pictured, there are two players.
•Player 1moves first and chooses either For U.
•Player 2sees Player 1's move and then chooses Aor R.
• Suppose that Player 1chooses Uand then Player 2chooses A, then Player 1gets 8 and Player 2
gets 2.
• The extensive form can also capture simultaneous-move games and games with imperfect
information.
• To represent it, either a dotted line connects different vertices to represent them as being part of the
same information set (i.e., the players do not know at which point they are), or a closed line is drawn
around them.
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Decision Making Techniques
Game theory,
Normal form
• The normal (or strategic form) game is usually represented by a matrix
which shows the players, strategies, and pay-offs.
• More generally it can be represented by any function that associates a
payoff for each player with every possible combination of actions.
• In the example there are two players; one chooses the row and the other chooses the column.
• Each player has two strategies, which are specified by the number of rows and the number of
columns.
• The payoffs are provided in the interior.
• The first number is the payoff received by the row player (Player 1 in our example);
• The second is the payoff for the column player (Player 2 in our example).
• Suppose that Player 1 plays Upand that Player 2 plays Left.
• Then Player 1 gets a payoff of 4, and Player 2 gets 3.
• When a game is presented in normal form, it is presumed that each player acts simultaneously or, at
least, without knowing the actions of the other.
• If players have some information about the choices of other players, the game is usually presented
in extensive form.
• Every extensive-form game has an equivalent normal-form game, however the transformation to
normal form may result in an exponential blow-up in the size of the representation, making it
computationally impractical.
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Decision Making Techniques
Simulation:
• It plays an important role in decision making.
• It is imitation of some real thing, or a process.
• The act of simulating something generally involves representation of certain
– key characteristics or
– behaviours
of a selected physical or abstract system.
• Simulation involves the use of models to represent real life situation.
• A simulation model is a mathematical model that calculates the impact of uncertain inputs and
decisions we make on outcomes that we care about, such as profit and loss, investment returns,
etc.
A simulation model will include:
– Modelinputsthat are uncertain numbers/ uncertain variables
– Intermediate calculations as required
– Modeloutputsthat depend on the inputs -- These are uncertain functions
• Simulation techniques can be used to assist management decision-making, where analytical
methods are either not available or inappropriate.
• Typical business problems where simulation could be used to aid management decision-making are
– Inventory control.
– Queuing problems.
– Production planning.
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Simulation,
• For queuing systems, it is usually not possible to develop analytical formulas, and simulation is often
the only means of analysis.
• Simulation can hence be used to investigate problems that are common in any situation involving
customers, items or orders arriving at a given point, and being processed in a specified order.
• For ex:
– Customers arrive in a bank and form a single queue, which feeds a number of service desks.
The arrival rate of the customers will determine the number of service desks to have open at
any specific point in time
• A queue system can be divided into four components
– Arrivals: Concerned with how items (people, cars etc) arrive in the system.
– Queue or waiting line: Concerned with what happens between the arrival of an item requiring
service and the time when service is carried out.
– Service: Concerned with the time taken to serve a customer. – Outlet or departure: The exit from the system.
• A queuing problem involves striking a balance between the cost of making reductions in service time
and the benefits gained from such a reduction
• There are a number of structures of queuing systems in practice.
• We will study only one i.e. single queue – single service point.
– Single queue – single service point
– Queue discipline is first come – first served.
Refer the handout for example.
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Decision Making Techniques
Decision Tree:
• It is a decision support tool that uses a tree- like graph or model of decisions and their possible
consequences, including chance event outcomes, resource costs, and utility. It is one way to display
an algorithm.
• Decision trees are commonly used in operations research, specifically in decision analysis, to help
identify a strategy most likely to reach a goal.
• Decision Tree is a flow-chart like structure in wh ich internal node represents test on an attribute,
each branch represents outcome of test and each leaf node represents class label (decision taken
after computing all attributes).
• A path from root to leaf represents classification rules.
• In decision analysis, a decision tree and the closely related influence diagram is used as a visual
and analytical decision support tool, where the expec ted values (or expected utility) of competing
alternatives are calculated.
• A decision tree consists of 3 types of nodes:
– Decision nodes - commonly represented by squares
– Chance nodes - represented by circles
– End nodes - represented by triangles
• Decision trees are commonly used in operations research, specifically in decision analysis, to help
identify a strategy most likely to reach a goal.
• If in practice decisions have to be taken on line with no recall under incomplete knowledge, a
decision tree should be paralleled by a probability model as a best choice model or online selection
model algorithm.
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Managerial decision making -
Decision Making Techniques
Decision Tree:
• Another use of decision trees is as a descriptive means for calculating conditional probabilities.
• Decision trees, influence diagrams, utility functions, and other decision analysis tools and methods
are taught to undergraduate students in schools of business, health economics, and public health,
and are examples of operations research or management science methods.
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