18ME56-OM_ Module 1-Curriculum COs Mapping.pdf

Dept. of ME, JSSATE, Bengaluru 1

I Can't Keep Calm Because I Am An
Operations Management Trainee
- Camila Cooper

Service Vs. Manufacturing
3
Dept. of ME, JSSATE, Bengaluru
Manufacturing and Service Organizations differ chiefly because manufacturing
is goods-oriented and service is act-oriented.
Tangible Act-Oriented
Goods Services
(Stevenson, W. J (2018). Operations Management)

Service Vs. Manufacturing
4

Service & Manufacturing - Similarities
5
• Both have customers, suppliers, scheduling and
staffing issues
• Both use technology
• Both have quality, productivity, & response
issues
• Both must forecast demand
• Both can have capacity, layout, and location
issues

Operations Management
• Course code: 18ME56
• Lecture hours/week: 3 (No. of credits = 3)
• CIE marks: 30 (blue book) + 10 (activity) = 40
• Number of CIEs: 3
• Final CIA marks: Average marks of three blue book
tests + Activity marks
• Minimum marks to be obtained: 16
• CIE duration: 1.5 hour
• SEE marks: 100 (5 questions, each 20 marks)
• SEE duration: 3 hours
6

Curriculum
7

Module – 1:
• Introduction: Functions within business
organizations, the operation management
function, classification of production systems,
Productivity, factors affecting productivity.
• Decision Making: The decision process,
characteristics of operations decisions, use of
models, decision making environments,
graphical linear programming, analysis and
trade-offs.
(8 hours)
8

Module – 2:
• Forecasting:
• Steps in forecasting process, approaches to
forecasting, forecasts based on judgment
and opinion, analysis of time series data,
accuracy and control of forecasts, choosing
a forecasting technique, elements of a
good forecast.
(8 hours)
9

Module – 3:
• Capacity & Location Planning:
• Importance of capacity decisions, defining and
measuring capacity, determinants of effective capacity,
determining capacity requirement, developing capacity
alternatives, evaluating alternatives.
• Need for location decisions, nature of locations
decisions, general procedure for making locations
decisions, evaluating locations decisions, facilities
layout – need for layout decisions, types of processing.
(8 hours)
10

Module – 4:
• Aggregate Planning
• Nature and scope of aggregate planning,
strategies of aggregate planning, techniques for
aggregate planning – graphical and charting
techniques, mathematical techniques.
• Master Scheduling
• The master production schedule, Master
scheduling process, Master scheduling methods.
(8 hours)
11

Module – 5:
• Material Requirement Planning (MRP):
• Dependent versus independent demand, an
overview of MRP – MRP inputs and outputs, MRP
processing, ERP capacity requirement planning,
benefits and limitations of MRP.
• Purchasing and Supply Chain Management (SCM):
• Introduction, Importance of purchasing and SCM,
the procurement process, Concept of tenders,
Approaches to SCM, Vendor development.
(8 hours)
12

Books Prescribed:
Text Books:
• Operations Management, William J Stevenson, Latest Ed., Tata McGraw Hill.
• Operations Management, David A Collier, James R Evans, Kunal Ganguly,
Cengage Learning India Pvt. Limited, 3rd Edition, 2016,
• Reference Books:
• Lee J Krajewski, Larry P Ritzman and Manoj Malhotra, Operations
Management – Processes and Supply Chain, Pearson Education Asia, 11th Edn,
2010
• R. Paneerselvam, Production and Operations Management, PHI, 2nd Edn, 2006
• B. Mahadevan, Operations Management – Theory and Practice, PHI, 2010, 2nd
Edn.
13

Course Outcomes:
At the end of this course, you will be able to:
CO# Course Outcome
Bloom’s
Level
1
Apply the necessary tools for decision making in operations
management.
3
2
Examine various approaches for forecasting the sales demand
for an organization.
4
3
List various capacity and location plans to determine the suitable
capacity required for meeting the forecast demand of an
organization.
4
4
Analyse the aggregate plan and master production schedule for
an organization, given its periodic demand.
4
5 Apply MRP, purchasing and SCM techniques into practice. 3
14

Bloom’s Learning Levels - Revised
15

Bloom’s Taxonomy- Revised
16

POs->
COs
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2
CO1 3 3 2 - - - - 2 - 2 2 - - -
CO2 3 3 3 - - - - 2 - 2 2
CO3 3 3 3 - - - - 2 - 2 2
CO4 3 3 3 - - - - 2 - 2 2
CO5 3 3 3 - - - - 2 - 2 2
Avg. 3 3 2.80 2 2 2
Mapping of COs with POs & PSOs
17

Justification of COs with POs and PSOs
• CO1-PO1: Use of decision making tools such as break-even analysis,
linear programming, statistical analysis, simulation, etc. demands a
strong knowledge of mathematics, science and engineering
fundamentals.
• CO2-PO1: Forecasting models are basically mathematical equations.
Formulating these models and solving them requires skill and a strong
knowledge of mathematics, science, engineering & management
fundamentals.
• CO3-PO1: Facility location and Capacity planning can be made by the
use various mathematical models. Use of these models and solving
them subsequently for arriving at a decision demands skill and
knowledge on mathematics, science, engineering & management
fundamentals.
• CO4-PO1: Preparation of aggregate plans and master schedule in an
organization requires a strong background of mathematics, science,
engineering & management fundamentals.
18

Program Outcomes
• PO1. Engineering knowledge: Apply the knowledge of mathematics,
science, engineering fundamentals, and an engineering specialization to
the solution of complex engineering problems.
• PO2. Problem analysis: Identify, formulate, review research literature,
and analyze complex engineering problems reaching substantiated
conclusions using first principles of mathematics, natural sciences, and
engineering sciences.
• PO3. Design/development of solutions: Design solutions for complex
engineering problems and design system components or processes that
meet the specified needs with appropriate consideration for the public
health and safety, and the cultural, societal, and environmental
considerations.
• PO4. Conduct investigations of complex problems: Use research-based
knowledge and research me thods including design of experiments,
analysis and interpretation of data, and synthesis of the information to
provide valid conclusions.
19

Program Outcomes
• PO5. Modern tool usage: Create, select, and apply appropriate
techniques, resources, and modern engineering and IT tools
including prediction and modeling to complex engineering
activities with an understanding of the limitations.
• PO6. The engineer and society: Apply reasoning informed by the
contextual knowledge to assess societal, health, safety, legal and
cultural issues and the consequent responsibilities relevant to the
professional engineering practice.
• PO7. Environment and sustainability: Understand the impact of
the professional engineering solutions in societal and
environmental contexts, and demonstrate the knowledge of, and
need for sustainable development.
• PO8. Ethics: Apply ethical principles and commit to professional
ethics and responsibilities and norms of the engineering practice.
20

Program Outcomes
• PO9. Individual and team work: Function effectively as an
individual, and as a member or leader in diverse teams, and in
multidisciplinary settings.
• PO10. Communication: Communicate effectively on complex
engineering activities with the engineering community and with
society at large, such as, being able to comprehend and write
effective reports and design documentation, make effective
presentations, and give and receive clear instructions.
• PO11. Project management and finance: Demonstrate knowledge
and understanding of the engineering and management principles
and apply these to one’s own work, as a member and leader in a
team, to manage projects and in multidisciplinary environments.
• PO12. Life-long learning: Recognize the need for, and have the
preparation and ability to engage in independent and life-long
learning in the broadest context of technological change.
21

Program Specific Outcomes
• PSO1: Apply the acquired knowledge in design,
thermal, manufacturing and interdisciplinary areas
for solving industry related problems.
• PSO2: Solve complex Mechanical Engineering
problems using appropriate software tools.
22

• Operations
• A set of activities that serve a purpose (result).
• Processes that either provide services or create goods.
• Take place in businesses such as restaurants, retail
stores, supermarkets, factories, hospitals, and colleges
and universities.
• Are the core of what a business organization does.
• Operations Management
• The management of systems or processes that create
goods and/or provide services.
23

24
• OM Transforms inputs to outputs
– Inputs are resources such as
• People, Material, and Money
– Outputs are goods and services
(Source: OM by Reid & Sanders)
• Concerned with converting a set of resources
into goods and services as efficiently as possible
to maximize the profit of an organization.

26
OM’s Transformation Process
(Source: OM by Reid & Sanders)
Value addition is the net increase between output product
value and input material value.
Efficient transformation is performing activities at the least
possible cost

27
OM’s Transformation Process – Ex. 1
Materials
Machines
Human resource
Money
Design & Draft
Cutting
Machining
Assembling
Painting
Quality assurance
Inputs Outputs
Transformation Process

28
OM’s Transformation Process – Ex. 2
Students with
raw but …
Teachers
Teaching aids
Classrooms &
other facilities
Teaching-Learning
Tests / Assignments
/ Seminars /
Projects
SEEs
Extracurricular
activities
Inputs Outputs
Transformation Process

https://www.youtube.com/watch?v=nG5-52a5lRo
https://www.youtube.com/watch?v=FbbGlVle3oU
https://www.youtube.com/watch?v=_VJkKZFuRvE
29

Operations Manager
• Operations managers are the improvement
people, the realistic, hard-nosed, make-it-work,
get-it-done people; the planners, coordinators,
and negotiators.
• They perform a variety of tasks in many different
types of businesses and organizations.
• Examples..
30

Operations Manager
• Operations managers plan and make decisions.
• Select the best possible alternatives that can have quite
different impacts on costs or profits.
• Some of the key decisions operations managers make:
• What: What resources will be needed, and in what amounts?
• When: When will each resource be needed? When should the
work be scheduled? When should materials and other supplies
be ordered? When is corrective action needed?
• Where: Where will the work be done?
• How: How will the product or service be designed? How will
the work be done (organization, methods, equipment)? How
will resources be allocated?
• Who: Who will do the work?
31
Costs
(budget),
Quality
and
Schedules
(time)
Source: OM by W J Stevenson

• The evolution of the name:
• Production Management
• Production and Operations Management
• Production/Operations Management
• Operations Management
32

Production Management Vs. Operations
Management
Meaning
Managing production-related activities of an
organization
Managing routine business activities of an
organization related to creation of products
as well as to the delivery of services
Scope
Limited to the production of goods; taking
decisions on quality, quantity, design and
pricing of the product being developed
Wider scope; management of routine
business activities, such as product quality,
design, quantity, storage, workforce
requirement, etc.
Focus
Offering the right quality of products at the
right time, in the right quantity and at the
right price.
Efficient and effective use of organizational
resources
Organization where it is prevalent
Organizations where products are created All types of organizations, such as service-
oriented firms, banks, manufacturing
companies, hospitals, etc.
https://www.termscompared.com/difference-between-operations-
management-and-production-management/

Operations Management - Evolution
Source: OM by Russel & Taylor

Operations Management - Evolution

Operations Management – Why study?
• Every aspect of business affects or is affected by operations.
• Many service jobs are closely related to operations
– Financial services
– Marketing services
– Accounting services
– Information services
• There is a significant amount of interaction and collaboration
amongst the functional areas.
• It provides an excellent vehicle for understanding the world
in which we live.
36

Functions within business organizations
37
A retail store, a hospital, a manufacturing firm, a car wash, or some
other type of business.

• Finance
• Responsible for securing financial resources at favorable prices
and allocating those resources throughout the organization;
• Budgeting, analyzing investment proposals;
• Providing funds for operations.
• Marketing
• Responsible for assessing consumer wants and needs;
• Selling and promoting the organization’s goods or services.
• Operations
• Responsible for producing the goods or providing the services
offered by the organization.
• Examples..
38
Functions within business organizations

• A system is an arrangement or assembly of inter-dependent
processes (activities) that are based on some logic and
objectives.
• A system operates as a whole and is designed (built) with an
intention to achieve (fulfill) some objective or do some work.
• Manufacturing is a huge system consisting of many
subsystems and activities that turn out useful outputs.
• A production system is a subsystem of manufacturing system
that includes all functions required to design, produce,
distribute and service a manufactured product.
• Elements of a production system are: inputs, transformation
and outputs.
• A production system may be intermittent or continuous.
39
Production Systems

40
Classification of production systems

41

42

• Job-Shop Production System
• A high variety of products and low volume.
• Use of general-purpose machines and facilities.
• Highly skilled operators who can take up each job as a challenge because
of uniqueness.
• Large inventory of materials, tools, parts.
• Batch Production System
• Shorter production runs.
• Plant and machinery are flexible.
• Plant and machinery set up are used for the production of the item in a
batch and change of set up is required for processing the next batch.
• Manufacturing lead-time and cost are lower as compared to job order
production. 43
Musical instruments, Body parts, Aircrafts

• Mass Production System
• Standardization of product and process sequence.
• Dedicated special purpose machines having higher production capacities
and output rates and hence a large volume of products.
• The shorter cycle time of production.
• Lower in process inventory.
• Perfectly balanced production lines.
• Continuous Production System
• Dedicated plant and equipment with zero flexibility.
• Material handling is fully automated.
• The process follows a predetermined sequence of operations.
• Component materials cannot be readily identified with the final product.
• Planning and scheduling is a routine action.
44
Food,
energy,
Fuel,
etc.
Automobiles, Footwear, Chocolates

• The state or quality of being productive
• The effectiveness of productive effort, especially
in industry, as measured in terms of the rate of
output per unit of input.
• The output of an industrial concern in relation to
the materials, labour, etc. it employs.
• Example … (land, crop, typist, etc.)
• Ratio of output to inputs
45
Productivity
One
acre
of
land
that
produces
10
pumpkins?

• A measure of the effective use of resources, usually expressed as
the ratio of output to input.
• An index that measures output (goods and services) relative to
the input (labor, materials, energy, and other resources) used to
produce it.
• Ratio of output to inputs,
• For a nation / organization, productivity growth is the relative
change in the productivity in the current period relative to
previous period.
46
Productivity

• Types (Computing Productivity)
• Total productivity
• Multifactor productivity
• Partial productivity
• The choice of productivity measure depends
primarily on the purpose of the measurement.
• For ex., If the purpose is to track improvements
in labor productivity, then labor becomes the
obvious input measure.
Productivity

• Types (Computing Productivity)
Productivity

• Determine the productivity for these cases:
a) Four workers installed 720 square yards of carpeting in
eight hours.
b) A machine produced 70 pieces in two hours. However,
two pieces were unusable.
Computing Productivity

b) A machine produced 70 pieces in two hours. However,
two pieces were unusable.

• Determine the multifactor productivity for the combined
input of labor and machine time using the following
data:
• Output: 7,040 units;
• Input: Labor: $1,000; Materials: $520; Overhead: $2,000

• A bank through its five tellers served a total 1497
customers during the past week. The bank works 5
days/week and the business hours are 10:30 am – 02:30
pm. Compute the productivity measure of its tellers.
• Soln.:
• No. of business hours / day / teller = 4
• Total no. of business hours / day = 5 x 4 = 20
• Total no. of business hours / week = 5 x 20 = 100
• Productivity = (No. of customers served / week) / (No. of
hours tellers worked/week)
= 1497 / 100 = 14.97 or 15 customers / hour

• An organization can use productivity
measures to
• compare its performance with that of
competitors,
• assess the relative performance of its
individual departments,
• compare the relative benefits of various
inputs,
• plan the most effective use of resources.
Why Productivity is Measured?

• Generally, methods, capital, quality, technology and management
affect productivity.
• A misconception is that workers are the main determinant of
productivity. Hence, organizations insist their employees to work
harder.
• The fact is that many productivity gains in the past have come
from technological improvements.
• However, technology alone won’t guarantee productivity gains; it
must be used wisely and thoughtfully.
• Current productivity pitfall results from employees’ use of
computers or smartphones for nonwork-related activities (playing
games or checking stock prices or sports scores on the Internet or
smartphones, and texting friends and relatives).
Factors Affecting Productivity

• Capital/Labour Ratio: is a measure of whether enough investment
is made in plant, machinery, tools, etc. to make effective use of
labour hours.
• Scarcity of some resources: such as energy, water, materials,
skilled labours, etc.
• Work-force changes is steady shift of from blue-collar occupations
to….
• Innovation and technology: will be developed if enough
investment is made in R & D; Strong patenting rules are required.
• Regulatory effects: sometimes, impose substantial constraints
(pollution, health, safety, labour benefits, etc.).
• Bargaining power: of organized labour to command wage increase.
• Quality of work life describes the organizational culture -
motivation to employees for teamwork, commitment, loyalty, etc.
Factors Affecting Productivity
Source: Joseph Monks, OM, 1987

• (Personal)
• Do Your Heavy Lifting When You're at Your Best. ...
• Stop Multitasking. ...
• Prepare a To-Do List Each Night. ...
• Cut Down Your To-Do List. ...
• Delegate Properly. ...
• Eliminate Distractions. ...
• Plan Phone Calls. ...
• Break up Work Periods.
Methods to Increase Productivity

• Strategies
• Increased output for the same input.
• Decreased input for the same output.
• Proportionate increase in the output is more than the
proportionate increase in the input.
• Proportionate decrease in the input is more than the
proportionate decrease in the output.
• Simultaneous increase in the output with decrease in the
input.
Methods to Increase Productivity
Source: R. Panneerselvam, POM, 2012

Part – 2:
Decision Making
58
• He who has a choice has trouble.
• Every decision ever taken is born out of choices.

• A process of consciously choosing an alternative among
the several available.
• Decision making is one of the most important basic
management skills for all of us. It is a cognitive ability. It
can differ from person to person.
• Decisions should neither be taken in haste nor be
procrastinated indefinitely.
• Making a decision which is timely and which is based on
careful analysis of various information is critical for an
operations manager.
Decision Making

Decision Making Process
https://www.umassd.edu/fycm/decision-making/process/

• 1. Identify the decision to be made
• What is the problem on hand?
• What is the objective to be achieved?
• How will the decision impact people or the organization?
• Urgency and criticality of the decision
• 2. Gather relevant information
• What information is needed?
• The best sources of information
• How to get it?
• Involves both internal and external “work.”
• Internal: a process of self-assessment.
• External: obtained online, in books, from other people, and from
other sources.

• 3. Identify the options
• Information collected helps identifying several possible paths of
action or alternatives.
• Imagination and additional information to construct new
alternatives may also be used.
• All possible and desirable alternatives are to be listed.
• 4. Weigh or Evaluate the evidence of each alternative
• Evaluate whether the need identified in Step 1 would be met or
resolved through the use of each alternative.
• Certain options seem favorable, have a higher potential for
reaching the goal.
• Place the alternatives in a priority order, based upon your own
value system.

• 5. Choose among alternatives
• After weighing the evidences, select the alternative that seems to
be best one for you.
• A combination of alternatives may also be chosen.
• The selected alternative may very likely be the same or similar to
the alternative that is placed at the top of the list at the end of
Step 4.
• 6. Implement the chosen alternative (Take action)
• Implement the actions associated with the alternative or option
being selected.
• 7. Analyse the results
• Evaluate whether or not the chosen option has resolved the need
identified in Step 1. If not, certain steps may be repeated.

• Operations decisions range from simple judgments to
complex analyses (these may also involve judgments).
• Judgmental decisions are made by basic knowledge,
experience and common sense.
• Both subjective and objective data is used to arrive at a
choice.
• The decisions are characterized by
– The significance of the decision being made
– The time and cost involved (limitations)
– The degree of complexity of the decision being made
Characteristics of Operations Decisions

• Significant (or long-lasting) decisions deserve more
consideration than trivial or routine one. Ex., medical
products, investment in new plant, etc.
• Time availability and cost analysis
• Decision complexity increases when a) many variables
are involved, b) the variables are highly interdependent
or sequentially related, and c) the data describing the
variables are incomplete or uncertain.
• Example: new factory location decisions (involve
economical, social, and environmental concerns; cost on
technology and amount of automation).
Characteristics of Operations Decisions

• Degree of certainty that exist with respect to the decision
variables and possible outcomes.
Decision Making Environment
Complete
Certainty
Complete
Uncertainty
Risk &
Uncertainty
How much
certainty exists?
All information Some information No information

• Degree of certainty – a) complete certainty, b) risk and
certainty, and c) extreme uncertainty
• Complete certainty: All the information to make decision
is available (or assumed to be available). Outcomes are
probably known.
• Decision making may not be easy since the problem may
be ill defined, the decision criteria may be unclear, there
may be too many variables to handle, etc.
– Some of the methods (tools) used are:
– Break-even analysis, Benefit/cost analysis, linear, non-
linear, integer, goal and dynamic programming

• Risk and uncertainty: Information about the decision
variables or the outcomes is usually probabilistic.
• Objective data from large samples may give more
certainty than subjective data.
– Statistical analysis for setting labour standards, forecasting,
inventory and quality control, etc.
– Queuing theory for waiting line, maintenance activities,
shop floor control activities.
– Network analysis techniques such as PERT, CPM, Decision
trees, etc.
– Simulation for duplicating the essence of an activity
without actually doing it.

• Complete Uncertainty: No information about the
decision variables or the outcomes is available.
– Game theory
– Coin flip

• Linear Programming
• A firm manufactures two types of products A and B and
sells them at a profit of Rs. 2 on type A and Rs. 3 on type
B. Each product is processed on two machines G and H.
Type A requires one minute of processing time on G and
2 minutes on H, type B requires one minute on G and
one minute on H. The machine G is available for not
more than 6 hours and 40 minutes while machine H is
available for 10 hours during one working day.
Formulate the problem as a linear programming
problem.
Decision Making - Certainty

• Let x1 be the number of products of type A and x2 be the
number of products of type B.

• Let, Z – the objective function = Total profit
• Z = 2 x1 + 3 x2 (objective function)
• The total time (in minutes) required on machine G is
given by
= x1 + x2
• But the machine G is not available for more than 6 hours
and 40 minutes (i.e., 400 minutes). Therefore,
• x1 + x2 ≤ 400
• Similarly, the total time (minutes) required on machine
H is 2x1 + x2. Since machine H is available for 600 min.,
• 2x1 + x2 ≤ 600

The Linear Programming Model (equations)
Maximize Z = 2 x1 + 3 x2 (objective function)
Subject to constraints
x1 + x2 ≤ 400 --- Machine G time constraint
2x1 + x2 ≤ 600 --- Machine H time constraint
x1 ≥ 0 & x2 ≥ 0 --- non negative constraints.
The Three basic elements of an LP model are:
• The objective function
• Decision variables
• A set of constraints

The Linear Programming Model (equations)
Soln.:
x1 + x2 = 400 --- 1
2x1 + x2 = 600 --- 2
Eqn. 2 – Eqn. 1 gives us,
x1 = 200 and x2 = 200
Hence, Profit maximized, Z = 2 (200) + 3 (200) =
Rs. 1000

Graphical Soln.:
•OABC is the area
bound by the two
constraint lines.
It is called Solution
Space.
Optimum value Z at
each point:
O = Zero
A = Rs. 4000
B = Rs. 1000
C = Rs. 600 Dept. of ME, JSSATE, Bengaluru 75

• Break-even analysis (Cost-Volume-Profit)
• Revenue = Unit Selling Price, SP x Sales quantity, Q
• Total Cost = Total Fixed Cost (FC) + Total Variable Cost (VC)
• Total profit, P = Total revenue – Total cost
• P = (Q x SP) – (FC + v x Q)
• P = Q (SP -v) – FC
Where, SP – Selling Price / unit; VC – Variable Cost/unit

Decision Making - Certainty: BEA

• If fixed costs are Rs. 40000 per week and variable costs
are estimated at 50% of the unit selling price of Rs.160,
what is the BEP?
• = (40000)/(160-80) = 500 units

• The owner of a bakery is planning to produce a new
cake, which will require leasing new equipment for a
monthly payment of $6,000. Variable costs would be $2
per cake, and cakes would retail for $7 each.
• How many cakes must be sold in order to break even?
• What would the profit (loss) be if 1,000 cakes are made
and sold in a month?
• How many cakes must be sold to realize a profit of
$4,000?
• If 2,000 cakes can be sold, and a profit target is $5,000,
what price should be charged per cake?

• FC = $6,000, VC = $2 per cake, SP = $7 per cake
• a.
• b. For Q = 1,000, P = Q ( SP − VC )  − FC
• = 1,000 ($7 − $2)− $6,000 = − $1,000
• c. Profit, P = $4,000; Solve for Q using Q = (P+FC)/(SP-VC)
• d. P = $5000, Q = 2000 cakes; We know, P = Q (SP -v) – FC
• $5,00 0 = 2,000 (SP − $2) − $6, 000
• Therefore, SP = $7.50

Risk & Uncertainty:
• When probabilities can be assigned to the occurrence of
states of nature (events that may occur in future), the
situation is referred to as decision making under risk.
• When probabilities cannot be assigned to the
occurrence of future events, the situation is called
decision making under uncertainty.
• Decision Criteria used:
– Maximax
– Maximin
– Minimax regret
– Hurwicz
– Equal likelihood (LaPlace)
Decision Making Situations

• A Textile MNC is contemplating the future of one of its
plants located in Mumbai. Three alternative decisions are
being considered: (1) Expand the plant and produce
lightweight, durable materials for possible sale to the
military, a market with little foreign competition; (2)
maintain the status quo at the plant, continuing
production of textile goods that are subject to heavy
foreign competition; or (3) sell the plant now. If one of the
first two alternatives is chosen, the plant will still be sold
at the end of the year. The amount of profit that could be
earned by selling the plant in a year depends on market
conditions. The following payoff table is prepared by the
top management of the company:
Decision Making – Risk & Uncertainty

• Determine the best decision using each of the decision
criteria,
1. Maximax, 2. Maximin, 3. Minimax regret
4. Hurwicz (Take α = 0.3), 5. Equal likelihood
83

• Maximax (Optimistic) criterion
• The decision maker optimistically assumes that ‘good
competitive conditions’ will prevail in the future.
• The decision selected will result in the maximum of the
maximum payoffs.
• Hence,
• Expand: $800,000
• Status quo: $1,300,000 ← Maximum
• Sell: $320,000
• Decision: Maintain status quo

• Maximin (Pessimistic) criterion
• The decision maker is pessimistic and assumes that
‘minimum payoffs’ will occur in the future.
• The decision maker selects the decision that will reflect
the maximum of the minimum payoffs.
• Hence,
• Expand: $500,000 ← Maximum
• Status quo: - $150,000
• Sell: $320,000
• Decision: Expand

• Minimax regret criterion
• The decision maker attempts to avoid regret by selecting the
decision alternative that minimizes the maximum regret.
• First, select the maximum payoff under each state of nature; then
all other payoffs under the respective states of nature are
subtracted from these amounts.
• The maximum regret for each decision must be determined, and
the decision corresponding to the minimum of these regret values
is selected.

• Minimax regret criterion
• Expand: $500,000 ← Minimum
• Status quo: $650,000
• Sell: $980,000

• Hurwicz criterion
• The decision maker is neither totally optimistic (maximax
criterion) nor totally pessimistic (maximin criterion).
• The decision payoffs are weighted by a coefficient of
optimism, α, a measure of the decision maker’s
optimism.
• If α =1, the decision maker is completely optimistic; if α =
0, the decision maker is completely pessimistic. (Given
this definition, (1 - α) is the coefficient of pessimism.)

• Hurwicz criterion
• For each decision alternative, the maximum payoff is
multiplied by α, and the minimum payoff is multiplied by
(1 - α).
• In the given example, if α equals 0.3 (i.e., the company is
slightly optimistic) and (1 - α)=0.7, the following decision
will result:
• Expand: $800,000(0.3) + 500,000(0.7) = $590,000 ← Maximum
• Status quo: $1,300,000(0.3) - 150,000(0.7) = $ 285,000
• Sell: $320,000(0.3) + $320,000(0.7) = $320,000

• Equal Likelihood:
• Each state of nature is weighted equally. That is, it is assumed
that the states of nature are equally likely to occur (weight of
0.5 each since there are two).
• Multiply the weights by each payoff for each decision.
• Select the alternative with the maximum of these weighted
values.
• Expand: $800,000(0.50) + $500,000(0.50) = $650,000 ←
Maximum
• Status quo: $1,300,000(0.50) +$150,000(0.50) = $575,000
• Sell: $320,000(0.50) + $320,000(0.50) = $320,000
• Decision is Expand

• Consider the following payoff table for three product
decisions (A, B, and C) and three future market
conditions (payoffs in $ millions).
• Determine the best decision using the following decision
criteria.
1. Maximax, 2. Maximin

• Decision Tree: A schematic representation of the alternatives
available to a decision maker and their possible consequences.
Decision Tree

• Using the information in the payoff table given and a
probability of 0.6 for new bridge and 0.4 for No New
Bridge, construct a decision tree and select the best
alternative:
Decision Making Situations
Decision
Alternative
Expected Payoff ($) under State of Nature
New Bridge No New Bridge
A 1 14
B 2 10
C 4 6

Decision Tree

18ME56-OM_ Module 1-Curriculum COs Mapping.pdf

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