The document outlines Multi-Criteria Decision Analysis (MCDA), a framework for evaluating decisions involving multiple conflicting criteria, promoting data-driven choices. It details the MCDA process, including defining decision problems, identifying criteria, assigning weights, scoring alternatives, and calculating weighted scores, illustrated with examples and real-world applications in healthcare, environmental management, and corporate strategy. Various MCDA methods such as the Weighted Sum Model, Analytic Hierarchy Process, and TOPSIS are also explained, highlighting their relevance in complex decision-making scenarios.

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Slides Prepared by Rafia Zafar
QUANTITATIVE
METHODS FOR
BUSINESS 8e

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Chapter 5
Introduction
 MCDA
 Core Concepts of MCDA
 MCDA Process
 MCDA Methods with Examples
 Real-World Applications of MCDA
 In-Class Problem Solving Exercise

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MCDA
•MCDA is a decision-making framework designed to evaluate multiple
conflicting criteria, essential in situations where trade-offs are required.
•MCDA helps bring structure and clarity to complex decisions, reducing the
influence of biases and focusing on objective analysis.
Importance in Decision-Making:
•In real-world scenarios, decisions often involve more than one criterion.
For example, businesses balancing cost, quality, and delivery speed when
selecting suppliers.
•MCDA enables a balanced approach, allowing for data-driven choices that
align with organizational goals.

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Core Concepts of MCDA
•Alternatives: Different options available to decision-makers
(e.g., potential suppliers or project locations).
•Criteria: Standards by which each alternative is judged (e.g.,
cost, quality, efficiency).
•Weights: Assigned to criteria based on their importance. A
higher weight reflects greater importance.
•Scoring: Each alternative receives a score for each criterion,
reflecting its performance in that area.

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MCDA Process
 Choosing a New Office Location for a growing company.
 Step 1: Define the Decision Problem:
• Problem: Find the most suitable office location considering cost, employee
commute time, amenities, and proximity to key clients
 Step 2: Identify Criteria
• Criteria List:Cost: Budget constraints for office rent.
• Commute Time: Average travel time for employees.
• Amenities: Access to restaurants, parking, etc.
• Proximity to Clients: Distance to major clients for convenient visits

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MCDA Process
 Step 3: Assign Weights to Criteria:
 Weight Assignment:
 Cost: 40%
 Commute Time: 25%
 Amenities: 15%
 Proximity to Clients: 20%
 Note that these weights total 100%, representing a balanced allocation of
importance based on the company’s priorities

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MCDA Process
 Step 4: Score Each Alternative:
 Example: Three locations (A, B, C) are rated on a scale of 1 to 10 for each
criterion:
 Location A: Cost: 8, Commute Time: 6, Amenities: 5, Proximity: 7
 Location B: Cost: 7, Commute Time: 8, Amenities: 7, Proximity: 6
 Location C: Cost: 6, Commute Time: 7, Amenities: 8, Proximity: 8

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MCDA Process
 Step 5: Calculate Weighted Scores:
• Multiply each score by its criterion weight and sum the results for each
location:
• Location A: (8×0.4) + (6×0.25) + (5×0.15) + (7×0.2) = 3.2 + 1.5 + 0.75 + 1.4
= 6.85
• Location B: (7×0.4) + (8×0.25) + (7×0.15) + (6×0.2) = 2.8 + 2.0 + 1.05 + 1.2
= 7.05
• Location C: (6×0.4) + (7×0.25) + (8×0.15) + (8×0.2) = 2.4 + 1.75 + 1.2 + 1.6
= 6.95
• Decision: Location B has the highest score (7.05), making it the preferred
choice based on the weighted criteria.

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MCDA Methods with Examples
 Weighted Sum Model (WSM):
Adds up weighted scores for each criterion. Simple yet effective for
straightforward problems.
• Example: Used in product selection, such as choosing the best software by
scoring on factors like functionality, cost, and support.
 Analytic Hierarchy Process (AHP):
Breaks down decisions into hierarchy levels and uses pairwise comparisons,
ideal for complex decisions.
• Example: In hiring, AHP can compare candidates based on experience,
education, and skill sets. Each criterion is ranked, and scores are aggregated
to select the most qualified candidate.

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MCDA Methods
 TOPSIS:
Identifies the option closest to an “ideal” solution and farthest from a “worst-
case” scenario.
• Example: Used by governments to select suppliers for infrastructure
projects, balancing cost efficiency and quality

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Real-World Applications of MCDA
 Healthcare:
• Resource Allocation: MCDA helps allocate limited resources, such as beds
or vaccines, by balancing factors like patient need, treatment cost, and
urgency.
• Example: During a health crisis, hospitals might use MCDA to prioritize
patient admissions based on factors like age, severity, and recovery
probability
 Environmental Management:
• Project Evaluation: MCDA is often used to assess projects involving
sustainability, balancing environmental impact with economic benefits.
• Example: Evaluating renewable energy projects (solar, wind, hydro) using
criteria like installation cost, environmental impact, and long-term benefits

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Real-World Applications of MCDA
 Urban Planning:
• Infrastructure Development: Helps planners prioritize projects by scoring
criteria like cost, public benefit, and environmental impact.
• Example: When selecting locations for new parks, MCDA considers factors
like population density, accessibility, and cost
 Corporate Strategy:
• Product Development: Companies use MCDA to evaluate product
development ideas based on market demand, production cost, and
competitive advantage.
• Example: A company may decide between launching a high-quality or
budget-friendly version of a product by scoring customer demand, profit
potential, and brand alignment

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Scenario
• Imagine you are part of a team choosing a logistics provider for your
company. Criteria include cost, delivery speed, reliability, and
environmental impact.
• Step 1: Define each criterion and assign weights based on what’s most
important for the company.
• Step 2: Provide ratings for three logistics providers.
• Step 3: Calculate the weighted scores and discuss which provider would be
the best choice.

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Scenario
 Your team is choosing between three logistics providers based on criteria including cost,
delivery speed, reliability, and environmental impact. Each criterion has been assigned a
weight according to its importance to the company.
 Solution Steps
 Step 1: Define Each Criterion and Assign Weights
• Cost: Lower costs are preferable as they help manage budget effectively.
• Weight: 0.4
• Delivery Speed: Faster delivery speed improves service levels and customer satisfaction.
• Weight: 0.3
• Reliability: Consistent service (on-time delivery, few issues) is crucial for maintaining
smooth operations.
• Weight: 0.2
• Environmental Impact: Providers with environmentally friendly practices support the
company’s sustainability goals.
• Weight: 0.1

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Scenario
Criteria Provider A Provider B Provider C
Cost 8 7 6
Delivery Speed 6 9 8
Reliability 7 8 9
Environmental Impact 5 7 8
Step 2: Provide Ratings for Three Logistics Providers
Each logistics provider is rated on a scale from 1 to 10 for each criterion, where 10 is the
best score and 1 is the worst.
Step 3: Calculate the Weighted Scores
Using the formula:
Weighted Score=∑(Criterion Score×Criterion Weight)

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Scenario
 Calculate the weighted score for each provider:
Provider A:
(8×0.4)+(6×0.3)+(7×0.2)+(5×0.1)
3.2+1.8+1.4+0.5=6.9
Provider B:
(7×0.4)+(9×0.3)+(8×0.2)+(7×0.1)
2.8+2.7+1.6+0.7=7.8
Provider C:
(6×0.4)+(8×0.3)+(9×0.2)+(8×0.1)
2.4+2.4+1.8+0.8=7.4

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Scenario
 Step 4: Select the Best Provider
• Final Scores:
• Provider A: 6.9
• Provider B: 7.8
• Provider C: 7.4
Based on the MCDA weighted scores, Provider B is the best choice with the
highest score of 7.8.