Intro to Operations Management

1. Key Concepts

Operations Management: Managing systems/processes that create goods or provide services.
Supply Chain: Sequence of activities/organizations involved in producing and delivering goods or services.

2. Goods vs. Services

Goods: Physical items (e.g., computers, cars, shampoo).
Services: Non-physical activities providing value (e.g., education, legal services, air travel).

3. The Transformation Process

Inputs (land, labor, capital, information) are transformed into Outputs (goods, services).
Control: Feedback is used to compare against standards to decide on corrective actions.

4. Manufacturing vs. Service Operations

Manufacturing: Focus on products, uniformity in production, less customer interaction.
Service: High customer interaction, variability in demand and output, focus on delivery and experience.

5. Basic Functions of Business

Operations, Marketing, Finance work in tandem to achieve business goals.
Finance ensures funding and investment analysis, Marketing drives demand and design, and Operations manages production or service delivery.

6. Career Opportunities in OM and Supply Chain

Operations Manager, Supply Chain Manager, Production Analyst, Inventory Manager, Quality Manager, and more.

7. Process Management

Processes transform inputs to outputs and include three categories:

• Upper-Management Processes: Govern the entire organization.
• Operational Processes: Core value-adding processes.
• Supporting Processes: Aid the core processes.

8. Sources of Variation

• Variety in Offerings: More variety leads to more variability in operations.
• Structural Variation: Predictable; critical for planning.
• Random Variation: Inherent natural fluctuations.
• Assignable Variation: Identifiable and manageable variations.

9. Operations Management Decisions

Operations decisions involve determining resources, scheduling, production location, design, and roles.
Key decisions: What, When, Where, How, and Who.

10. Models in Decision-Making

Models help simplify real-life systems. Types include:

• Physical Models (e.g., miniature airplane)
• Schematic Models (e.g., drawings)
• Mathematical Models (e.g., inventory optimization)

11. Metrics and Trade-offs

Common metrics: Profits, Costs, Quality, Productivity, Inventories.
Trade-offs: Giving up one benefit for another, such as holding more inventory to improve customer service.

12. Systems Perspective

Organizations consist of subsystems (Marketing, Operations, Finance) working toward common objectives. Focus on interdependence ensures efficiency.

13. Historical Evolution of Operations Management

• Industrial Revolution: Division of labor, steam engine, interchangeable parts.
• Scientific Management: Efficiency-driven (Frederick Taylor).
• Human Relations Movement: Focus on worker motivation and psychology (e.g., Elton Mayo, Abraham Maslow).
• Decision Models: Statistical sampling, linear programming (George Dantzig).
• Japanese Influence: Quality focus and Just-in-Time production.

14. Key Issues in Modern Operations

• Managing technology, quality, and innovation.
• Sustainability and environmental responsibility.
• Cybersecurity and risk management.
• Competing in global markets with limited resources.

15. Supply Chain Challenges

• Managing outsourcing and globalization.
• Balancing transportation costs and competitive pressures.
• E-commerce integration and inventory management.

Competitiveness, Strategy, and Productivity

1. Competitiveness

How effectively an organization meets customer needs relative to competitors. Organizations compete through operations and marketing by addressing:

• Consumer needs and wants
• Pricing and quality
• Advertising and promotion

2. Ways Businesses Compete

• Product and service design
• Cost and pricing
• Location and convenience
• Quality of offerings
• Quick response to market demands
• Flexibility in operations
• Effective inventory and supply chain management
• Service excellence

3. Reasons for Business Failure

• Lack of operations strategy
• Ignoring strengths, opportunities, or competitive threats
• Overemphasis on short-term performance over R&D
• Poor process design and improvement
• Insufficient investment in capital and talent
• Weak internal communication and collaboration
• Misalignment with customer expectations

4. Mission, Goals, and Strategy

• Mission: Defines the organization’s purpose and reason for existence.
• Goals: Provide detailed outcomes aligned with the mission.
• Strategies: Roadmap for achieving goals.
• Tactics: Practical actions for strategy implementation.

5. Core Competencies and Strategy Alignment

Core competencies are unique capabilities giving a competitive edge. Successful strategy formulation aligns competencies with external opportunities through:

• SWOT Analysis: Strengths, Weaknesses, Opportunities, Threats
• Order Qualifiers: Minimum standards required for product/service acceptance.
• Order Winners: Features that differentiate from competitors.

6. Operations Strategy Examples

• Low Cost: Walmart, U.S. Postal Service
• Responsiveness: FedEx, McDonald’s
• Differentiation by Quality: Sony, Coca-Cola
• Differentiation by Innovation: Apple, 3M
• Differentiation by Service: Disney, IBM
• Location-Based Convenience: Malls, supermarkets

7. Time-Based Strategies

Strategies focusing on reducing the time needed to complete tasks. Benefits include cost reduction, higher quality, and improved customer service. Examples:

• Planning, design, processing, and delivery time reductions

8. Agile Operations

A strategy that emphasizes flexibility to adapt to changes in the market. It involves balancing cost, quality, reliability, and flexibility to gain a competitive advantage.

9. The Balanced Scorecard Approach

Transforms strategy into actionable objectives, measured across:

• Financial performance
• Customer satisfaction
• Internal processes
• Learning and growth

10. Productivity

Productivity: The ratio of output to input, tracking the efficient use of resources.

• Importance: Higher productivity drives competitive advantage, profitability, and standards of living.
• Service Sector Challenges: High variability and measurement difficulty.

11. Productivity Measures

Examples of partial productivity measures include:

• Output per labor hour
• Output per unit of capital

12. Factors Affecting Productivity

• Internal Factors: Human resources, financial resources, technology, product quality
• External Factors: Economic and political conditions, market competition, supplier performance

13. Recent Technological Advances Affecting Productivity

• Drones, GPS, 3D printers
• RFID tags, AI, medical imaging

14. Steps to Improve Productivity

• Identify productivity measures and bottlenecks
• Develop improvement methods and set realistic goals
• Support productivity efforts with management backing
• Track and publicize improvements

Forecasting

1. Key Concepts

Forecast: A prediction about the future value of a variable (e.g., demand, weather). Forecasts guide decision-making across multiple areas, including operations, marketing, finance, and human resources.

2. Features Common to All Forecasts

• Forecasts assume past patterns will continue into the future.
• They are not perfect due to random variation and uncertainty.
• Forecasts for groups of items are more accurate than for individual items.
• Accuracy decreases as the forecast horizon increases.

3. Elements of a Good Forecast

• Timely, accurate, reliable, and cost-effective.
• Expressed in meaningful units and documented in writing.
• Simple to understand and use.

4. Steps in the Forecasting Process

1. Define the purpose of the forecast.
2. Establish the time horizon.
3. Gather and analyze data.
4. Select a forecasting technique.
5. Generate the forecast.
6. Monitor forecast errors and adjust as needed.

5. Forecasting Approaches

• Qualitative Forecasting: Relies on opinions and soft data (e.g., consumer surveys, expert opinions).
• Quantitative Forecasting: Uses historical data or causal variables to generate forecasts.

6. Qualitative Techniques

• Executive Opinions: Developed through meetings of upper management.
• Salesforce Opinions: Inputs from sales teams with customer insights.
• Consumer Surveys: Collect feedback directly from customers.
• Delphi Method: Iterative process aimed at achieving consensus among experts.

7. Time-Series Forecasting

• Trend: Long-term upward or downward movement.
• Seasonality: Regular variations related to time (e.g., holidays).
• Cycle: Longer-term wavelike patterns linked to economic or political conditions.
• Irregular Variations: Unusual, unpredictable events (e.g., strikes).
• Random Variation: Residual variations with no clear cause.

8. Forecasting Techniques

• Naïve Forecast: Uses the previous period’s value as the forecast.
• Moving Average: Averages recent values to smooth fluctuations.
• Weighted Moving Average: Assigns greater weight to recent data points.
• Exponential Smoothing: Updates forecasts by adding a portion of the forecast error.
• Linear Trend: Fits a line to historical data to identify trends.
• Trend-Adjusted Exponential Smoothing: Adjusts forecasts for trends using smoothing constants.

9. Seasonality Techniques

• Additive Model: Adds a seasonal component to the average value.
• Multiplicative Model: Multiplies the average by a seasonal relative.
• Seasonal Relatives: Used to adjust data for seasonality by scaling based on historical patterns.

10. Associative Forecasting

• Regression Analysis: Fits a line to a set of data points to model relationships between variables.
• Correlation Coefficient (r): Measures the strength and direction of the relationship between two variables.
• Coefficient of Determination (r²): Indicates how much variability in the dependent variable is explained by the independent variable.

11. Forecast Accuracy

• MAD (Mean Absolute Deviation): Averages absolute forecast errors.
• MSE (Mean Squared Error): Weighs larger errors more heavily.
• MAPE (Mean Absolute Percentage Error): Expresses error as a percentage of actual values.

12. Forecast Monitoring

• Track errors regularly to identify bias or non-random errors.
• Use control charts to monitor forecast performance.
• Tracking signals help detect forecast bias and guide corrective actions.

13. Factors in Choosing a Forecasting Technique

• Cost and accuracy: Balance between expense and precision.
• Historical data availability: Essential for quantitative methods.
• Software and time: Availability of tools and time for analysis.
• Forecast horizon: Shorter horizons tend to yield more accurate forecasts.

14. Improving Forecasts

• Use accurate, timely data and focus on short-term forecasts.
• Share forecasts within the supply chain to improve coordination.
• Continuously monitor and update forecasts to respond to changing conditions.

Product and Service Design

1. Strategic Importance of Product and Service Design

Product and service offerings define an organization’s identity. The design or redesign of products must align with the organization’s strategy and adapt to market opportunities or threats.

2. Key Questions for Product and Service Design

• Is there demand? Assess market size and demand patterns.
• Can we produce or deliver it? Evaluate manufacturability and serviceability.
• What quality level is appropriate? Align with customer expectations and competitor quality.
• Does it make economic sense? Factor in costs, profits, liabilities, and sustainability.

3. Reasons for Design or Redesign

• Economic changes
• Social or demographic shifts
• Political, legal, or liability requirements
• Competitive pressure
• Cost or resource availability changes
• Technological advances

4. Idea Generation Sources

• Supply-Chain Based: Customers, suppliers, distributors, employees.
• Competitor Based: Reverse engineering and competitive analysis.
• Research Based: Basic research, applied research, and product development.

5. Legal, Ethical, and Sustainability Considerations

• Legal: Product liability, litigation, recalls, and compliance with the Uniform Commercial Code.
• Ethical: Balance speed, cost, and quality to avoid reputation risks.
• Sustainability: Design with cradle-to-grave assessments, end-of-life programs, and the 3 Rs (Reduce, Reuse, Recycle).

6. Phases in Product Design and Development

1. Feasibility analysis
2. Product specifications
3. Process specifications
4. Prototype development
5. Design review
6. Market test
7. Product launch
8. Follow-up evaluation

7. Design Techniques

• Standardization: Reduces variety, lowers costs, and streamlines production but may limit customization.
• Mass Customization: Combines standardized production with final-stage customization.
• Delayed Differentiation: Production is completed only after customer preferences are known.
• Modular Design: Uses interchangeable modules to increase flexibility.

8. Design for Reliability and Robustness

• Reliability: Product’s ability to function under specified conditions. Improve reliability through design enhancements, preventive maintenance, and system improvements.
• Robust Design: Products or services that perform well across a variety of conditions, reducing the chance of failure.

9. Quality Function Deployment (QFD)

QFD ensures customer requirements are integrated throughout the product development process. The House of Quality visualizes how product attributes align with customer needs.

10. Kano Model for Customer Satisfaction

• Basic Quality: Expected features that must be present.
• Performance Quality: Features that proportionally increase satisfaction.
• Excitement Quality: Unexpected features that delight customers.

11. Computer-Aided Design (CAD)

CAD increases designer productivity, creates a database for manufacturing, and enables cost analysis and simulations.

12. Manufacturability and Component Commonality

• Manufacturability: Ease of fabrication or assembly affects cost, quality, and productivity.
• Component Commonality: Using the same components across multiple products saves time, reduces inventory, and simplifies repairs.

13. Service Design and Key Considerations

• Key Issues: Variation in service requirements and level of customer involvement.
• Differences from Product Design: Services are intangible, created and delivered simultaneously, and cannot be inventoried. Location and customer interaction are crucial.

14. Phases in Service Design

1. Conceptualize (idea generation, customer needs assessment)
2. Identify service components
3. Determine performance specifications
4. Translate performance specs into design specs
5. Translate design specs into delivery specs

15. Characteristics of a Well-Designed Service System

• Aligned with organizational mission
• User-friendly and cost-effective
• Consistent, reliable, and easy to maintain
• Has effective linkages between front-end and back-end operations

16. Guidelines for Successful Service Design

1. Define the service package in detail.
2. Focus on the customer’s perspective.
3. Align recruitment and training with service expectations.
4. Monitor and improve service continuously.

17. Operations Strategy for Product and Service Design

• Bundle products and services to enhance value.
• Use multiple-use platforms to balance variety and efficiency.
• Continuously look for small improvements.
• Shorten the time to market for new or redesigned offerings.