• Operations is a core activity: transforming inputs (labour, materials, capital, technology) into outputs (goods or services). If this transformation is inefficient, the organization suffers in cost, quality, delivery time, competitiveness.
  
• Every organization—manufacturing or service—has operations. Even in service organizations, production here refers to service production: e.g. hospitals, banks, education.
  
• POM links closely with strategy: operations decisions are strategic in nature (location, capacity, quality, supply chain). They affect competitive priorities: cost, quality, flexibility, delivery, innovation.
  
• POM employs quantitative tools (forecasting, linear programming, inventory models, project scheduling) so MBA students must be capable of both conceptual and analytical thinking.
  

• Describe the nature and scope of POM and how it relates to other parts of the organization. (Scribd)
  
• Understand how operations contributes to organizational goals.
  
• Appreciate quality importance.
  
• Discuss product/service design.
  
• Explain technology management.
  
• Formulate linear programming models; understand aggregate planning; apply inventory models; understand MRP and JIT; understand project management techniques. (Scribd)
  
• Evaluate location alternatives. Forecasting. Work measurement. Learning curves. Etc.
  

1. POM — An Introduction
   
   • Definition: POM is the process of planning, organising, directing and controlling all the activities which transform inputs into goods & services. It encompasses design, operations, control, improvement.
     
   • Manufacturing vs Service Operations: Service operations often have the characteristics of perishability, customer participation, heterogeneity, intangibility. Manufacturing is more tangible, can hold inventory, more predictable in many cases.
     
   • Operations Strategy: alignment between operations decisions and overall business strategy. Competitive priorities typically include cost, quality, speed/delivery, flexibility, and sometimes innovation. Strategy determines trade‐offs.
     
   • Operations environment & competitive advantage: how external factors (market demand, competition, technology, globalization, supply chain, regulation) shape operational needs.
     
2. Operations Strategy
   
   • Translating corporate/business strategy into operations‐level decisions: capacity, technology, location, layout, supply chain, quality.
     
   • Competitive priorities: e.g. low cost vs differentiation; consistent quality vs speedy service; volume vs flexibility (manufacturing & services).
     
   • Order winners vs qualifiers: what you must have to even be considered (qualifiers), vs what wins you the customer (order winners).
     
   • Strategic decisions about make vs buy; degree of vertical integration; level of automation.
     
3. Forecasting in POM
   
   • Purpose: anticipate demand (sales, service demand) to make decisions about capacity, inventory, workforce, scheduling, purchasing.
     
   • Types: qualitative (Delphi, market research, customer surveys), quantitative (time series, causal models, moving averages, exponential smoothing, trend analysis).
     
   • Measures of forecast accuracy: Mean Absolute Deviation (MAD), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE).
     
   • Forecasting horizon issues: short‐term vs long‐term forecasts; aggregation/disaggregation.
     
4. Process Management
   
   • Process types: job processes, batch, assembly line, continuous/flow processes; differentiating by volume, variety, customization, lead times.
     
   • Process design decisions: process mapping, process‐flow analysis, capacity utilization; balancing line, reduction of bottlenecks.
     
   • Process improvements: process reengineering, lean thinking, reducing waste, improving flow.
     

1. Job Design
   
   • How work is structured: division of labour, specialization vs job enlargement, job rotation, job enrichment.
     
   • Human factors: ergonomics, fatigue, motivation, quality. Impacts on productivity and quality.
     
2. Management of Technology
   
   • Deciding what technologies to adopt: automation, robotics, digital technologies, ICT, Industry 4.0, AI etc.
     
   • Technology life cycle; technology as enabler of cost reduction, quality improvement, flexibility.
     
   • Challenges: cost, training, obsolescence, maintaining technology.
     
3. Site (Location) Selection
   
   • Importance: location affects costs (transportation, logistics, utilities, labour), access to markets, suppliers, infrastructure, government policy, environment.
     
   • Factors: proximity to markets vs suppliers; labour cost and skills; land; infrastructure; government policy & incentives; environmental issues; community factors.
     
   • Methods for evaluating alternatives: factor rating, centre‐of‐gravity, cost‐volume profit analysis, transportation models.
     

1. Supply Chain Management (SCM)
   
   • Definition: managing the network of upstream suppliers, internal operations, and downstream distribution to deliver product/service to customers.
     
   • Key issues: coordination, information sharing, lead times, supplier reliability, risk, responsiveness vs efficiency, inventory across the supply chain.
     
   • Concepts: Bullwhip effect, supply chain integration, vendor managed inventory, outsourcing, reverse logistics.
     
2. Inventory Management
   
   • Roles of inventory: buffer against uncertainties in demand/supply; allow economies of scale; support decoupling of processes; permit seasonal/forecasted demand.
     
   • Costs of inventory: holding cost, ordering/setup cost, stockout cost.
     
   • Inventory models: Economic Order Quantity (EOQ), quantity discounts, reorder point, safety stock, ABC classification, periodic vs continuous review systems.
     
3. Aggregate Planning
   
   • Purpose: intermediate‐term planning (e.g. 3‐18 months) to match supply (capacity, workforce, inventory) to forecasted demand in a cost‐effective way.
     
   • Strategies: level strategy, chase strategy, hybrid. Using subcontracting, inventory buildup, workforce changes, overtime.
     
   • Cost trade‐offs: cost of holding inventory vs cost of changing workforce vs cost of overtime/subcontracting.
     
4. Linear Programming
   
   • Used to optimise resource use subject to constraints (e.g. maximize profit, minimize cost) subject to resource capacities, demands.
     
   • Components: decision variables, objective function, constraints.
     
   • Methods: simplex method, duality, sensitivity analysis.
     
5. Materials Requirements Planning (MRP)
   
   • Purpose: for manufacturing environments, to schedule material arrivals so inputs are available for production when needed, avoid shortages, minimize inventory.
     
   • Components: master production schedule (MPS), bill of materials (BOM), inventory status, lead times.
     
   • Issues: requires reliable data; lot sizing; impact of forecast errors.
     
6. Just-In-Time (JIT) Systems
   
   • Philosophy: produce what is needed, when needed, in the amount needed – reduce inventory, reduce waste, lead times.
     
   • Techniques: pull systems, Kanban, small lot sizes, tight supplier relationships.
     
   • Benefits vs Risks: better quality, lower inventory costs, but sensitive to disruptions, requires discipline, stable demand, reliable supply chain.
     
7. Project Management
   
   • Projects are unique, non‐routine operations with defined start and finish.
     
   • Tools: Work Breakdown Structure (WBS), Network planning: PERT (Program Evaluation Review Technique), CPM (Critical Path Method), Gantt Charts.
     
   • Network analysis: identifying critical path, slack, float; resource allocation; crashing; cost/time trade‐offs.
     

1. Productivity
   
   • Definition: ratio of outputs to inputs. Can be labour productivity, machine productivity, total factor productivity.
     
   • Ways to improve: process improvement, technology, training, layout, elimination of waste.
     
2. Work Methods
   
   • Systematic study of ways of doing work. Includes process flow, sequence of operations, motion study, methods improvement.
     
3. Work Measurement
   
   • Determining how long it should take to do a task: time study, work sampling, predetermined motion time systems, standard times.
     
   • Used for capacity planning, job design, incentive systems.
     
4. Learning Curves
   
   • Concept: as a task is repeated, the time required per unit tends to decrease at a predictable rate (learning effect).
     
   • Uses: forecasting labour/time costs, setting performance benchmarks.
     
5. Total Quality Management (TQM)
   
   • Philosophy of continuous improvement; everyone in organization participates in improving processes, products, and services.
     
   • Tools: Statistical Process Control (SPC), control charts, cause & effect diagrams, Pareto analysis, Six Sigma, benchmarking, quality circles.
     
   • Dimensions of quality: performance, reliability, durability, features, conformance, serviceability, aesthetics.
     
6. Maintenance and Reliability
   
   • Maintenance types: preventive, predictive, corrective.
     
   • Reliability: probability a system or component performs its required functions under stated conditions for a given period.
     
   • Measures: MTBF (Mean Time Between Failures), MTTR (Mean Time to Repair), availability.
     
   • Importance: minimizing downtime, maintaining consistent quality, reducing costs of breakdowns.
     

• Forecasting feeds into capacity planning, aggregate planning, inventory and MRP decisions.
  
• Location and layout decisions made early have long‐term impacts on cost, flexibility, quality.
  
• Decisions to adopt technology or automation affect job design, work methods, measurement, reliability, and cost structures.
  
• Quality management (TQM, SPC etc.) requires alignment with process design, supplier management, inventory (raw material quality), maintenance.
  
• Lean/JIT philosophy overlaps with SCM, inventory, process flow, technology and quality.
  
• Control decisions (measurement, quality, reliability) help ensure that plans (aggregate, scheduling etc.) are executed well.
  

• Manufacturing: automobile plants, textile mills, electronics factories — decisions on layout, automation, inventory to reduce cost and improve quality.
  
• Service operations: banks, hospitals, airlines — service design, capacity planning (e.g. number of beds/doctors), scheduling, reliability, maintaining service quality.
  
• Supply chain networks: deciding supplier contracts, warehousing, transportation, distribution strategies.
  
• Project‐based industries: construction, IT projects — scheduling, resource allocation, managing time/cost trade‐offs.
  

• Uncertainty and variability: in demand, supply lead times, process times, quality issues.
  
• Data accuracy: MRP, forecasting, lot sizes require accurate input data; poor data leads to bad decisions.
  
• Integration across functions: operations must align with marketing, finance, HR. For example, marketing may push for delivery speed; operations must plan capacity etc.
  
• Balancing trade‐offs: cost vs quality; flexibility vs efficiency; inventory vs responsiveness.
  
• Technological changes, disruptions: e.g. supply chain shocks, pandemics, labour issues.
  

• A large goods manufacturer choosing plant location: using factor rating combining costs (labour, transport), market access, infrastructure.
  
• An electronics assembly plant implementing JIT and Kanban to reduce WIP (work‐in‐progress) and inventory cost.
  
• A hospital using forecasting and process design to reduce waiting times for patients, improving service quality.
  
• Use of SPC (control charts) in a bottling plant to monitor consistency of fill volumes, detect early drift.
  

• Stevenson, W. J. — Operations Management (other editions)
  
• Chase, R. B., Aquilano, N. J., Jacobs, F. R. — Production and Operations Management: Manufacturing & Services
  
• Krajewski, Ritzman, Malhotra — Operations Management: Process and Value Chains
  
• Russell & Taylor — Operations Management: Quality and Competitiveness in a Global Environment
  

• The course is 2 credit units, consists of 20 study units.
  
• Assessment is 50% from Tutor-Marked Assignments (TMAs) and 50% from final examination. Students are expected to submit a number of TMAs (eight out of many) for grading. (Scribd)
  
• Final exam is 3 hours long. Questions will typically reflect self‐test, practice exercises, TMA types. So practising numerical problems (inventory, LP, project scheduling etc.) is vital.
  

Quote:“Discuss how operations strategy contributes to competitive advantage. Illustrate with examples. What trade‐offs do operations managers face when designing a production system?”

1. Definition of operations strategy; link to competitive priorities (cost, quality, speed, flexibility etc.).
   
2. How operations strategy converts business strategy into decisions: capacity, technology, location, layout, supply chain.
   
3. Real/ hypothetical examples (e.g. Amazon’s operations strategy focuses on speed and delivery; Toyota’s strategy emphasizes quality and lean production).
   
4. Discussion of trade‐offs: e.g. high quality vs low cost; flexibility vs efficiency; investing in automation vs labour costs; high inventory for responsiveness vs cost of carrying inventory.
   
5. Conclusion: operations strategy must be aligned with market needs and other functional areas; trade‐offs must be explicitly recognized; continuous improvement is important.
   

• Master the quantitative tools: be able to formulate, solve, interpret linear programming, project networks, inventory (EOQ etc.), forecasting.
  
• Understand definitions and relationships: e.g. difference between process types; between JIT and traditional inventory systems; between job, batch, line, continuous flow.
  
• Use diagrams and flow charts: process flows; network diagrams; control charts; layout sketches. Visuals help for clarity.
  
• Case studies are useful: try to find examples from Nigerian firms or industries you’re familiar with to illustrate location decision, quality problems, etc.
  
• Practice TMAs (assignments) seriously—they often build up to exam style.
  
• Keep abreast of current practice: e.g. lean, Industry 4.0, supply chain risk, digital transformation—these may inform discussion even though not deeply in syllabus.