MG215 Lecture Notes Flashcards

Module 1: Operations, Supply Chain & Strategy

• Operations:

  • SIPOC: Supplier, Input, Process, Output, Customer - with the process at the center.
  • Operations Management (OM): Design, Plan, Execute, Control, Improve.
  • Three Key Business Functions: Operations vs. Finance vs. Marketing.
  • OM Goals: Efficiency (doing things right) vs. Effectiveness (doing the right things).

• Process View of an Organization:

  • Processes can be linked to form an organization.
  • Four Core Process Families:
    • Supplier relationship processes.
    • New service/product development processes.
    • Order fulfillment processes.
    • Customer relationship processes.

Supply Chain

• Supply chain is interconnected SIPOCs of many companies.
• Supply chain is a huge “operation” itself.
• Supply Chain Flows: material, information, money, both forward and backward.
• Downstream vs. Upstream Partners.
• Linear vs. Closed Loop Supply Chain.
• Supply Chain Management (SCM): Planning, Sourcing, Making, Delivering & Returning Goods vs. Services.
• Every product is a bundle of goods and services:
  • Pure goods, core goods, core services, purer services.
• Services are: (1) Heterogeneous, (2) Intangible, (3) Perishable, (4) Inseparable.

Levels of Planning

• Strategic Planning: Decisions with Long-Term effect (1-5 years).
• Tactical Planning: Decisions with Mid-Term effect (6 to 18 months).
• Operational Decisions: Decisions with Short-Term effect (1-12 weeks).

Levels of Strategy

• Corporate Strategy: What businesses should we be in?
• Business Unit Strategy: How do we compete in each business?
• Functional Strategy: How does each business function (OM, MKT, …) contribute?
• Business Unit Strategy: Establish a fit between market (who), product (what) and company (how).

“Who” Concepts

• Key customers and their desired outcomes.
• Customer segmentation.
• Order winners, order losers, order qualifiers.

“What” Concepts

• Value proposition ($value = \frac{benefits}{costs}$
• Competitive priorities (product-related vs. process-related).
• Strategic trade-offs (you cannot be all to all customers).

“How” Concepts

• Core capabilities.
• Strategic resources.
• Functional Strategies (i.e., Operations strategy, Marketing strategy).
• Maintain and maximize the overlap among Who, What, How.

“Operations Strategy”

• Reconciliation process between market demand, technology, and a firm’s inherent operational capabilities.
• Demands regular introspection and recalibration, especially in industries characterized by:
  • Emergence of new technologies.
  • Pressure of sustainability goals.
  • Rise of new competition.
  • Rapid shifts in customer preferences.
  • Complying with regulations.
• Components:
  • Structural decisions: What resources and how to organize them?
    • Capacity & Process Design.
    • Facilities & Location.
    • Technology.
    • Supply Chain.
  • Infra-structural decisions: What the company does?
    • Workforce (hiring, training, scheduling, retention, etc).
    • Production Planning & Control.
    • Product/Process Innovation and Improvement.
    • Organization & Management.

Module 2: Process

• Process Building Blocks:
  • Process = a specific sequence of steps to follow for achieving a specific goal.
  • Each process needs inputs from suppliers to produce outputs for customers.
  • Each process needs resources: labor, machines, facilities, knowledge, capital, etc.
  • A process can have multiple flow units: material, people, information.
  • Each process is constructed of many activities: (1) operation, (2) transportation, (3) inspection, (4) delay, (5) storage.

“Process Strategy”

• Deliberate decisions about a process i.e., sequence, arrange, and organize process flows, activities and resources such that the process can effectively satisfy its specific goal which is to support the business’s competitive priorities (cost, time, quality, …).
• Strategic trade-offs in processes:
  • Standardization vs. Customization.
  • Efficiency vs. Responsiveness.
  • Capital-Intensive vs. Labor-Intensive.
  • Output volume vs. Output Variety.

Process Facility Layouts

• Product Layout: arranged steps and resources in the order they are used, good for making large volumes of a standardized product.
• Functional Layout: arrange steps and resources according to their functions, good for making a variety of products in small batches.
• Cellular Layout: combines elements of both product and functional layouts, grouping steps and resources into cells to handle a family of products with similar characteristics.
• Fixed Position: keep the product stationary while resources come to it.

Product-Process Matrix

• A matrix with Output volume vs. Output Variety as the major trade-off.
• Houses the following 7 different types of processes:
  1. Project
  2. Job-shop production
  3. Batch production
  4. Mass production
  5. Continuous production
  6. Mass customization
  7. Cellular manufacturing

Decoupling Point

• Where should we place the decoupling point in supply chain?
• The decoupling point is where the supply chain transitions from a 'Push' strategy to a 'Pull' strategy.
  1. Make-to-Stock (MTS) (also called build-to-stock) (mostly push-based)
  2. Assemble-to-Order (ATO)
  3. Make-to-Order (MTO)
  4. Engineer-to-Order (ETO) (also called design-to-order) (mostly pull-based)

“Process Visualization”

• Learn the language of process visualization.
  • 4 components: Vocabulary, Grammar, Sentence, Paragraph
  • Use the universal shapes: rectangle, triangles, arrows, ovals, diamonds, etc
• Follow the rules of process visualization
  • Rule 1: Mastering the granularity
  • Rule 2: Adaptive detailing
  • Rule 3: Do your research and collect data
  • Rule 4: Process Mapping is an Iterative process itself
• Choose the right visualization tactic:
  • Process flow diagram
  • Swimlane diagram vs. Service blueprint
  • Physical layout diagram

“Capacity”

• Design Capacity: maximum possible output rate based on “perfect” conditions.
• Effective Capacity: maximum possible output rate based on “realistic” conditions.
• Planned Utilization: $\frac{Effective \ Capacity}{Design \ Capacity}$
• Utilization of Maximum Capacity: $\frac{Actual \ output}{Design \ Capacity}$
• Utilization of Effective Capacity: $\frac{Actual \ output}{Effective \ Capacity}$

“Process Bottleneck”

• Theory of Constraints (TOC) and its five iterative steps.
• A chain is as strong as its weakest link.
• Process Capacity: capacity of the bottleneck step.
• Capacity planning: short-term, mid-term and long-term moves to elevate capacity constraints.

Process “Time” Measures

• Cycle Time: can be applied to one step of the process or the entire process.
  • The process cycle is determined by its bottleneck step.
  • Cycle time = $\frac{1}{Capacity}$
  • Process Cycle time = $\frac{1}{Process \ Capacity}$
• Throughput Time: from start to end (also called flow time or lead time).
  • Sum of process steps’ cycle times and any delay (i.e., wait) in between the steps.
• Takt Time: a target for the process cycle time dictated by customer demand.
  • $Takt \ time = \frac{Available \ Time \ to \ Produce}{Required \ Output \ Rate}$
• Process Efficiency (for an assembly line with workers) = $\frac{Sum \ of \ the \ Actual \ Work\ Times}{Number \ of \ Stations \ * \ Takt \ Time} *100$

Little’s Law (L=λ×W)

• Three components of Little’s Law
  1. L (Average Inventory or Work-in-Process, WIP) – The average number of flow units in a system at any given time.
  2. λ (Average Throughput Rate) – The average rate at which flow units enter and exit the system per unit of time.
  3. W (Average Throughput Time or Lead Time) – The average time a flow unit spends in the system from entry to exit.
• Assumptions of Little’s Law – what are they?
• Applications of Little’s Law – what are they?

Module 3: Inventory

• Types of Inventories:
  • Raw material, WIP, Finished Goods, MRO
  • Cycle Stock, Decoupling Inventory, Pipeline (Transit) Inventory, Seasonal Inventory, Anticipation Inventory, Safety Stock, Speculative Stock
• Roles of inventory:
  • Balancing supply and demand
  • Buffering uncertainty in demand and/or supply
  • Enabling economies of buying
  • Enabling geographic specialization
• Inventory Performance Metrics
  • Service level
  • Inventory turnover (backward looking)
    1. $\frac{Cost \ of \ Goods \ Sold}{Average \ Inventory \ Value}$
  • Days of supply (forward-looking)
  • $\frac{Average \ Inventory \ Value}{Cost \ of \ Goods \ Sold} *365$
  • $\frac{Ending \ Inventory \ Value}{Cost \ of \ Goods \ Sold} *365$
  • Probability of meeting demand = 1 - stockout risk
• Inventory Management Systems
  • For perishable products:
    • Newsvendor model (single-period model for short-lived products)
  • For non-perishable products (multi-period models)
    • Continuous review model
      • EOQ
        • EOQ Assumptions
        • EOQ with uncertainty
        • EOQ with quantity discounts
      • EPQ
    • Periodic review model

Bullwhip Effect

• What is it?
• What causes it?
• What are some mitigation solutions?
• Inventory Costs:
  • Product cost
  • Carrying cost
  • Ordering cost
  • Stockout cost

Economic Order Quantity (EOQ) vs. Economic Production Quantity (EPQ)

Module 4: Demand & Supply Planning

• Goal: Have the right product delivered to the right customer at the right place at the right time at the right price and right quantity i.e., match demand with supply
• Demand planning + Supply planning.

“Demand Planning”

• Demand Forecasting + Demand Management
  • Demand Forecasting predicts future, usually based on past data and expert opinions
  • Demand Management helps us manipulate and share the demand to match our supply

“Demand Management”

• What is it? Actively influencing and shaping demand to better align it with supply and operational constraints.
• Goal: Reduce demand variability, smooth demand peaks, shift timing, and optimize limited supply and fixed capacity usage.
• Tactics:
  • Use pricing power to influence demand
    • Dynamic Pricing
    • Yield Management (dynamic pricing + inventory rationing)
  • Manage timing of order fulfillment
    • Postponement
  • Nudging customer towards Alternative and/more profitable choices
  • Share information with customers

“Demand Forecasting”

• What is it? Estimating future customer demand using historical data, trends, market signals, etc.
• Goal: Improve accuracy of what, when, and how much customers will want.
• Forecasting principles
• Forecasting Methods
• Forecasting trade-offs
  • Short-term vs. long-terms
  • Detailed or aggregate
• Forecasting process steps
• Cost of forecasting
• Cost of inaccurate forecast
  • Forecast error
  • Drivers of accuracy
• How to choose a forecasting method?
  • Cost, accuracy, …

Forecasting Methods

• Judgement-based
  • Grassroots forecasting
  • Executive judgements
  • Marketing research
  • Delphi Method
• Statistical models
  • Time series
  • Casual models
  • Simulations models
  • AI

Forecasting Method: Time-Series Method

Forecast Accuracy Metrics

Module 4: Sales & Operational Planning

• 3 Types of Planning:

Sales and Operations Planning Process (S&OP)

Level vs. Chase Aggreging Planning Inputs

• Operations-related inputs
  • Current workforce
  • Production capacity per worker per period
  • Beginning inventory
  • Production hours per period
• Cost-related inputs
  • Inventory holding cost (per unit per unit of time)
  • Hiring cost (per worker)
  • Subcontracting cost (per unit of production)
  • Firing/layoff cost (per worker)
  • Regular hourly wage rate (per worker)
  • Overtime hourly wage rate (per worker)
• Marketing-related inputs
  • Demand forecast per period
• Intermediate Outputs Combine Operations-related and Cost-related Inputs to calculate the following outputs:
  • Regular Labor cost per unit of production = $\frac{Current \ Workforce}{Production \ Capacity \ per \ Worker} × \frac{Regular \ hourly \ wage \ rate}{Number \ of \ hours \ in \ a \ Month}$ ($ per unit of production)
  • Overtime Labor cost per unit of production = $\frac{Current \ Workforce}{Production \ Capacity \ per \ Worker} × \frac{Overtime \ hourly \ wage \ rate}{Number \ of \ hours \ in \ a \ Month}$ ($ per unit of production)

Final Outputs

• Strategy 1: "Level " à Per-period production rate = $\frac{Total \ Demand - Beginning \ Inventory}{Number \ of \ Production \ Periods}$ [Units per period]
• Strategy 2: "Chase" à Per-period production rate = Per-period Demand
• Required Number of Workers = $\frac{Required \ Production \ per \ Period}{Production \ Capacity \ per \ Worker \ in \ a \ Month}$
• Beginning Inventory = Previous Period’s Ending Inventory
• Ending Inventory = Beginning Inventory + Production – Demand
• Beginning Number of Workers = Previous Period’s Ending Number of Workers
• Ending Number of Workers = Beginning Number of Workers + Hires – Layoff
• Regular production cost = Regular Labor cost per unit of production* Total regular production
• Overtime cost = Overtime Labor cost per unit of production * Total overtime production
• Subcontracting cost = Subcontracting cost per unit * Total subcontracted production
• Inventory Cost = Inventory holding cost * Total average inventory
• Hire or Fire Cost = Number of new hires * hiring cost + Number of fires * firing cost

Module 5: Quality

• What is Quality?

  • 8 Dimensions of Product Quality:

    1. Performance – Does what it's supposed to

    2. Conformance – Meets design specs

    3. Features – Bonus functions or extras

    4. Aesthetics – Look, feel, style

    5. Reliability – Works every time

    6. Durability – Lasts over a long time

    7. Serviceability – Easy to fix

    8. Perceived Quality – Customer’s impression

  • 5 Dimensions of Service Quality (RATER):

    1. Reliability – Consistent delivery

    2. Assurance – Inspires trust

    3. Tangibles – Appearance of space, people, tools

    4. Empathy – Personal attention

    5. Responsiveness – Quick and helpful

Quality Gap Model

Cost of Quality (COQ)

Evolution of Quality Thinking in Organizations

“Why Averages Are Misleading”

• Averages summarize data, but they hide important details about performance variation.
• Variation tells us how much outcomes fluctuate around the average.
• Key idea: To understand a system, you must study its variation, not just its average.

“Types of Variation”

• Common Cause Variation = natural fluctuation built into a stable system. It reflects the system’s design, materials, people, and environment.
• Special Cause Variation = unexpected disruption from a new, unusual, or external factor.
• Tampering = reacting to common cause variation as if something is wrong, making the process worse.
• Control Charts help distinguish normal variation from signals of special causes. Upper/Lower Control Limits = ±3 standard deviations around the mean (covering ~99.73% of natural fluctuation).
• Important: Staying inside control limits ≠ being safe; patterns like runs, trends, or cycles may still reveal special causes.

“Sources of Variation”

• Key idea: Variation has many sources (also called causes) — to manage quality, you must first understand where variation originates.
• Process-induced variation ("6 Ms"):
  • Man, Machine, Method, Material, Measurement, Mother Nature
• Customer-induced variation comes from:
  • Arrival times, requests, capabilities, effort, and expectations.

“How to Properly Manage Variation”

• Common Cause Variation is built into the system. ➔ To reduce it, improve or redesign the process (better methods, training, tools, materials).
  • Red Bead Experiment: If the system is bad, hard work alone won't fix it — only system change will.
• Special Cause Variation signals something abnormal. ➔ Requires root cause analysis and targeted corrective action — not general system changes.
• Never "tamper" with a stable system based on normal ups and downs ➔ Tampering increases variation and degrades performance.
  • Funnel Experiment: Good intentions to "fix" every deviation can destroy a stable process.

Lean 🧹 “If it doesn’t add value, it’s waste.”

• Main Focus: Improve efficiency by eliminating waste and enhancing flow
• Philosophy Origin: Toyota Production System (TPS)

Six Sigma 📊 “Measure it to improve it.”

• Main Focus: Improve effectiveness by reducing variation and defects
• Philosophy Origin: Motorola (1980s) – grounded in statistical quality control and customer expectations