Core Concepts in Operations Management, Quality, and Behavioral Science

Posted on Dec 4, 2025 in Business Administration and Management (BAM)

Behavioral Science and Decision Making

Behavioral Science is the study of why people act and make decisions the way they do.

Key Insight: If you understand the dynamics of decision making, you can influence that decision in your favor.

Rational Decision Making

1. Consider the options, then pick the one that maximizes profit or experience.
2. Assess pros and cons objectively without prejudice.

Irrational Decision Making

• Allows irrelevant biases, emotions, and environment to influence our decisions.

Predictably Irrational

• Individuals are susceptible to the same influences over and over again.

Service Recovery Paradox

A customer becomes more loyal after a firm successfully resolves an issue than if the service had been perfect from the start.

Stages of Service Recovery

• Pre-Recovery: Begins at the first occurrence of failure. The firm must understand customer expectations of remediation.
• Immediate Recovery: The firm decides how to resolve the failure. Response speed is critical. Resolution should be correlated to the service failure. Avoid generic responses.
• Follow-Up: Occurs after the situation has been resolved. Implement changes so the failure does not occur again.

Framing Expectations

We inherently expect higher-priced items to be higher quality (this extends to brand names, packaging, and presentation).

• Why it Works: Confirmation bias (we hate to be wrong).
• How to Use It: Start with a higher price to frame expectations, then offer a discount to reach the market price.

Decoy Effect

A middle option is useless, and a third option is “asymmetrically dominated,” making the target option seem superior, even if it is not strictly needed.

Free Effect

People have a strong emotional response to “Free,” and there is pain associated with spending money.

Data Analytics Fundamentals

Data Analytics is the act of processing, cleaning, and modeling data with the goal of discovering useful information to support decision making.

Benefits of Data Analytics

• Helps us make better decisions (removes opinions).
• Helps us make predictions about future events.
• Helps us focus (or target) specific problems or customers.

Privacy vs. Convenience Trade-Off

“If you don’t pay for a product, you are the product.”

This is a trade-off where users often give up privacy for easier, personalized experiences, while businesses use data to create these convenient services.

Types of Data Analytics

Note: There is a linear relationship between complexity and value.

• Descriptive Analytics: Answers “What happened?” Gives valuable insights into the past, signaling something is wrong or right, without explaining why.
• Diagnostic Analytics: Answers “Why something happened?” Measures data against other data to find relationships and dependencies.
• Predictive Analytics: Answers “What is likely to happen?” Uses the findings of Diagnostic Analytics to detect tendencies, clusters, and exceptions, and to predict future trends.
• Prescriptive Analytics: Answers “What action should we take?” Takes the predicted options and suggests a range of prescribed actions and the potential outcomes of each action.

Operations Efficiency Applications

1. Optimization Models: Maximize one variable while minimizing others.
2. Credit Acceptance: Clustering prospective customers into those who will default or not default.
3. Predictive Maintenance & Condition Based Monitoring: Collecting data from the Internet of Things (IoT).

Service Operations Management

Service Operations develops the processes and decisions of a company for the simultaneous production and consumption of an intangible product to ensure customer success and experience.

Why Services Are Important

Good service leads to happy customers, which generates revenue. However, providing good service is very difficult, and “good” service is often not good enough.

Evolution of Economic Offerings

Agricultural → Manufacturing → Service → Experience

• Services have moved past transactional interactions to experience-based relationships.
• Experiences create value by engaging and connecting with the customer in a personal and memorable way. Businesses can charge more for experiences.
• (Experiences → Relationships → Loyalty)

Service vs. Product Characteristics

• Services are created and consumed simultaneously.
• You cannot inventory unused service capacity.
• Customer participation plays a key role in their own satisfaction.
• It is almost impossible to patent a service.
• Services often have low barriers to entry.

Challenges in Service Operations

• Customers are all unique.
• The customer’s perspective is all that matters.
• It is difficult to replicate assembly line and economies of scale cost reduction techniques found in products.
• Customer compatibility plays a role in satisfaction.
• Variability is much more difficult to reduce than in manufacturing.

Key to Success

Setting and meeting customer expectations is key.

Customer Satisfaction Metrics

Measured by surveys, retention rate, and Net Promoter Score (NPS).

The Service Profit Chain

This model links profitability to process design and employee satisfaction.

Internal Service Quality → Employee Satisfaction → Employee Retention & Productivity → Great Customer Service → Customer Satisfaction → Customer Loyalty → Higher Revenue → Higher Profit

Benefits of the Chain

• Loyal customers are cheaper to serve (and willing to pay more).
• Productive employees lower operating costs.
• Employee retention lowers training, hiring, and inefficiency costs.

Servicescape

The physical facility or environment where the service takes place.

• Reflects the values of the organization without words.
• Must be flexible to accommodate changes in demand.
• Should put the customer in the mood to spend money.

Types of Service Variability

• Arrival Variability: Customers arrive at times when there are not enough service providers.
• Request Variability: Patients arrive at a hospital, all with different needs.
• Capability Variability: A patient is unable to explain symptoms to a doctor.
• Effort Variability: A customer does not provide all financial documentation to their tax advisor.
• Subjective Preference Variability: Customers receive identical service but perceive its quality differently.

Strategies for Variability

• Companies that rely on good customer experiences tend to accommodate variability.
• Companies that rely on operational simplicity tend to try and reduce variability.

Managing Demand and Capacity

This is a major challenge because there is no inventory as a safety net. Hiring new employees does not yield results overnight, and capacity must match demand in real-time. Forecasting is more vital for services than manufacturing.

Quality Management Principles

The Importance of Quality

1. Customers expect a certain level of quality for the products/services they buy.
2. The penalty for poor quality is much greater than the benefit of good quality.

Product/Service Quality

Meeting expectations → Customer Satisfaction → Higher Revenue

Process Quality

Reducing process variability → Less waste/defects → Lower Costs

Trade-Off: Customer Value vs. Cost. The most important component of any product is the one that fails.

Framing as a Cognitive Bias

People tend to avoid risk when a negative frame is presented and seek risk when a positive frame is presented.

Types of Quality Focus

• Product Quality: Characteristics that meet customer acceptability.
• Process Quality: Consistent results within a specified range.
• Decision Quality: A structured process for making sound choices, focusing on the quality of the decision-making process itself.

Total Quality Management (TQM)

Managing the entire organization to excel in all dimensions of products and services that are important to customers.

Two Operational Goals of Quality

1. Careful Design of the Product/Service: Focuses on the inherent value of the product in the marketplace.
2. Ensure Consistent Production: Focuses on the degree to which the product design specifications are met.

Costs of Quality

(Costs increase down the list)

• Appraisal Costs: Inspecting, auditing, and testing.
• Prevention Costs: Efforts to keep defects from occurring.
• Internal Failure Costs: Defects caught internally and either scrapped or corrected.
• External Failure Costs: Defects seen by the customer.
• Opportunity Costs: Loss of future business due to poor quality reputation.

Quality Objective

To deliver a consistent product or service to the customer that meets their expectations.

Six Sigma Methodology

A philosophy and set of methods used to eliminate defects in products and processes. It seeks to reduce variation in the process that leads to defects. The goal is no more than 3.4 defects per million opportunities (DPMO).

The DMAIC Process

• Define: Identify customers and their priorities.
• Measure: Determine how to measure the process and how it is performing.
• Analyze: Determine the most likely causes of defects.
• Improve: Identify means to remove the causes of defects.
• Control: Determine how to maintain the improvements.

Quality Management Tools

• Control Chart: Shows how process output varies over time.
• Fishbone (Ishikawa) Diagram: Used for cause-and-effect analysis.
• Flowchart: A diagram of the sequence of operations.
• Run Chart: Depicts trends in data over time.
• Pareto Chart: Helps to break down a problem into components (80/20 rule).
• Checksheet: A basic form to standardize data collection.
• Opportunity Flow Diagram: Used to separate value-added from non-value-added steps.

Lean Management

Lean Management focuses on eliminating waste (anything that adds cost but not value) and then simplifying the process.

Lean Principles

1. Continuous Improvement: Continuously improving processes to enhance efficiency and quality. This involves analyzing processes to identify and eliminate waste (process steps, material, labor, time, money, etc.).
2. Just-in-Time (JIT): Process steps are performed “Just-in-Time.” Nothing is done before it is needed.

Seven Sources of Waste (Muda)

1. Waste from overproduction.
2. Waste of waiting time.
3. Transportation waste.
4. Inventory waste.
5. Processing waste.
6. Waste of motion.
7. Waste from product defects.

Pull Manufacturing (Make-to-Order, JIT)

Characterized by low internal costs but no safety net.

• Process efficiency is the goal.
• Eliminates Work-In-Process (WIP) inventory and bottlenecks.
• Focuses on “busy” materials, not workstations.
• Only work when needed to produce a sold product.
• No “buffer” if a problem occurs.

Push Manufacturing (Make-to-Stock)

Characterized by high internal costs with a safety net.

• Focuses on personal workstation output maximization.
• Prioritizes workstation efficiency.
• Focuses on busy employees, not efficient material flow.
• Lots of defective product may accumulate before being noticed.
• High WIP inventory and bottlenecks are common.

Operations Planning and Capacity

Operations Planning is the process of turning a strategic plan into a detailed map of who does what and when.

Requirements for Operations Planning

• Requires an integrated effort between sales, product development, manufacturing, supply chain, logistics, and finance.
• Starts with a forecast of demand.
• Ends with an operational plan detailing needed resources: material requirements, manpower (and required skills), production capacity/scheduling, and distribution.

Revenue Management

Customers value products and services differently. Timing can significantly change the value (e.g., perishable goods vs. event-specific services).

Price Segmentation

Involves single versus multi-price optimization strategies.

Managing Demand Variation

Strategies for handling demand variation compared to forecasts:

If Demand is Lower than Forecasted:

• Idle employees and machinery.
• Layoffs.
• Try to switch to a different product.

If Demand is Higher than Forecasted:

• Outsource production.
• Work overtime.
• Hire new full-time or part-time employees.

Chase Strategy

Matches demand by hiring and laying off employees as necessary, resulting in no inventory buildup.

Level Strategy

Keeps production the same throughout the year, using inventory to match demand fluctuations.

Capacity Management

• Capacity: The design output of a process.
• Utilization: The ratio of actual output to design output (a common measurement).

Capacity Cushion

The amount of additional capacity needed to absorb variability and still meet demand. The required amount is directly related to the variability in the process.

Costs and Benefits

1. Unused capacity costs money by paying people/machines to sit idle.
2. Too little capacity costs money by not meeting demand.

Trade-Offs

• More cushion → Less risk, More cost.
• Less cushion → More risk, Less cost.

Optimal Strategy: Reduce the amount of variability in the process.

Types of Process Variability

• Customer Demand
• Supply Chain issues
• Worker Productivity
• Worker Attendance
• Machine Performance
• Machine Reliability

Work Standardization

Has an enormous impact on output and quality. The goal is the same output, in large quantities, efficiently.

Statistical Process Control (SPC)

SPC is a method of monitoring the quality of our process by observing variation in output. It is used to keep the process stable, consistent, and under control. Every output has a target value and upper and lower limits of acceptable variation. SPC uses samples from output measures to estimate the mean (average) and the amount of variation (standard deviation).

Key Principle: The smaller the standard deviation, the more under control the process is (less variation in the output).

SPC Terminology

• Control Charts: Shows how process output varies over time and helps identify when special cause variation occurs in the process.
• Process Capability: Assesses the process’s ability to remain within tolerance limits.
• Specification Limits (USL, LSL): The range of variation that is considered acceptable by the designer and customer.
• Process Control Limits (UPCL, LPCL): The range of variation that a process is naturally able to maintain.

Process Capability Rules

• If PCL > SL: The process is incapable of being defect-free.
• If SL > PCL: The process is capable of being defect-free.

Process Capability Index (Cpk)

Shows how well the parts being produced fit into the range specified by the design specification. A Cpk larger than 1 indicates the process is capable.

Sigma Level

An indication of how many outputs we can expect outside the specification limits (defects).

Changing Specification Limits

An acceptable solution if the current specification limits are so tight they do not add any value in the eyes of the customer.

Defect Probability

Process Performance Metrics

• Consistency: A process is consistent if its standard deviation is small.
• Accuracy: A process is accurate if its average performance is close to the target.