Defect Detectives

You are either running a platform or managing a restaurant kitchen — and the system you are part of is more connected than it looks. In Order Ops, every order accepted, every preparation time estimated, and every commission rate negotiated has consequences that ripple across the entire ecosystem. When the rain hits and drivers disappear, the question is not just whether your own operation holds — it is whether the system does.

Authors:

Dr. Jaya Priyadarshini

Academic Partner:

LEVEL

Undergraduate, MBA, Executive Ed, Graduate

TYPE

Multi Player

DURATION

90 mins

DISCIPLINE

Operations Management

Introduction

Defect Detectives: A Quality Control Simulation immerses participants in two realistic operational contexts a consumer goods manufacturing plant and a quick-commerce dark store in urban India both grappling with escalating defect-related customer complaints amid efficient workflows.

Assuming the role of Quality Control Manager, players analyze defect data sets, dashboards, and charts to identify patterns, uncover root causes, and formulate evidence-based improvement actions. The simulation integrates the sequential application of the 7 QC Tools, guiding structured analytical phases where each tool's output informs the next, culminating in a data-supported action plan and control-chart validation of process enhancements. The core objective is to reduce defects, stabilize processes, and elevate operational performance through data-driven problem solving.

Learning Objectives

Apply seven QC tools systematically
Identify root causes, not symptoms
Prioritise defects using Pareto
Assess stability with control charts
Integrate tools across PDCA cycle

Key Features

Two distinct operational contexts — a consumer-goods manufacturing plant and a quick-commerce dark store — each demanding the sequential application of the Seven QC Tools
Strict tool-chain progression aligned with the PDCA cycle, where each tool's output feeds the next and premature advancement incurs scoring penalties
Attempt-based scoring mechanism that discourages random guessing, with point decay across successive incorrect submissions
Performance evaluation across four dimensions: tool application accuracy, diagnostic consistency, conceptual understanding, and improvement validation via control charts
Facilitator dashboard providing class-level analytics and individual performance breakdowns across both scenarios

Educational Outcomes

Ability to diagnose quality problems systematically using data from both manufacturing and service operations
Proficiency in applying the Seven QC Tools as a coherent, interdependent chain rather than a set of isolated techniques
Capacity to distinguish between symptoms and underlying root causes using evidence-based reasoning
Skill to evaluate process stability and validate the impact of improvements using pre- and post-improvement control charts
A lasting mindset shift: quality improvement is diagnostic before prescriptive, and sustainable stability requires a disciplined diagnose–decide–validate cycle

Topics Covered

Seven QC Tools

PDCA Cycle & Continuous Improvement

Total Quality Management (TQM)

Statistical Process Control

Root Cause Analysis