Lean Six Sigma Refresher
Data Collection Plan Table
A Data Collection Plan in Lean Six Sigma (LSS) is a structured document that outlines what data will be collected, how it will be collected, and why it matters during a project. It ensures that the team gathers reliable, relevant, and sufficient data to analyze problems and validate improvements.
📄 Purpose
Clarity: Defines exactly what information is needed to measure the problem and improvement.
Consistency: Ensures data is collected in a standardized way across team members.
Accuracy: Reduces bias and errors by specifying sources, methods, and timing.
Efficiency: Prevents wasted effort on irrelevant or excessive data.
Alignment: Connects data directly to project goals and metrics.
🧩 Typical Components
Objective – Why the data is being collected (e.g., measure defect rate, cycle time).
Metrics/Variables – Specific data points (e.g., number of defects per batch, processing time in minutes).
Operational Definitions – Clear definitions so everyone measures the same way (e.g., “defect = any product failing inspection criteria”).
Data Sources – Where the data comes from (systems, logs, observations, surveys).
Collection Method – How data will be gathered (manual checklists, automated reports, sampling).
Frequency & Duration – When and how often data will be collected (daily, weekly, per batch).
Responsible Person(s) – Who is accountable for collecting and validating the data.
Validation Plan – Steps to ensure data integrity (spot checks, audits, calibration).
✅ Value in LSS Projects
Provides the foundation for the Measure phase of DMAIC.
Ensures analysis is based on facts, not assumptions.
Builds credibility with stakeholders by showing objective evidence.
Supports root cause analysis and validates whether improvements are working.
Takeaway: A Data Collection Plan is the blueprint for trustworthy measurement. Without it, Lean Six Sigma projects risk basing decisions on incomplete or unreliable data.