1.1.3 Deliverables of a Lean Six Sigma Project

Deliverables of a Lean Six Sigma Project Introduction to Project Deliverables Deliverables of a Lean Six Sigma project are the tangible outputs that demonstrate progress, rigor, and results across the DMAIC phases. They make the work auditable, repeatable, and sustainable. Every deliverable should: - Align with problem and business need - Be evidence-based, using data and analysis - Be phase-appropriate, supporting gate reviews - Be clear and complete, so another practitioner could follow the logic This article focuses only on deliverables expected across Define, Measure, Analyze, Improve, and Control, at a depth consistent with advanced practice. --- Define Phase Deliverables Project Charter The project charter is the foundational Define-phase deliverable that frames the project and sets expectations. Key elements: - Business case - Why the project matters now - Financial and non-financial impacts - Problem statement - Specific, measurable problem - Describes gap between current performance and target - Avoids causes and solutions - Goal statement - Quantified target (e.g., reduce defect rate from X to Y by date) - Time-bound and realistic - Scope - Clear boundaries (in-scope and out-of-scope) - Process start and end points - High-level timeline and milestones - Expected completion dates for each DMAIC phase - High-level risks and assumptions - Constraints that may affect deliverables or timing A strong charter is testable: it should be possible at the end of the project to say clearly whether the goal was met within scope and time. SIPOC Diagram The SIPOC (Suppliers–Inputs–Process–Outputs–Customers) is a high-level process map used early in Define. Essential contents: - Suppliers: key providers of inputs - Inputs: critical materials, information, or resources - Process: 4–7 high-level steps, end-to-end - Outputs: products, services, or information produced - Customers: receivers of the outputs Deliverable expectations: - Captures the full process relevant to the problem statement - Ensures alignment on process boundaries - Identifies where critical data will come from and where CTQs exist Voice of the Customer and CTQs Define produces clarity on customer needs and their translation into measurable requirements. Key deliverables: - VOC summary - Collected input from customers (external or internal) - Themes categorized (e.g., quality, speed, reliability) - CTQ (Critical-to-Quality) tree or list - Translation of vague needs into measurable characteristics - For each CTQ: definition, unit of measure, target, and specification limits These deliverables ensure the project’s success criteria reflect customer value, not just internal preferences. High-Level Process Map Beyond the SIPOC, a high-level (often “as-is”) process map at a slightly more detailed level is typically completed. Deliverable characteristics: - End-to-end flow from trigger to closure - Clear identification of main paths and key decision points - Visual separation of major process stages This map establishes a baseline understanding of flow and helps later with data collection planning. --- Measure Phase Deliverables Detailed Process Map and Value Stream View In Measure, the process map is refined to support precise measurement and waste identification. Deliverables include: - Detailed process map - Step-level sequence with decisions, rework loops, and handoffs - Identification of where data will be collected (e.g., at step, queue, output) - Value-added vs non-value-added classification - Each step categorized as value-added, non-value-added but necessary, or non-value-added waste - Cycle time and wait time annotations (when data become available) These deliverables provide a structural basis for measurement and later root cause analysis. Data Collection Plan A rigorous data collection plan is a central Measure-phase deliverable. Key elements: - Operational definitions - Clear definitions of defects, opportunities, units, and measures - Unambiguous rules so different people would measure the same way - Data sources and locations - Systems, forms, machines, or manual observation points - Sampling strategy - Sampling method (e.g., random, systematic) - Sample size and frequency - Time period and conditions (shifts, days, product types) - Data collection procedures - Who collects, how, and with what tools - Instructions to avoid bias and missing data The plan must be detailed enough that data quality and traceability can be objectively evaluated later. Measurement System Analysis (MSA) Results MSA evaluates whether the measurement system is reliable for the project’s purpose. Typical deliverables: - MSA plan - Type of study (e.g., Gage R&R for variable data; attribute agreement for attribute data) - Number of appraisers, parts/items, and repetitions - MSA summary results - For variable data: metrics such as % of variation due to measurement system (e.g., %GRR), repeatability, reproducibility - For attribute data: percent agreement within appraiser, between appraisers, and versus standard - Conclusion and action - Decision on suitability of the measurement system - Any calibration, training, or method changes implemented A valid Measure phase requires documented assurance that the data are trustworthy for subsequent analysis. Baseline Performance and Capability Measure concludes with a quantified baseline of the process. Key deliverables: - Descriptive statistics of key metrics - Mean, median, standard deviation, range, distribution shape - Baseline performance metrics - Defects per unit (DPU), defects per million opportunities (DPMO), yield - Current sigma level for critical CTQs - Process capability analysis (when appropriate) - Cp, Cpk for stable processes with known specification limits - For non-normal data, appropriate alternative capability methods - Graphical displays - Histograms, boxplots, run charts, Pareto charts as needed to visualize baseline These deliverables define the “before” state against which improvement will be judged. --- Analyze Phase Deliverables Verified Problem Statement and Focus Metric As understanding deepens, the problem statement and focus metric may be refined. Deliverables: - Confirmed or updated problem statement - Now supported by data, not just perception - Primary Y (output) metric - Clearly selected, with rationale - Linked to CTQ and business impact This ensures that analysis and improvement address the most critical measurable outcome. Root Cause Analysis Artifacts Analyze creates a chain of evidence from symptoms to causes. Common deliverables: - Cause-and-effect (Ishikawa) diagram - Structured listing of potential causes categorized (e.g., Method, Machine, Material, Man, Measurement, Environment) - 5 Whys or similar logic trail - Documentation of how deeper causes were identified - Process analysis outputs - Time analysis, rework loops, bottleneck identification, handoff issues These deliverables show the breadth of considered causes before narrowing to vital few. Data-Based Hypothesis and Statistical Analysis Analyze-phase deliverables must show how suspected causes were tested with data, not just opinion. Key elements: - Analysis plan - Which tools and tests will be used and why (e.g., correlation, regression, t-tests, ANOVA, chi-square) - Cleaned and structured analysis dataset - Documentation of data cleaning: outliers, missing data, transformations if used - Hypothesis test and modeling results - Stated hypotheses (H₀ and H₁) for each test - p-values, confidence intervals, and effect sizes where applicable - Graphical analysis (e.g., boxplots by factor level, scatter plots, interaction plots) - Identified Xs (critical inputs) - List of statistically and practically significant factors - Direction and magnitude of impact on the Y The core deliverable is a clear, evidence-based explanation of which factors truly drive variation in the critical outcome. Verified Root Causes Analyze should end with a concise, validated set of root causes. Deliverables: - Prioritized cause list - Ranked by impact on Y and ease/difficulty of influence - Verification evidence - Data and analysis that confirm these causes are real and significant - Problem-to-cause logic - A succinct narrative or diagram linking problem → drivers → root causes This becomes the foundation for designing effective improvements. --- Improve Phase Deliverables Solution Generation and Selection Improve begins with structured solution creation and evaluation. Deliverables: - List of potential solutions - Derived from root causes, not random brainstorming - Screening and selection criteria - Impact, feasibility, cost, risk, alignment with constraints - Solution selection documentation - Why specific solutions were chosen or rejected - How trade-offs were made These deliverables demonstrate that improvement ideas are logically grounded in analysis findings. Risk Assessment and Mitigation (FMEA) A Failure Modes and Effects Analysis (FMEA) or similar risk assessment is usually a key Improve deliverable. Typical FMEA contents: - Process steps and potential failure modes - What could go wrong with the new or modified process - Effects and causes of each failure - Customer or process impact, suspected causes, existing controls - Risk ratings - Severity, occurrence, and detection ratings with resulting risk priority values - Mitigation actions - Actions to reduce high-risk failure modes - Updated ratings after mitigation where applicable This deliverable ensures improvements are robust and do not introduce new, unmanaged risks. Pilot Plan and Pilot Results Before broad rollout, a controlled pilot validates the effectiveness of proposed solutions. Pilot deliverables: - Pilot plan - Objectives and success criteria (linked to primary Y and critical CTQs) - Scope of pilot (where, when, which products/customers) - Data collection and monitoring plan during pilot - Pilot execution record - Evidence that the plan was followed or, if not, how it deviated - Pilot results - Comparison of performance before vs during pilot - Statistical evaluation (e.g., tests of means or proportions, control charts) where appropriate - Pilot conclusion - Whether criteria were met and what adjustments are needed before full-scale implementation A strong pilot deliverable package reduces the risk of failure on full rollout. Finalized Improvement Design Once solutions are validated, the improved process design must be clearly documented. Key deliverables: - Future-state process map - Updated flow with new steps, eliminated waste, reduced rework - New or revised standards and procedures - Work instructions, checklists, job aids - Parameter settings for equipment or systems - Resource and infrastructure changes - Required tools, layouts, system configuration updates The improved design is what transitions into the Control phase for long-term stabilization. --- Control Phase Deliverables Control Plan The control plan is the central deliverable that defines how performance will be maintained. Essential elements: - Controlled characteristics (Ys and critical Xs) - Specific metrics to monitor, with clear operational definitions - Control methods and frequency - How each metric is measured (instrument, system, form) - How often, by whom, and in what conditions - Control limits and action thresholds - Where control charts are used, type of chart and its limits - Clear criteria for out-of-control signals or specification violations - Reaction plan - Step-by-step actions when a metric goes out of control - Escalation path and documentation requirements This deliverable operationalizes the “hold the gain” objective of Control. Control Charts and Ongoing Monitoring Evidence When applicable, statistical process control is documented and deployed. Deliverables: - Control chart selection and rationale - Type of chart (e.g., X̄–R, I–MR, p, u) aligned with data type and sampling - Initial control chart setup - Baseline data used for establishing center line and control limits - Demonstration that the post-improvement process is stable (or steps taken if not) - Monitoring plan - Who maintains charts, reviews patterns, and responds to signals These deliverables demonstrate that the process is not only improved but also statistically monitored. Standardization and Documentation Improvement must be embedded in formal documentation so it does not revert. Deliverables: - Updated standard operating procedures (SOPs) - Reflecting new process flow and best practices - Training materials and completion records - Training content aligned with new standards - Evidence that relevant personnel have been trained and are competent - Visual controls and checklists - Visual aids at the point of work to reinforce correct methods This documentation ensures the improved process is consistently executed. Verified Sustained Performance Before formal closure, there must be evidence that gains are sustained. Key deliverables: - Post-improvement performance data - Sufficient time window of data under normal conditions - Same definitions and methods as baseline for comparability - Before-and-after comparison - Statistical confirmation that the improvement is significant and maintained - Updated sigma level or capability indices for key CTQs - Residual issue log and follow-on actions - Items that require continued monitoring or future projects These deliverables confirm that the project has achieved and preserved its goals. --- Cross-Phase Deliverables Project Storyboard or Tollgate Package Across phases, work is often consolidated into a storyboard or set of tollgate documents. Typical contents per phase: - Define: charter, SIPOC, VOC/CTQs, initial high-level map - Measure: detailed map, data collection plan, MSA results, baseline capability - Analyze: root cause analysis, statistical findings, verified vital Xs - Improve: selected solutions, FMEA, pilot results, future-state design - Control: control plan, control charts, sustainment evidence, updated documentation This integrated deliverable: - Shows logical progression from problem to solution - Provides traceability from data to decisions - Supports formal gate reviews and organizational learning Financial Benefit and Results Summary A concise summary of quantifiable impact is a critical closing deliverable. Key elements: - Baseline vs improved performance - Clearly stated and numerically supported (e.g., DPMO, cycle time, cost per unit) - Financial impact estimation - Annualized savings or revenue impact, with assumptions stated - Non-financial benefits - Defect reduction, lead-time reduction, customer satisfaction changes, risk reduction This deliverable aligns project outcomes with organizational objectives and justifies the investment. --- Common Quality Criteria for Deliverables To ensure deliverables are consistently robust: - Clarity - Free of ambiguity, jargon minimized or defined - Traceability - Each conclusion logically follows from documented analysis - Consistency - Definitions, metrics, and assumptions are used consistently across phases - Data integrity - Data sources, transformations, and limitations are transparent - Actionability - Deliverables support decisions, behavior changes, and long-term control Applying these criteria across all DMAIC phases strengthens both the project outcome and its documentation. --- Summary Deliverables of a Lean Six Sigma project form a coherent chain from problem definition to sustained improvement: - Define establishes the project’s purpose and boundaries through a solid charter, SIPOC, VOC/CTQs, and high-level mapping. - Measure creates a reliable factual base with detailed process maps, a data collection plan, MSA results, and baseline capability. - Analyze identifies and verifies true root causes using structured root cause artifacts and data-driven statistical analysis. - Improve designs, tests, and finalizes effective solutions via solution selection, risk assessment, piloting, and future-state design. - Control secures the gains with a rigorous control plan, monitoring mechanisms, standardized documentation, and proof of sustained performance. Cross-phase deliverables such as the project storyboard and financial impact summary integrate this work into a clear narrative. Mastery of these deliverables ensures that Lean Six Sigma projects are not just completed but demonstrably effective, auditable, and sustainable.