Posted: September 17th, 2024

Six Sigma DMAIC Implementation and Process Analysis

Kingston University – BS7102 Operations Management
Assessment Brief: Six Sigma Implementation and Operational Process Mapping

This assessment requires you to produce a 2,500-word individual operations improvement report for a UK manufacturing or service organisation of your choice. You will apply the DMAIC framework to diagnose a specific operational process, construct a process map identifying non-value-adding activities, and propose a Six Sigma implementation plan with measurable targets. The report carries 50% of the module mark and is assessed on the rigour of your process analysis, the depth of your DMAIC application, and the practicality of your improvement recommendations. Submit via Canvas by 23:59 on Friday 22 May 2026.

Module and Assessment Details

Module code: BS7102
Module title: Operations Management
Assessment type: Individual written report
Weighting: 50% of total module mark
Word count: 2,500 words (+/- 10%, excluding reference list, appendices, and process maps)
Submission deadline: Friday 22 May 2026, 23:59 (UK time)
Submission method: Canvas assignment portal (Turnitin-enabled)
Referencing style: Harvard (Kingston University standard)
Module leader: Dr Priya Nair

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Context

Kingston University’s BS7102 Operations Management module equips postgraduate students with the analytical tools to diagnose and improve operational processes across manufacturing and service sectors. The module sits within Kingston Business School’s broader commitment to practice-led teaching and aligns with the Chartered Institute of Logistics and Transport’s professional standards. This assessment builds directly on the weekly seminar work covering process mapping, value stream analysis, the DMAIC cycle, and statistical process control. It also connects to the formative process analysis workshop run in Weeks 4 and 5, where you practised constructing a current-state process map and identifying bottleneck activities. The skills developed in this assessment are directly transferable to roles in operations consultancy, continuous improvement, and production management.

Task Description

You are an operations improvement consultant engaged by a client organisation that has identified declining process efficiency in one of its core operational areas. Select one organisation from the following sectors: food and beverage manufacturing, pharmaceutical production, logistics and warehousing, or financial services operations. The organisation must have publicly available operational data or industry benchmark reports that allow you to substantiate your analysis.

Your task is to produce a formal operations improvement report addressed to the client’s operations director. The report must accomplish four things. First, select a specific operational process and construct a current-state process map that identifies all process steps, decision points, handoffs, and delays. Second, apply the Define and Measure phases of DMAIC to quantify the process problem, including process cycle efficiency, defect rates, or throughput metrics. Third, apply the Analyse phase to identify root causes of inefficiency using at least two analytical tools such as cause-and-effect diagrams, Pareto analysis, or five whys analysis. Fourth, propose an Improve and Control plan that specifies the Six Sigma tools to be applied, the expected improvement targets, and the monitoring mechanisms to sustain the gains.

The report must follow a professional consultancy structure: executive summary, introduction, process selection and context, current-state process map, Define and Measure phases, Analyse phase, Improve and Control plan, recommendations, and reference list. The process map and any supporting calculations should be included as appendices and do not count towards the word count.

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Assessment Requirements

• Use at least eight academic or professional sources, including a minimum of four peer-reviewed journal articles published between 2020 and 2026.
• Apply the DMAIC framework explicitly, with each phase clearly signposted in the report structure.
• Include a current-state process map within the appendices, using standard process mapping symbols or swimlane format.
• Calculate at least two quantitative process metrics, such as process cycle efficiency, first-pass yield, or defects per million opportunities.
• Cite all sources using the Harvard referencing system. In-text citations must include page numbers where you quote directly.
• Write in formal academic English. Avoid first-person pronouns except in the executive summary, where “this report” or “the analysis” is preferred.
• Submit as a single Word document (.docx). Font: Calibri or Arial, size 12. Line spacing: 1.5. Margins: 2.54 cm.
• The executive summary must not exceed 200 words and does not count towards the word limit.

Marking Rubric

Criteria	Weight	Distinction (70–100)	Merit (60–69)	Pass (40–59)	Fail (0–39)
Process mapping and problem definition	25%	Process map captures all critical steps, decision points, and delays with precision; problem statement is specific, measurable, and grounded in operational data.	Process map is accurate and complete; problem statement is clear and mostly well-substantiated.	Process map is present but lacks detail; problem statement is vague or poorly defined.	Process map is absent or inaccurate; problem statement is missing or irrelevant.
DMAIC application and analytical depth	30%	DMAIC phases are applied with rigour; quantitative metrics are correctly calculated and interpreted; root cause analysis uses multiple tools to identify systemic issues.	DMAIC phases are applied correctly; metrics are mostly accurate; root cause analysis identifies relevant causes.	DMAIC phases are attempted but lack depth; metrics contain errors; root cause analysis is superficial.	DMAIC is not applied or is fundamentally misunderstood; metrics are absent or incorrect.
Improvement plan and feasibility	25%	Improve and Control plans are specific, actionable, and proportionate; targets are evidence-based; monitoring mechanisms are clearly defined with ownership and frequency.	Improvement plans are logical and mostly well-justified; monitoring mechanisms are adequate.	Improvement plans are generic; monitoring mechanisms are vague or absent.	Improvement plans are missing or disconnected from the analysis.
Structure, presentation, and academic writing	20%	Report is professionally structured; writing is clear, concise, and error-free; executive summary captures the essential argument and recommendations.	Report is well-structured; writing is clear with minor errors; executive summary is adequate.	Report follows the required structure; writing is comprehensible but contains noticeable errors.	Structure is unclear; writing contains frequent errors that impede understanding.

Sample Answer: Six Sigma Implementation and Operational Process Mapping

Mapping the Current State of a Pharmaceutical Production Line

A strong response to this brief begins by anchoring the process analysis in a specific, verifiable operational context. For a pharmaceutical production line, the current-state process map might trace the flow from raw material receipt through dispensing, granulation, compression, coating, and packaging, noting the queue times between each stage. The Define phase would then articulate the problem in measurable terms: for instance, that the compression stage achieves only 72% first-pass yield, resulting in 28% of batches requiring rework or rejection. The Measure phase would calculate process cycle efficiency by dividing value-added time by total lead time, often revealing that value-added activities account for less than 10% of total throughput time. Research by Adeodu et al. (2023) in Heliyon demonstrates how a [structured DMAIC framework improved warehouse process efficiency by 34%](https://doi.org/10.1016/j.heliyon.2023.e14915) through systematic identification of non-value-adding activities. The Analyse phase would deploy a cause-and-effect diagram to trace the 28% rejection rate to factors including inconsistent granule moisture content, worn compression tooling, and operator variability in machine setup. A Pareto analysis would then rank these causes by frequency, prioritising the tooling and moisture control issues for immediate intervention. The report’s strength lies in connecting each analytical finding to a specific operational consequence, rather than presenting tools as disconnected exercises.

Applying DMAIC to a Logistics and Warehousing Operation

Students frequently treat DMAIC as a linear checklist rather than an iterative problem-solving cycle, which weakens the analytical coherence of their reports. A distinction-level response demonstrates how findings from the Analyse phase feed back into the Define and Measure phases, refining the problem statement as new evidence emerges. For a logistics operation, the initial problem might be defined as “order picking delays exceeding 45 minutes per pallet.” The Measure phase would quantify the current state through time-and-motion studies, identifying that pickers spend 38% of their time walking between locations rather than picking. The Analyse phase would use five whys analysis to trace this back to warehouse layout decisions made three years earlier, when product velocity classifications were not considered. Gilligan et al. (2023) in the TQM Journal show how Six Sigma DMAIC methodology [reduced process variability and improved yields in an Irish meat processing plant](https://doi.org/10.1108/TQM-02-2023-0040) by applying the same iterative logic: define the defect, measure its frequency, analyse its causes, and then implement targeted improvements. For the logistics case, the Improve phase might propose a slotting optimisation project using ABC velocity analysis, while the Control phase would establish weekly pick-path audits and a dashboard tracking walk-time percentage. The report must then specify the expected improvement in order picking time, the resources required, and the monitoring mechanisms that will sustain the gains after the project closes.

From Root Cause to Control Plan: Sustaining Process Gains

The Control phase is where many reports lose marks because students propose improvement actions without specifying how the process will be monitored after implementation. A distinction-level Control plan defines the metric to be tracked, the target value, the measurement frequency, the responsible owner, and the escalation trigger if performance drifts. For a pharmaceutical compression process, the Control plan might specify that granule moisture content is measured every two hours, with a target range of 2.0 to 3.0 percent, owned by the shift quality technician, and escalated to the production manager if two consecutive readings fall outside the range. This approach aligns with the DMAIC principle that improvements must be institutionalised through standard work, visual management, and statistical process control. Research by Mittal et al. (2023) in Heliyon demonstrates that Six Sigma DMAIC projects [sustain improvements most effectively when control plans include clear ownership and routine monitoring](https://doi.org/10.1016/j.heliyon.2023.e14915) rather than relying on ad hoc checks. The strongest reports also include a risk assessment for the improvement plan itself, identifying what could cause the gains to erode and specifying contingency actions. Common risks include staff turnover among trained operators, supplier changes that alter raw material characteristics, and production volume increases that stress the revised process beyond its design capacity.

Research, Writing, and Citation Guidance

Why This Matters in Practice

Six Sigma and DMAIC skills are among the most transferable operational competencies in manufacturing, logistics, and service industries. The UK’s Made Smarter programme reported in 2024 that manufacturers implementing structured continuous improvement methodologies achieved average productivity gains of 12% within eighteen months. Professional bodies including the Chartered Quality Institute and the American Society for Quality recognise Six Sigma certification as evidence of operational competence. The ability to map a process, quantify inefficiency, identify root causes, and design a control plan is therefore directly applicable to roles in production management, quality assurance, and operations consultancy.

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Frequently Asked Question

How do I calculate process cycle efficiency for a DMAIC report?

Process cycle efficiency is calculated by dividing value-added time by total lead time and expressing the result as a percentage. Value-added time includes only those activities that transform the product or service in ways the customer values. Queue times, inspection delays, rework loops, and transportation between stages do not count as value-added. For example, if a production process has 45 minutes of value-added activity and 12 hours of total lead time, the process cycle efficiency is 45 minutes divided by 720 minutes, which equals 6.25%. Most manufacturing processes operate between 5% and 25% process cycle efficiency, and service processes often fall below 5%. The metric is useful because it quantifies the scale of improvement opportunity before any changes are made, providing a baseline against which the Improve phase can be evaluated.

Recommended Reading

• Adeodu, A., Maladzhi, R., Kana-Kana Katumba, M.G. and Daniyan, I. (2023) ‘Development of an improvement framework for warehouse processes using lean six sigma (DMAIC) approach. A case of third party logistics (3PL) services’, Heliyon, 9(4), e14915. doi: 10.1016/j.heliyon.2023.e14915.
• Gilligan, R., Moran, R. and McDermott, O. (2023) ‘Six Sigma application in an Irish meat processing plant to improve process yields’, TQM Journal, 35(9), pp. 210–230. doi: 10.1108/TQM-02-2023-0040.
• Mittal, A., Gupta, P., Kumar, V., Al Owad, A., Mahlawat, S. and Singh, S. (2023) ‘The performance improvement analysis using Six Sigma DMAIC methodology: A case study on Indian manufacturing company’, Heliyon, 9(4), e14915. doi: 10.1016/j.heliyon.2023.e14915.
• Project Management Institute (2021) A Guide to the Project Management Body of Knowledge (PMBOK Guide). 7th edn. Newtown Square, PA: PMI.
• Yadav, N., Upadhyay, A., Kumar, A. and Gilani, H. (2022) ‘Achieving operational excellence through the lens of lean and Six Sigma during the COVID-19 pandemic’, The International Journal of Logistics Management, 33(3), pp. 818–835. doi: 10.1108/IJLM-06-2021-0331.

Next Assessment: Week 9 Discussion Post

Module: BS7102 Operations Management
Week: 9
Assessment type: Discussion board post and peer responses
Weighting: 10% of total module mark
Initial post deadline: Wednesday of Week 9, 23:59
Peer response deadline: Sunday of Week 9, 23:59

Drawing on your Week 8 seminar on lean thinking and continuous improvement, write an initial discussion post of 300–400 words that addresses the following question: “Can Six Sigma and lean methodologies coexist effectively within the same operational system, or do their underlying philosophies create irreconcilable tensions?” Use one example from a UK or international organisation to support your argument. Your post must engage with at least one academic source from the module reading list and one contemporary industry example. After posting, respond to at least two peers with substantive comments of 100–150 words each. Responses must advance the discussion by introducing new evidence, challenging an assumption, or connecting the peer’s argument to a different operations management framework. Marks are awarded for the quality of the initial argument, the integration of evidence, and the analytical depth of peer responses.

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