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Top Six Sigma Case Study 2024

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Six Sigma is an array of methods and resources for enhancing corporate operations. When Bill Smith was an engineer at Motorola, he introduced it in 1986 to find and eliminate mistakes and defects, reduce variance, and improve quality and efficiency. Six Sigma was first used in manufacturing as a quality control tool. When long-term defect levels are less than 3.4 defects per million opportunities ( DPMO ), Six Sigma quality is reached.

Six Sigma case study   offers a glimpse into how various companies have harnessed the five distinct phases: defining, measuring, analyzing, improving, and controlling, principles of Six Sigma to overcome challenges, streamline processes, and improve across diverse industries.

What Are Six Sigma Case Studies, and Why Are They Important?

Six Sigma case studies examples   show how Six Sigma techniques have been used in businesses to solve issues or enhance operations. For practitioners and companies pondering enforcing Six Sigma concepts, these case studies are an invaluable resource to learn the advantages and efficacy of Six Sigma adoption.

Here are the reasons why six sigma case study is important:

Success Illustration: Case studies demonstrate how Six Sigma projects generate tangible advantages like better productivity, fewer defects, and more customer satisfaction while providing unambiguous evidence of their efficacy.

Learning Opportunities:  They deliver vital insights to use Six Sigma tools and processes realistically and allow others to learn from successful approaches and avoid common errors.

ROI Demonstration:  Case studies provide quantitative data to show the return on investment from Six Sigma projects, which helps justify resources and get support for future initiatives.

Promoting Adoption:  They cultivate a continuous improvement culture and show how Six Sigma concepts can be used in different situations and sectors, which encourages other businesses to embrace the methodology.

Become a Six Sigma Certified Professional and lead process improvement teams to success. Learn how to streamline processes and drive organizational growth in any industry. Join our Lean 6 Sigma training courses and transform your career trajectory with valuable skills and industry recognition.

Six Sigma Case Studies

Let us discuss some real-world case study on six sigma   examples of successful Six Sigma undertakings through case studies:

1. Six Sigma Success: Catalent Pharma Solutions

Do you know how Six Sigma techniques turned things around for Catalent Pharma Solutions?

Six Sigma methodologies, initially presented by Motorola in 1986 and prominently used by General Electric during CEO Jack Welch's leadership, are essential for enhancing customer contentment via defect minimization. Catalent Pharma Solutions, a top pharmaceutical development business, employed Six Sigma to address high mistake rates in its Zydis product line. By applying statistical analysis and automation, training employees to various belt levels, and implementing Six Sigma procedures, Catalent was able to maintain product batches and boost production. This case study illustrates how Six Sigma approaches are beneficial for businesses across all industries as they can improve processes, prevent losses, and aid in cost reduction.

2. TDLR's Record Management: A Six Sigma Success Story

The Texas Department of Licensing and Regulation (TDLR) faced escalating costs due to the storage of records, prompting a Six Sigma initiative led by Alaric Robertson. By implementing Six Sigma methodologies, process mapping, and systematic review, TDLR successfully reduced storage costs and streamlined record management processes. With a team effort and strategic changes, TDLR has achieved significant cost savings and improved efficiency. The project also led to the establishment of a robust records management department within TDLR.

3. Six Sigma Environmental Success: Baxter Manufacturing

Baxter Manufacturing utilized Six Sigma principles to enhance its environmental performance and aim for greater efficiency. Through the implementation of Lean manufacturing and accurate data collection, Baxter reduced waste generation while doubling revenue and maintaining waste levels. With a cross-functional team trained in Six Sigma, the company achieved significant water and cost savings without major investments in technology. It led to promotions for team leaders and showcased the effectiveness of Six Sigma in improving environmental sustainability.

4. Aerospace Manufacturer Boosts Efficiency With Six Sigma

Have you heard about how Six Sigma principles transformed an aerospace parts manufacturer? Here is the 6 Sigma case study   for aerospace parts manufacturer

A small aerospace parts manufacturer used Six Sigma to cut machining cycle time, reducing costs. Key engineers obtained Six Sigma certification and led the project, involving management and operators. Using DMAIC, they analyzed data, identified root causes, and implemented lean solutions. The process yielded a 46% reduction in cycle time and an 80% decrease in variation, enhanced productivity and profitability. The case highlights how Six Sigma principles can benefit businesses of all sizes and emphasizes the importance of training for successful implementation.

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5. Ford Motors: Driving Success

This is a   case study on Six Sigma  i ncorporated by Ford Motors to streamline processes, improve quality, significantly reduce costs, and reduce environmental impact. Initially met with skepticism, Ford's implementation overcame challenges, achieving remarkable results: $2.19 billion in waste reduction, $1 billion in savings, and a five-point increase in customer satisfaction. Ford's Consumer-driven Six Sigma initiative set a benchmark in the automotive industry and proved the efficacy of data-driven problem-solving. Despite obstacles, Ford's Six Sigma exemplifies transformative success in process improvement and customer satisfaction enhancement.

6. 3M's Pollution Prevention Six Sigma Success

Have you checked out how 3M tackled pollution with Six Sigma? It's pretty remarkable. 3M leveraged Six Sigma to pioneer pollution prevention, saving $1 billion and averting 2.6 million pounds of pollutants over 31 years. With 55,000 employees trained and 45,000 Lean Six Sigma projects completed, they focused on waste reduction and energy efficiency. Results included a 61% decrease in volatile air emissions and a 64% reduction in EPA Toxic Release Inventory. Surpassing goals, they doubled Pollution Prevention Pays projects and showcased Six Sigma's prowess in cost-saving measures.

7. Microsoft Sigma Story Lean Six Sigma

By using Lean Six Sigma case studies, Microsoft increased customer interactions and profitability through waste removal and process optimization. They concentrated on improving the quality of the current process and reducing problems by utilizing the DMAIC technique. Eight areas were the focus of waste elimination: motion, inventory, non-value-added procedures, waiting periods, overproduction, defects, and underutilized staff talent. Microsoft streamlined processes and encouraged innovation, which allowed them to maintain productivity and client satisfaction even as technology changed.

8. Xerox's Lean Six Sigma Success Story Six Sigma

It is another important case study of the Six Sigma project. When Xerox implemented Lean Six Sigma in 2003, the organization underwent a significant transformation. They reduced variance and eliminated waste as they painstakingly optimized internal operations. It improved their operational effectiveness and raised the caliber of their goods and services. Through extensive training programs for staff members, Xerox enabled its employees to spearhead projects aimed at improving different departments and functions. The organization saw significant improvements in customer satisfaction and service performance.

9. A Green Belt Project Six Sigma Case Study

It is one of the best examples of a Six Sigma case study. Anne Cesarone's Green Belt project successfully reduced router configuration time by 16 minutes, a remarkable 55% improvement. Anne maintained router inventory, made improvements to documentation and configuration files, and started router requests sooner by resolving last-minute requests and setup mistakes. The initiative resulted in less router programming time from 29 to 13 minutes, an increase in router order lead time of 11 days, and a 60% drop in incorrect configurations. These raised customer happiness and increased operational effectiveness while proving the benefits of process improvement initiatives.

10. Improving Street Maintenance Payments with Lean Six Sigma

Jessica Shirley-Saenz, a Black Belt at the City of San Antonio, used Lean Six Sigma to address delays in street maintenance payments Lean Six Sigma case study examples. Contractors were experiencing extended payment times, risking project delays and city infrastructure integrity. Root causes included payment rejections and delayed invoicing. By implementing quantity tolerance thresholds, centralizing documentation processes, and updating payment workflows, monthly payment requests increased from 97 to 116. Rejected payments decreased from 17 to 12, reducing the rejection percentage from 58% to 42%, saving $6.6 million.

 Six Sigma's effectiveness spans industries, from healthcare to technology. Case studies demonstrate its ability to optimize processes and improve outcomes. From healthcare facilities streamlining patient care to tech companies enhancing software development, Six Sigma offers adaptable solutions for diverse challenges. These real-world examples illustrate how its methodologies drive efficiency, quality, and customer satisfaction. Professionals can learn valuable lessons from using Six Sigma in healthcare studies, identify strategies to overcome obstacles and facilitate continuous improvement. Organizations can emulate best practices and implement similar initiatives to achieve measurable results by studying successful implementations.

Ready to enhance your skills and advance your career with Six Sigma certification? Join our comprehensive KnowledgeHut's best lean Six Sigma courses to master Six Sigma principles and methodologies. Become a sought-after professional in IT, Manufacturing, Healthcare, Finance, and more industries. Enroll now to accelerate your career growth!

Frequently Asked Questions (FAQs)

Six Sigma case studies are available in various formats and places, such as books, academic journals, professional publications, and Internet sites. Many companies that have effectively adopted Six Sigma publish their case studies on their websites or at industry exhibitions and conferences.

Six Sigma case studies provide insightful information on how businesses have addressed certain issues, enhanced procedures, and produced noticeable outcomes. Professionals gain knowledge about best practices, prevalent errors to avoid, and creative problem-solving methods in several industries and circumstances.

Professionals can share their Six Sigma case studies through industry forums, professional networking platforms, blogs, and social media. They can submit their case studies to publications or at conferences and workshops to reach a wider audience within the Six Sigma community.

Shivender Sharma

Shivendra Sharma, an accomplished author of the international bestseller 'Being Yogi,' is a multifaceted professional. With an MBA in HR and a Lean Six Sigma Master Black Belt, he boasts 15 years of experience in business and digital transformation, strategy consulting, and process improvement. As a member of the Technical Committee of the International Association of Six Sigma Certification (IASSC), he has led multi-million dollar savings through organization-wide transformation projects. Shivendra's expertise lies in deploying Lean and Six Sigma tools across global stakeholders in EMEA, North America, and APAC, achieving remarkable business results. 

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Six Sigma Case Study: Everything You Need to Know

Explore the field of Six Sigma Case Studies in our comprehensive blog. From defining the methodology to real-world applications, our 'Six Sigma Case Study: Everything You Need to Know' blog sheds light on this powerful problem-solving tool. Uncover success stories and learn how Six Sigma can drive efficiency and quality improvements in various industries.

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By analysing such case studies, one can gain insights into the successful application of Six Sigma in various industries and understand its impact on process improvement. Read this blog on Six Sigma Case Study to learn how real-world businesses have achieved remarkable process improvement and cost savings. 

Table of Contents  

1) Understanding Six Sigma Methodology 

2) Six Sigma Case Study 

a) Improving customer service 

b) Improving delivery efficiency 

3) Conclusion 

Understanding Six Sigma Methodology

By applying statistical analysis and data-driven decision-making, Six Sigma helps organisations identify the root cause of problems and implement effective solutions. It emphasises the importance of process standardisation, continuous improvement, and customer satisfaction. With its focus on rigorous measurement and analysis, Six Sigma enables organisations to drive efficiency, reduce waste, and deliver exceptional products and services. The methodology follows a step-by-step process called Define, Measure, Analyse, Improve, and Control (DMAIC). These five phases are briefly explained below: 

a) Define: The project goals and customer requirements are clearly defined in this phase.  

b) Measure: In this phase, data is collected to understand the process's current state and identify improvement areas.  

c) Analyse: This phase focuses on analysing data to determine the root cause of defects or variations.  

d) Improve: This phase involves implementing solutions and making necessary changes to eliminate the identified issues.  

Six Sigma Case Study  

In this section we discuss two Six Sigma Case Study that will help you understand and use it better.  

Case Study 1: Improving customer service  

This Six Sigma Case Study will focus on a telecommunications company facing significant customer service challenges. The issues included long wait times, frequent call transfers, unresolved issues, and many more. The company decided to apply Six Sigma methodologies to enhance customer satisfaction.  

a) Define phase: Using the DMAIC approach, the team began by defining the problem: long wait times and inefficient call handling. They set a goal to reduce average wait time and increase first-call resolution rates.  

b) Measure phase: In this phase, data was collected to analyse call volume, wait times, and reasons for call transfers. This helped identify bottlenecks and areas for improvement.  

c) Analyse phase: During this phase, the team discovered that inadequate training and complex call routing were key contributors to the problems. They also found that certain product issues required better resolution protocols.  

d) Improve phase: In this phase, targeted solutions were introduced and implemented to address these issues. The team revamped the training program, ensuring agents were well-trained and equipped to handle customer inquiries. They simplified call routing and introduced automated prompts for quicker issue resolution.  

e) Control phase: Finally, monitoring systems were established in the control phase to track key metrics and ensure sustained improvements. Regular feedback loops were implemented to identify emerging challenges and make necessary adjustments.  

The results were exceptional. Average wait times were reduced by 40%, and first-call resolution rates increased by 25%. Customer satisfaction scores improved significantly, leading to increased loyalty and positive word-of-mouth.  

This Six Sigma Case Study highlights how Six Sigma methodologies can drive transformative improvements in customer service. By focusing on data analysis, process optimisation, and continuous monitoring, organisations can achieve outstanding outcomes and deliver exceptional customer experiences. 

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Case Study 2: Improving delivery efficiency

a) Define phase: The business used the Voice of the Customer (VoC) tool to understand customer needs and expectations. They identified prompt delivery, correct product selection, and a knowledgeable distribution team as crucial customer requirements. 

b) Measure phase: The team collected data to evaluate the problem of slow delivery. They discovered that their Order Fulfillment Cycle Time (OFCT) was 46% longer than competitors, leading to customer dissatisfaction.  

c) Analyse phase: The team brainstormed potential causes of slow delivery, including accuracy of sales plans, buffer stock issues, vendor delivery performance, and manufacturing schedule delays. They conducted a regression analysis, revealing that inadequate buffer stock for high-demand products was the main issue affecting delivery efficiency.  

d) Improve phase: The distributor implemented a monthly demand review to ensure that in-demand products are readily available. They emphasised ordering and providing customers with the specific products they desired.  

e) Control phase: The team developed plans to monitor sales of the top 20% of bestselling products, avoiding over or under-supply situations. They conducted annual reviews to identify any changes in demand and proactively adjust product offerings.  

By applying Six Sigma Principles , the plumbing product distributor significantly improved its delivery efficiency, addressing the root cause of customer dissatisfaction. Prompt action, data-driven decision-making, and ongoing monitoring allowed them to meet customer expectations, enhance its reputation, and maintain a competitive edge in the industry. This case demonstrates the power of Lean Six Sigma in driving operational excellence and customer-centric improvements. 

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Conclusion  

We hope this blog gives you enough insights into the Six Sigma Case Study. This blog showcased the effectiveness of its methodology in driving transformative improvements. By applying DMAIC and using customer insights and data analysis, organisations have successfully resolved delivery inefficiencies, improving customer satisfaction and operational performance. The blog highlights how Six Sigma can be a powerful framework for organisations seeking excellence and exceptional value. 

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Lean Six Sigma Project Examples | 17 Full Case Studies

Ready to begin your first Lean Six Sigma project? Looking for examples for inspiration or reference to get you started? Here are some project storyboards from different industries and from home. Remember, Lean Six Sigma can help you with more than just work!

• Reducing Underwriting Resubmits by Over 20%  

Governments

• A Call to Change: Pioneering Lean Six Sigma at Los Angeles County  
• Can Lean Six Sigma Be Applied in County Government?  
• How the City of San Antonio Increased Payments for Street Maintenance Using Lean Six Sigma  
• Reducing Bid Tab Creation Cycle Time by 22%  
• Reducing Cycle Time for Natural Disaster Response by 50%  

Manufacturing

• Increasing First Run Parts From 60% to 90% With Lean Six Sigma  
• Reducing Bent/Scratched/Damaged (BSD) Scrap for Building Envelopes  
• Reducing Lead Time in Customer Replacement Part Orders by 41%  
• Reducing Learning Curve Ramp for Temp Employees by 2 Weeks  
• Reducing Purchase Order Lead Time by 33% Using Lean Six Sigma  
• Herding Cats Using Lean Six Sigma: How to Plan for and Manage the Chaos of Parallel Processes  
• Lean Six Sigma Increases Daily Meat Production by 25%  
• Lean Six Sigma Helps Feed People In Need 45% Faster  
• Accelerating Lean Productivity With Immersive Collaboration  
• Reducing Incorrect Router Installations by 60% for Call One  
• Reducing Software Bug Fix Lead Time From 25 to 15 Days  

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Real-Life Examples of Six Sigma Implementation – Six Sigma Examples/ Use Cases

Six Sigma is a creative and flexible  series of methodologies aimed at improving organizational process quality and effectiveness. This blog on Six Sigma examples will explain a few use cases of Six Sigma methodology. Business today requires companies to be operational at maximum efficiency and effectiveness. The competitive markets mean everyone is looking to distinguish themselves and offer better products and services. A sustainable way to introduce better business practices is by changing your approach fundamentally. 

Companies are built to achieve corporate goals. The methods to achieve them are plenty and streamlined by management for incorporation. The concepts of optimization, minimizing waste, and maximizing productivity are strongly incorporated into the foundation of Lean and Six Sigma principles. 

These business models are conceptual and can be adapted to any industry or business environment. All you need is a guided professional and a willingness to convert your better business practices into the best possible. In this article, let us explore some Six Sigma examples and success stories.

What is Six Sigma?

The definition of Six Sigma has been under much debate. It can be broadly classified into four concepts:

A Philosophy  – Six Sigma is a school of thought that views workflows and activities as processes that can be expounded, quantified, analyzed, bettered, and monitored. It states an input is required to produce an output. Therefore, exercising control over the input gives you a firm hand in managing output. It is sometimes expressed in the equation  y=f(x)  where  x  stands for the input and  y  for the output. 

A Set of Tools –  Six Sigma comprises controls such as qualitative techniques and quantitative tools used to improve business capabilities internally. Six Sigma tools include SPC (statistical process control), FMEA (failure mode and effects analysis), and control charts. Professionals who deal with Six Sigma explain that tools are continually evolving and are not set in stone. 

A Methodology –  Six Sigma is considered to be a derivative of the DMAIC approach . DMAIC is a data-centric improvement method that operates cyclically. It revolves around Defining, Measuring, Analyzing, Improving, and Controlling. This principle drives Six Sigma users to begin by understanding the existing problem and implementing long term solutions. 

A Metric –  When assessing Six Sigma as a metric, it is defined as 3.4 defects per million opportunities.

Six Sigma, in its simplest form, reduces the possibility of variation in production. The objective is to have a firm grasp on the production process. Lean Six Sigma is a term often associated with Six Sigma. Lean methods are used to minimize wastage during production; this includes time and resources spent on processes that do not directly contribute to better output from activities. Lean Six Sigma is a philosophy that brings together waste minimization and production optimization. It improves customer satisfaction by removing unnecessary processes and waste, creating better workflows, faster output, and possibly a competitive advantage. To attest to the importance of Six Sigma, in the next section of this article, let us explore some Six Sigma examples.

Implementing Six Sigma 

Six Sigma can be implemented in a number of strategies, however there are two baseline options provided to all organizations looking to make the transition;

Introducing Six Sigma Training

Organizations can introduce a fundamental revamp across the organization through a Six Sigma program. Expose employees to better practices and conditioning by introducing the fundamentals and allowing a professional to understand what Six Sigma is and what it helps with. It is important to note that it is mostly an information transfer that happens during Six Sigma training . It is up to the business to adopt the methods to the organization and its practices. 

Introducing Six Sigma Infrastructure 

Creating a Six Sigma infrastructure can be quickly moved along by introducing certified professionals into your organization. Often called “Black Belts”, they move into your business for a period of four weeks to four months and begin teaching your business how to adapt the strategies to your activities. Creating the infrastructure creates a firm guideline to make changes to operations and corporate culture. 

Now let us look into some interesting Six Sigma examples and success stories.

Six Sigma Examples

There are several organizations across various industries that have adopted Six Sigma practices to great success . High profile clients include;

General Electric

The American multinational was struggling to improve overall product quality and service even with the best professionals onboarded. After running a six sigma method trial, the company was able to introduce better-streamlining measures into product assurance. As a result, revenue increased. 

This Indian based technology behemoth was the industry frontrunner for consumer goods. However, their customer service was less than satisfactory. Enter Six Sigma. Over time the methods were used to neutralize threats and create a better experience for clients. 

We all know and love the technology giant that gave us Windows and Office. A contributing factor to the success behind their service and products is Six Sigma. The industry leader has made it no secret that Six Sigma methods have enabled better back-end processes and, as a result, better user experience. It acts as a case in point for companies looking to transition into Six Sigma practices. 

The telecommunications company was one of the first to implement six sigma methods. As a trial, the company implemented Six Sigma to assess the impact on improving product quality and streamlining the transition between services to revenue. The positive results created better company-wide performance and permanent incorporation. 

Boeing   Airlines

One of the world’s largest aerospace companies was having issues with air fans within the engines. Unable to pinpoint the exact problem, a group of experts were called in to investigate. They deduced the problem stemmed from FOD (foreign object damage). Upon more in-depth inspection using Six Sigma methods , they could trace the problem to a more fundamental manufacturing issue causing electrical issues along with the FOD. 

Practically, the application for six sigma methods can be seen across any organization attempting to create better output. Introducing better control measures for various parts of the production process helps produce desirable results. 

Final Thoughts

The beauty of Six Sigma methods lies in their ability to adapt to different environments. The increased efficiency and effectiveness are tangible in the success stories of industry giants implementing Six Sigma to success. Add to the real-life Six Sigma examples of by introducing skilled professionals or the Six Sigma infrastructure to your organization. 

The enterprises usually divide their workforce depending on the hierarchy to get their employees trained in different  Lean Six Sigma training programs  in Yellow Belt, Green Belt, Black Belt, Master Black Belt, and Six Sigma Champion. To get a better understanding of which Lean Six Sigma course benefits the most for you or the team, check out some of the popular courses below to get a comprehensive understanding of the same: 

Lean Six Sigma Yellow Belt Certification Training

Lean Six Sigma Green Belt Certification Training

Lean Six Sigma Black Belt Certification Training

Lean Fundamentals Certification Training

Lean IT Certification Training

RCA Through Six Sigma Certification Training

7QC Tools Certification Training

Value Stream Mapping Certification Training

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Category: Case Studies

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Lean Six Sigma Case Studies

Welcome to the Lean Six Sigma Academy’s Case Studies section! Here, you will find a collection of real-world examples of how companies have successfully implemented the Lean Six Sigma methodology to improve their business operations. Each case study includes an overview of the business challenge that was faced, the approach that was taken, the results that were achieved and feedback from the client on their experience. These case studies showcase the wide range of industries and organizations that have benefited from Lean Six Sigma, and serve as inspiration and guidance for those looking to implement the methodology in their own business. 

OE Partners

Orrcon Steel

The toyota production system.

Lean Six Sigma for the improvement of company processes: the Schnell S.p.A. case study

The TQM Journal

ISSN : 1754-2731

Article publication date: 15 October 2021

Issue publication date: 17 December 2021

The aim of this study is to develop an in-depth case study on the implementation on Lean six sigma (LSS) in Schnell S.p.A., Italian company leader of an important multinational industrial group, highlighting the benefits that can be achieved from a careful application of this method, the main challenges and organizational learning from its implementation.

Design/methodology/approach

The study has been developed with a qualitative approach, creating a single in-depth case study, with the participant observation of researchers in the project which lasted 4 months. Periodic weekly meetings were done with the working group to exchange feedback on the development of the project to share opinions and data.

A project has been developed to stabilize the procurement process of a pull-type production cell, which experienced delays in supply lead times. The causes of the problems in their process of managing the supply of the production cell were found and some inefficiencies in the internal process of fulfillment of supply orders have been intercepted, the optimization of which has allowed the generation of an automatic system for sending supply orders, coming directly from the production line.

Originality/value

This study described the path and dynamics of the transformation process that business organizations undertake for optimizing their profitability and competitive advantage, placing emphasis on an innovative methodology for conducting business process improvement projects, which constitutes its operating philosophy on the effective and efficient use of company resources and skills, to guarantee to the company the achievement of a lasting and defensible competitive advantage over time.

• Lean thinking
• Lean production
• Quality management
• Continuous improvement

Murmura, F. , Bravi, L. , Musso, F. and Mosciszko, A. (2021), "Lean Six Sigma for the improvement of company processes: the Schnell S.p.A. case study", The TQM Journal , Vol. 33 No. 7, pp. 351-376. https://doi.org/10.1108/TQM-06-2021-0196

Emerald Publishing Limited

Copyright © 2021, Federica Murmura, Laura Bravi, Fabio Musso and Aleksandra Mosciszko

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

The development of an effective quality improvement or continuous improvement strategy is a key factor for long-term success of modern organizations. Over the last decade, Lean Six Sigma (LSS) has become one of the most popular and proven business process improvement methodologies organizations have ever witnessed in the past ( Antony et al. , 2017 ), and it has been accepted globally as a management strategy for achieving Process Excellence ( Gijo et al. , 2019 ).

Lean Six Sigma is a management strategy for improving corporate productivity and profitability, that aim to maximize the Customer satisfaction by reducing constraints which the company organization is subject in terms of activities that do not create value for the Customer. In practice, LSS is an improvement strategy that analyze quantitative data on business performance to identify, eliminate and control problems and inefficiencies related to manufacturing cost, service cost, quality, productivity and customer satisfaction ( Singh and Rathi, 2019 ; Snee, 2010 ) throughout the business processes.

The objectives of quality and efficiency, supported by Lean Six Sigma, are made by DMAIC: a structured method for improving the performance of existing processes ( Sordan et al. , 2020 ), based on the application of the concepts Define, Measure, Analyze, Improve and Control. It provides a standardized guideline for the elaboration of improvement projects and provides different statistical tools and techniques appropriate to each phase of the DMAIC cycle ( Sordan et al. , 2020 ) able to lead to the root causes of business problems and to eliminate the wastes and reduce the variation, thus, ensuring substantial improvement in business processes ( Bhat et al. , 2020 ).

The term LSS was first introduced into literature around 2000 LSS, while LSS teaching was established in 2003 as part of the evolution of Six Sigma ( Timans et al. , 2012 ). Since that time, there has been a noticeable increase in LSS popularity and deployment in the industrial world ( Shah et al. , 2008 ) and researchers had the interest to publish more papers on LSS to try to come up with a comprehensive approach to achieve continuous improvement. However, as suggested by Albliwi et al. (2015) , there are still many gaps that need to be addressed in LSS literature such as benefits, motivation factors, challenges and limitations ( Pepper and Spedding, 2010 ; Laureani and Antony, 2012 ), and there is also a lack of research in the relation between LSS and organizational learning and in recent years a lot of systematic literature reviews on the topic have been published on the topic but only few case studies have been analyzed in the research field to cover this gap.

Therefore, the aim of this study is to cover this gap, by developing an in-depth case study on the implementation on LSS in an Italian company leader of an important multinational industrial group, that is Schnell S.p.A., that constitutes its main research and production center and provides technological, organizational and commercial support for the entire group. Schnell operates in over 150 countries around the world through its 11 subsidiaries, over 50 agents and resellers, and a dense network of service centers.

This research work has the objective of highlighting the benefits that can be achieved from a careful application of LSS method in the company, the main challenges and also organizational learning from LSS implementation, showing its application in details in an important reality like that of Schnell S.p.A.

The paper is structured as follows: Section 2 depicts the theoretical background, describing the merging of Lean Production and Six Sigma and defining the critical success factors of lean six sigma implementation; Section 3 defines the methodology used, Section 4 presents and discusses the results of the case study while the last section draws the main conclusions.

2. Literature review

2.1 the merging of two quality philosophies: lean production and six sigma.

The LSS notion was announced to the world in 2002, when Michael George used it for the first time in the book “Lean Six Sigma: Combining Six Sigma with Lean Speed” ( Sordan et al. , 2020 ; Sreedharan and Raju, 2016 ). He is the founder and Chief Executive Officer of the George Group, one of the largest LSS project consulting firms in the United States.

Although its appearance is quite recent, LSS arise from two complementary but different approaches ( Sordan et al. , 2020 ): Toyota Production System (TPS), a famous organizational orientation developed in Japan, from the 1960s and 1980s, spread with the concept of “Lean Thinking”; and Six Sigma, a technical quality management program, introduced by Motorola Corporation in manufacturing arena in 1987 ( Singh and Rathi, 2019 ).

The synergy between Lean and Six Sigma created a data-driven ( Sreedharan and Raju, 2016 ) and top-down business strategy to improve the quality and productivity of organizations ( Singh and Rathi, 2019 ; Sordan et al. , 2020 ).

When we talk about Lean Thinking, we are talking about a business culture, based on respect, trust and cooperation between employees and oriented by a constant search for perfection that allows to reach the highest quality of products and services offered by the company and consequently to maximize customer satisfaction.

To achieve this goal of perfection and to optimize profits, corporate actions must be aimed at a constant effort to reduce costs and wastes of tangible and intangible resources, by distinguishing valued-added activities from non-value-added activities and eliminating wastes that increases cost without adding value in the eyes of the customer ( Antony et al. , 2017 ; Cudney et al. , 2014 ): activities that are unnecessary and not required for the operations of the business ( Jayaram, 2016 ).

Lean Thinking emphasizes on productivity improvement along with speed to respond to customer needs and create a streamlined, high-quality system that produces finished products at the pace of customer demand with little or no waste ( Lande et al. , 2016 ).

Wastes are called Muda, and they can be defined as real sins that hinder the ideals of perfection. The eight types of waste are defined as transport, inventory, motion, waiting, overproduction, overprocessing, defects and non-utilized skills ( Gijo et al. , 2019 ). To identify and eliminate Muda, Lean strategy brings a set of proven tools and techniques that allow to reduce lead times, inventories, set up times, equipment downtime, scrap, rework and other wastes of the hidden factory ( Lande et al. , 2016 ). Corbett (2011) affirms that while lean focuses on the elimination of waste and improving flow, it has some secondary effects: quality is improved; the product spends less time in the process, thereby reducing the chances of damage and obsolescence.

But we have to remember that the commitment to Lean Thinking must start at the top management level and should be cascaded down to various levels across the organization to improve flow and efficiency of processes ( Antony et al. , 2017 ).

Six Sigma (SS) is a business process improvement and problem-solving approach ( Lande et al. , 2016 ) that seeks to find and eliminate causes of variability, as well as defects or mistakes in business processes, by focusing on process outputs which are critical in the eyes of customers ( Antony et al. , 2017 ). The main objective of Six Sigma is to obtain “zero defect” or, in statistical terms, to reduce defects up to 3.4 parts per million opportunities ( Singh et al. , 2019 ).

To study variability, Six Sigma utilizes a problem-solving methodology to define, measure, analyze, improve and control processes and implement cost-effective solutions leading to significant financial savings ( Singh et al. , 2019 ) not only for manufacture sectors but also remove the defects throughout the corporations ( Singh and Rathi, 2019 ). This methodology is called DMAIC and it emphasizes on variation reduction, defect reduction and process evaluation (the effectiveness issue).

The complementarity between both approaches can be justified when the deficiencies inherent in each of them are observed, acting in isolation ( Sordan et al. , 2020 ). Both had produced tremendous results but had limitations: Lean is not well suited to resolving complex problems that require intensive data analysis, and advanced statistical methods, and, Six Sigma implementation showed how not every problem can be resolved with only a big data collection ( Antony et al. , 2017 ).

Lean does not address variation within a process; rather it addresses variation between end-to-end processes which appears in the form of waste. One of the major limitations of Lean is that it cannot be used to tackle problems related to process stability and capability ( Gijo et al. , 2019 ) and it tends to work best with “solution known” problems, where we realize that we are not operating to best practices, Lean implements them and make rapid improvements with minimal data collection ( Hoerl and Gardner, 2010 ). Six Sigma is most effective when used for improvement projects intended to drive processes towards process entitlement, in situations where the solution to the problem is unknown ( Snee and Hoerl, 2007 ).

As stated by Pepper and Spedding (2010) if lean is implemented without Six Sigma, there is a lack of tools to fully exploit the improvement of its potential. Conversely, if Six Sigma is adopted without lean thinking, there would be a cache of tools for the improvement team to use, but no strategy or framework to bring one's application to a system.

Combining Lean manufacturing principles and Six Sigma tools and techniques enables organizations to form a powerful improvement combination ( Hoerl and Gardner, 2010 ; Lande et al. , 2016 ) that has allowed many organizations to solve more problems quicker ( Antony et al. , 2017 ). It is a successful integration because Lean focuses on improving the flow of information and materials between the steps in the process and Six Sigma works to improve the value-adding transformations which occur with in the process steps ( Antony et al. , 2017 ).

LSS defines an approach, but of course does not dictate the specific progression of the project or dictate the unique mix of tools to be used, which of course needs to be problem specific ( Hoerl and Gardner, 2010 ). The appropriate blend of Lean and Six Sigma tools useful on any one problem therefore depends on the nature of the specific problem being solved ( Antony et al. , 2017 ).

The marriage between these two methodologies provides a more integrated, coherent and holistic approach to continuous improvement ( Pepper and Spedding, 2010 ) and has led to the creation of a breakthrough managerial concept ( Sordan et al. , 2020 ; Chiarini, 2012 ) with the aim to create a new business culture that breaks the link with the traditional way of working in all productive functions. LSS adds a new task to daily working duties: the recovery of operational efficiency through training growth of people, extensive use of data culture and problem-solving methodologies; all activities that simultaneously allow the improvement of quality, the costs and business complexities reduction, the increasing revenue ( Galdino de Freitas and Gomes Costa, 2017 ; Jayaram, 2016 ) and, finally, greater reliability of the services provided to the end customer. The application of LSS methodology results in reduced waste, defects and improve process, which in turn provide high-quality products at minimum cost, and this leads to customer delight, which ultimately raises the societal living standard ( Singh et al. , 2019 ; Jayaram, 2016 ), the well-being of employees and the quality of the work environment (Galdino de Freitas and Gomes Costa, 2017 ).

LSS aims not only to improve financial results through the improvement of company production processes, but it targets to help organizations build an adequate relationship with society, employees and the environment ( Galdino de Freitas and Gomes Costa, 2017 ).

Both Lean and SS require a company to focus on its products and customers and LSS as a part of management strategy to increase the market share and maximize profit ( Lande et al. , 2016 ). It produces benefits in terms of better operational efficiency, cost-effectiveness and higher process quality, because it promotes total employee participation from both top-down and bottom-up as a win-win practice to both management and staff members ( Gijo et al. , 2019 ).

2.2 Critical success factors of lean six sigma implementation

Lean Six Sigma strategy is versatile in nature and has a lot of applications in a variety of industries.

It can be applied in manufacturing as well as non-manufacturing environment ( Singh and Rathi, 2019 ). It has broad applicability in service, healthcare, government, non-profits, education ( Antony et al. , 2017 ) automotive, textile, steel and aerospace industries ( Sordan et al. , 2020 ). Although LSS has its roots in manufacturing, it is proven to be a well-established process excellence methodology in almost every sector despite its size and nature ( Gijo et al. , 2019 ). It is useful in small-and medium-size organizations as well as large organizations ( Antony et al. , 2017 ).

LSS is also suitable for less experienced organizations: Bhat et al. (2020) write about the successful deployment of LSS strategy in an Indian industry with orthodox industrial practices, limited manpower, constrained capital and confined knowledge on scientific improvement practices, and the research proves that even a novice user can effectively participate and implement LSS with proper mentoring to enhance the system.

Regardless of the sector in which the LSS is applied, this shows the spread of LSS in various organizations as one of the best strategies for organizational excellence ( Sreedharan and Raju, 2016 ). But it is important to remember that achieving maximum strategic and management efficiency cannot be based on the replication of principles and models of Lean approach.

Each organization is immersed in different social, cultural and economic conditions. For this reason, lean tools must be sized and customized on business contexts and simultaneously the entire business organization must be adapted to the changes that Lean Six Sigma generates and that it needs to be applied effectively ( Lande et al. , 2016 ; Raval et al. , 2018 ; Singh et al. , 2019 ; Gijo et al. , 2019 ).

These requirements for cultural change are the main critical success factors for LSS ( Sreedharan and Raju, 2016 ).

Critical success factors are the actions and processes that must be controlled by the management ( Lande et al. , 2016 ) during the implementation of a LSS project.

Top management involvement and commitment ( Lande et al. , 2016 ; Gijo et al. , 2019 ). The top management involvement and commitment are essential for successful implementation ( Pepper and Spedding, 2010 ) of any LSS initiative. It must personally support all improvement initiatives and integrate the LSS culture into entire organizations. Its active participation can multiply the positive project effects and make a significant impact at all levels ( Gijo et al. , 2019 ). If the top management will not take initiatives and not show their full involvement it could cause the failure of LSS implementation ( Singh et al. , 2019 ).

Employee involvement, empowerment and training ( Lande et al. , 2016 ; Gijo et al. , 2019 ; Bhat et al. , 2020 ). The cultural growth of internal staff is the heart of LSS programs because it offers necessary tools to create a clear vision of the project, to focus on teamwork and, above all, to fight the resistance to cultural and operational changes ( Singh et al. , 2019 ; Sunder and Antony, 2018 ). Employee training also contributes to gain a high level of internal communication which facilitates the implementation of LSS ( Lande et al. , 2016 ; Singh et al. , 2019 ; Gijo et al. , 2019 ; Bhat et al. , 2020 ). Training is necessary to create a supporting infrastructure (the belt system) and a holistic approach to improvement including area of application and methodology used ( Antony et al. , 2017 ). The belt system includes Master Black Belt, Black Belt, Green Belt, Yellow Belt and depending on the complexity of the problem considered and skills required to solve it, the appropriate Belts are selected ( Gijo et al. , 2019 ) to play the role of leadership and guidance of the project team.

Linking LSS to business strategy and customer satisfaction ( Lande et al. , 2016 ). Improvement projects must be closely linked with maximizing customer satisfaction. Top management defines business objectives and identifies improvement projects capable of guaranteeing greater remuneration in terms of optimizing company productivity and profitability, as well as projects that can be reached using available resources, which do not require high investments and which allow to obtain undisputed results with limited deadlines in a limited period of time. Improper linkage between organizational objective and customer's requirement leads to failure of LSS implementation ( Singh et al. , 2019 ; Singh et al. , 2019 ; Gijo et al. , 2019 ).

3. Methodology

The study is a conceptual development and it has been developed with a qualitative approach, creating a single in-depth case study of Schnell S.p.A. that derives from a Group Purchasing Excellence Project. The case study allowed for examining in depth the implementation of a Lean Six Sigma improvement project for the transformation and simplification of the production process of the Schnell “Alfa” and “Beta” machines with the aim to reduce the delivery times of its products ( Yin, 1994 ). The case study was developed with the participant observation of researchers in the project which lasted 4 months, starting from November 4, 2019 to March 4, 2020. As for the participant observation, the researcher was directly involved in the LSS implementation activities, collaborating with the working group in the figure of the project manager, and facing directly obstacles and problems that emerged during these stages of the same (par. 4.2.1.1 will define the detailed description of the project). Periodic weekly meetings were done with the entire working group to exchange feedback on the development of the project, to share opinions and data. Participant observation activity was triangulated with secondary data, such as company reports and the website, collected during the period of support in the company. Secondary data have been used mostly to describe Schnell history, structure and the services it offers to customers.

Minitab 19 statistical analysis software was used to describe and summarize the data collected during the project and shown in the result section.

4. Results and discussion

4.1 company profile: schnell s.p.a.

Schnell S.p.A. is an Italian company that has been operating for almost 60 years in the manufacturing sector of automatic machines and plants for processing iron for reinforced concrete. It was born in 1962 thanks to the devotion of a group of entrepreneurs, driven by the dream of transforming the tiring and dirty world of iron working, into a modern industry, dedicated to conquering the global market. The company embarks on its own path by offering a first innovative solution that allowed faster binding of the reinforcing bars, flanked by the production of construction site machinery for cutting and bending the bars. The rise in the automatic machinery sector has started with the development of mechanisms for the production of cylindrical cages; however, the real change of course compared to its competitors will take place with the addition of electric servomotors, used, before now, only in fields such as robotics and military industry. Thanks to this type of instrumentation, Schnell machines are characterized by high power, speed, reliability and precision. They guarantee to the customer the achievement of economies of scale and better production techniques due to the high productivity offered, reduced set up times and low maintenance costs. Schnell S.p.A. offers the market a high range of machines and systems that allow a variety of processing of iron for reinforced concrete, including straightening, stirrup bending and shaping machines for bending, shaping and cutting iron in rolls or bars; cage making machines for the formation of cylindrical poles and cages for construction; machines and plants for the production of electrowelded mesh; machines for wire straightening and cold rolling lines; rotor straightening machines for processing steel wires for the industrial sector; machines for the production of prefabricated insulating panels for building construction; software for the management of iron processing centers using Schnell automatic machines. As a result of the high quality of these products, Schnell S.p.A. has managed to win the trust of its customers all over the world, reaching a turnover of over 100 million euros.

The Schnell Group is characterized by a staff of over 700 employees worldwide, and is made up of 5 production plants; 7 centers for installation, sales, spare parts and after-sales services; Schnell Software (Spain), which is a center for the creation and development of software systems for the management and organization of production carried out using Schnell machines and Schnell Home S.r.l., production center of machines for the construction of innovative elements for building construction, called “Concrewall”. Achieving a highly competitive advantage over its competitors in the same sector was possible due to constant investments in research, development and technological innovation of products and processes. Product innovation, since the company is always ready to respond to market needs through the development of a customer-oriented approach, which allows to offer integrated and customized production solutions. Process innovation, since, as stated in the “Integrated Quality Policy” and “Purchasing Excellence Group Program” of Schnell S.p.A., the efforts of the whole company are oriented to create effective methods of managing internal operational processes, with a view to maximizing end customer satisfaction.

As a result of the constant commitment in this direction, at the end of 2007, Schnell S.p.A. managed to obtain the quality system certification according to the ISO 9001 standard, delivered by the prestigious certification body TUV Italy, and renewed in 2019 in compliance with the updates undergone by the standard in September 2015.

The important results obtained in terms of product and process quality was also possible due to the dissemination and application of Lean Manufacturing principles and methodologies.

4.2 The development of the lean six sigma project in Schnell S.p.A

The layout of the cell, the equipment and the production tools have been designed and arranged horizontally following the phases of the process;

The production plans were planned on order, therefore, on the basis of the orders received from its customers, following the production theories with the pull logic;

The manufacturing of the machines was organized in small batches conducted with the one-piece flow system;

The management of the entire procurement process of raw materials and production components has been entrusted to the Kanban system;

The line operators have been trained to complete all manufacturing operations in complete autonomy.

The products supplied with their own identification codes;

Periodicity of reordering;

Minimum order quantity;

Delivery Lead Time (in working days);

Safety Stock Level: quantity of products to be held in the warehouse as a mandatory stock;

Technical specifications of production;

Specifications for packaging and delivery.

For further stabilization of the production process, aimed at increasing product quality, the characterizing element of the In-Lining Line was to reach a Free-Pass quality level. This qualitative incoming methodology has allowed a high reduction in the variability of the external production process, of the components characterized therein, while requiring significant direct and indirect investments by sourcing.

The entire In-Lining apparatus is governed by a vital element for the correct planning of the production phases: the supply Lead Time.

This index represents the time elapsing from the time of issue of the purchase order to the time of actual receipt of the goods. It allows to efficiently plan the supply of production components, and therefore, to define the periods for sending purchase orders.

Lead time of supply;

On-time Delivery (the ratio between the number of orders processed on time and the number of total orders processed, in the period considered).

With a view to Project Management, a work team was set up with the task of studying and analyzing the procurement process of the In-Lining line, and the phases of the Plan-Do-Check-Act (PDCA) and DMAIC approach were followed for the implementation of the project.

4.2.1 “Define” phase

The objective of the first phase of the project was to identify all the aspects necessary to define the process to be improved, therefore, to develop a planning prospectus called Project Charter containing: the representation of the problem detected, the objectives to be achieved, the requirements required from the customer, the inputs and outputs of the process and the metrics necessary to measure it, the enhancement of the current process and possible savings achievable by improving the process, the team members, and finally, the deadlines of the project phases.

4.2.1.1 Project description

Analyzing the lead times of supply of the supplying process of the In-Lining Line, conducted with the Kanban system, it was reported that the most important supplier in terms of quantity, tends not to respect the agreed delivery terms.

Upper specification limit (USL) = LEAD TIME 5 days (working);

Lower specification limit (LSL) = LEAD TIME 2 days (working).

Analyze the deliveries to the line of the last available calendar period, from 01/11/2018 to 31/10/2019;

Perform stratification of the detected deliveries, until the root causes are reached;

Define the initiatives and control charts to ensure the stability of the procurement process over time.

Lead Time of supply;

Defects per Unit – DPU;

Defects Per Million of Opportunity – DPMO;

Sigma Level.

The project team was made up of the members defined in Table 1 .

The implementation of the DMAIC phases was organized through the Gantt Chart ( Figure 1 ), with the aim of a precise subdivision over time of the individual activities to be carried out, while all the information that defines the project was collected in the Project Charter document of Figure 2 .

4.2.1.2 Project risk analysis

During the planning of the project, different potential risks were identified that could affect the smooth running of the project. These were found in relation to different sources from which they could derive (see Table 2 ).

Severity (P): expresses the potential damage that the occurrence of the risk could cause in the implementation of the project;

Occurrence (G): expresses the probability that the risk may occur;

Detection (R): expresses the probability of risk detection once it has occurred.

Each variable was assigned a score from 1 to 5, in which 1 represents an insignificant risk condition and 5 that of extreme risk (only for the Detection variable, the lower the score assigned, the greater the probability of risk detection).

The most critical risks have been identified through the Risk Priority Index – Risk Priority Number (RPN) obtained from formula f.1. f .1 ) RPN = S × O × D

The highest priority was checked for the risks “Inability to use software” and “Insufficient knowledge and skills of members” (see Table 3 ).

4.2.1.3 Process representation

To obtain a macro view of the process, the Supplier Input Process Output Customer (SIPOC) diagram has been developed ( Figure 3 ) which highlights the main elements that make up the activities examined.

4.2.2 “Measure” phase

The second phase was aimed at defining and measuring the progress of the process at the current stage. For a better representation, the flow of activities necessary to replenish the In-Lining line has been outlined through the Flow Chart ( Figure 4 ) which identifies on the left side the operations that add value within the process (AV), while, on the right side, those with non-added value (NAV), therefore considered as waste.

The process was further represented through the Value Stream Mapping technique ( Figure 5 ) which allowed to estimate a total Process Time (P/T) of 11.6202 h (11 h 37 min and 12 s), divided into 11.40417h (11 h 24 min and 15 s) for value-added activities and 2.216 h (12 min and 57 s) for non-value-added activities. Together with downtime and shipping times, the entire process is performed with a maximum total Lead Time (L/T) of 8 days, 8 h, 5 min and 28 s.

4.2.2.1 Data collection

PRODUCT A.1;

PRODUCT A.2;

PRODUCT B.1;

PRODUCT B.2;

PRODUCT C.1;

PRODUCT C.2;

These products are characterized by belonging to similar categories, therefore, with the aim of greater interpretation and a better comparison of data, the population has been grouped into stratified categories with reference to the product group to which they belong, type of production component and final product.

4.2.2.2 Interpretation of data with statistical tools

In the first phase, the graphical summary analysis was performed ( Figure 6 ) showing the results of the Anderson-Darling Normality Test, the descriptive statistics and the confidence intervals for the mean, median and standard deviation of the data population in exam. The graphs show that deliveries are characterized by an average delivery lead time of 9.4324 working days which falls within a range of 70 working days. The recorded variation therefore determines a standard deviation of 14.4877.

Second, from the Anderson-Darling normality test, a p -value <0.005 is obtained: this value demonstrates that the analyzed data derive from a distribution that cannot be approximated to a Gaussian model.

The current result is a consequence of the fact that in the population, in correspondence with the value in the 3rd Quartile of 7 days and Maximum of 74 working days, irregular values can be highlighted, called outliers, which arise from particular causes of a special type, and which therefore prevent a regular data analysis and interpretation, negatively affecting all study results.

It was highlighted that these were four deliveries relating to the same order, made on August 31, 2018, of two components of CATEGORY C, in particular of PRODUCT C.2.

Through a more in-depth investigation, it was possible to observe that the supply agreement was drawn up and confirmed prior to the first delivery of the product in the sample phase. Consequently, the high delivery lead time was justified by the fact that the supplier had to provide totally new products, the production of which had to be studied and adapted to their production processes.

Given the particular situation, to carry out a more meaningful analysis, it was decided not to consider the indicated outliers values, and to run the graphical summary analysis again, this time on a population made up of N  = 70 units ( Figure 7 ).

In this case, the standard deviation assumes the value 4.1852, the average delivery Lead Time tends to reduce to the value of 6.1429 working days; however, again it is possible to deduce a p -value < 0.005; therefore, the data derives from a distribution that cannot be approximated to a Gaussian model. It is possible to conclude that the entire process is not under statistical control: the distribution consists of values that cannot be approximated to a Gaussian model, characterized by a supply trend that cannot be predicted over time.

On the basis of these results, it was possible to state that the supplier encountered numerous difficulties in fulfilling supply orders from the In-Lining Line, since the delivery process of the components was characterized by Lead Times that deviate significantly compared to the average lead time recorded (see Figure 8 ).

To express the supplier's performance in terms of Process Sigma, the values of Table 4 were taken into consideration, which summarizes the variables necessary for the calculation of the Defects Per Units (DPU), the Defects Per Opportunity (DPO) and the Defects per Million of opportunity (DPMO) index: (1) DPU = Numerosità   difetti   rilevata ( D ) Numerosità   campione ( U ) (2) DPO = DPU Opportunità   di   errore ( O ) (3) DPMO = DPO × 1.000.000

The supply of the In-Lining line is characterized by a Sigma Level equal to 1.85, therefore, the current process is carried out with a yield of 63.51%.

4.2.3 “Analyze” phase

Based on the considerations obtained from the measurements made in the Measure phase, in this third stage of the project the team's goal was to intercept the categories of components that found the greatest difficulties in the procurement process.

Considering the high variability of the delivery process, in order to identify priority areas of intervention, the analysis was further processed through the Pareto diagram and, for easier interpretation, it was carried out by stratifying the data on the basis of the single category of belonging (see Figures 9 and 10 ).

It was observed that 39% of deliveries ( Table 5 ), carried out in the period under consideration, were carried out outside the established lead time specifications of 5 working days. The supplier presents the greatest number of critical issues with the fulfillment of orders relating to the GROUP A category, in particular with the fulfillment of PRODUCT A.1 and PRODUCT A.2, and to a lesser extent, with PRODUCT B.1 and PRODUCT B.2.

For the GROUP B category, difficulties were found in the delivery of the PRODUCT C.2 and PRODUCT D components; however, for the latter, the non-conformities found cannot be analyzed, as they are insignificant.

4.2.4 “Improve” phase

In the Improve phase, the purpose of the study activity was to identify the root causes of the problems that the Business Partner identified in the process of fulfilling the supply orders of the In-Lining line, and secondly to identify the paths for improvement to correct the criticalities detected.

4.2.4.1 Root cause analysis

The study was developed by analyzing the temporal trend of orders in the period considered for each PRODUCT category indicated at the end of the Analyze phase. For deliveries with greater difficulty, inquiries were carried out on the dates of issue and actual delivery of supply orders. In this phase, the help offered by the Production Planner of the Production Department who deals with the management of the production planning of the In-Lining cell was of great support. First of all, it was possible to deepen that in the delivery process of PRODUCT A.1 and PRODUCT C.2, in relation to the deliveries of the orders of the week 3/2019 and 2/2019, issued respectively with Lead Time of 23 and 22 working days, the supplier communicated the breakdown of a machinery necessary for the production of the components; therefore, it was not able to respect the contractual specifications. The Lead Time values detected here can be considered as outliers, determined by causes of a special type.

By analyzing PRODUCT A.2, it was possible to ascertain that some phases of the production process of the supplier in question were carried out in outsourcing to external suppliers not regulated by subcontracting contracts and, therefore, without evaluations in terms of lead time. As a result of this type of production management, instabilities in the internal delivery process have been generated.

For some deliveries, the supply lead time has been calculated incorrectly.

The supplier tends not to comply with lead time specifications, especially after prolonged company closure periods and in correspondence with orders processed in short periods.

To identify the root cause of the difficulties highlighted, the Five Why (5Why) method was used, which allowed to identify the cause-and-effect relationships of the problems to be analyzed ( Table 6 ). With the help of this problem finding tool, it was possible to ascertain that for some deliveries examined, the delivery lead time was calculated incorrectly as for orders corresponding to the deliveries themselves, the generation date did not correspond to the date of sending the order to the supplier. The system for sending supply orders for the In-Lining line provides that the verification and approval phase, carried out after the automatic proposal generation phase, takes place manually through the action of the Back Office – Purchase Department operator. In situations of absence of the operator, or late approval of the order, the supplier receives the document on a different date from that of issue.

With reference to the second problem identified, it was analyzed that the Business Partner highlights critical issues in terms of supply lead time, in relation to the fulfillment of orders received following prolonged company closure periods and for those received in short periods.

In the first case, these are deliveries made in the time interval corresponding to the periods of early January, late April and early September: time intervals that follow the periods of company holidays for national holidays.

It was assumed that prior to these company holiday periods, the warehouse safety stock was entirely consumed and not restored with further production of components. Therefore, it was considered that the supplier finds it difficult to ensure the restart of the post–holiday production activity through the forecast of its monthly requirements; therefore, it is unable to prevent the stock breaking of its warehouse.

For the second case, however, the supplier presented difficulties in fulfilling the orders placed in correspondence of short periods. More precisely, an out of specification Lead Time was highlighted in correspondence with the second/third order received in a monthly time interval. Also, for this criticality it has been hypothesized that there may be difficulties in ensuring an efficient planning of production activities and a correct forecast of one's monthly requirements, without incurring stock-outs in one's warehouse.

Activate an automatic system for generating, approving and sending orders to the supplier;

Arrange a meeting with the business partner in order to discuss the critical issues detected in the period studied.

With the aim of preventing further errors in the measurement system of the supply lead time indicator, and therefore overcoming the time gaps recorded between the generation phase and the order sending phase, the information technology (IT) department was entrusted with the task to generate an IT system that can automatically complete the entire process of fulfilling the supply orders coming from the In-Lining line. Considering the utmost importance of this improvement activity, the automatism created was implemented in the process starting from the first week of February 2020.

Check the efficiency of internal production planning;

Verify whether the process of managing the economic lot and purchasing the components creates an imbalance in the company loan;

Check if all the clauses contained in the stipulated subcontracting contract have been effectively understood;

Check if in the production planning phase, the periodicity of reordering of components is taken into consideration.

Lastly, having ascertained the delivery problems encountered when supplying the PRODUCT A.2 component, the Management of the production process of the In-Lining line carried out a strategic Make or Buy analysis. As a result of the evaluation carried out, on 14/11/2019, the subcontracting contract was canceled and the procurement of the components was entrusted to an alternative Business Partner.

4.2.5 “Control” phase

In the last phase of the DMAIC project, some activities were identified and implemented in order to keep under control the improvement activities introduced in the Improve phase.

To verify the operation and validity of the automated system for generating, approving and sending the supply orders of the In-Lining line, the IT department has launched a checkup mechanism with the aim of transmitting to the Purchase Department a daily report on the effective sending of orders created automatically.

Considering, however, the need to investigate the possible difficulties encountered, the meeting with the Business Partner was scheduled for the second week of March.

4.3 Benefits deriving from the implementation of the project

After an accurate analysis of the problem related to the reduction of lead time and its causes, it has emerged that the main concern is that in most cases the supply lead time has been calculated incorrectly, while in others supplier tends not to comply with lead time specifications, mostly after company closure periods and when orders are processed in short periods.

First, the implementation of the project has made the company become fully aware of the inefficiencies present in the delivery process of some of its components, allowing a high reduction in the variability of the external production process of these components. Reducing delivery times has also allowed to better plan the supply of production components, defining the periods for sending purchase orders. An automatic system for managing supplier orders has been activated, and it has permitted to reduce errors during the order creation and management process, having a positive effect on the consolidation of the process under consideration. Moreover, a meeting with suppliers was carried out and it has permitted to discuss and confirm together with the business partners the clauses contained in the subcontracting contract, to better plan the periodicity of reordering of components, but also internally improve the efficiency of production planning. From a quantitative point of view, the benefits will be assessed over the long term, with a careful analysis.

5. Conclusion, implications and future research directions

This study was carried out with the main objective of describing the path and dynamics of the transformation process that business organizations undertake with the aim of optimizing their profitability and competitive advantage following the profound environmental changes to which they are subject to, placing emphasis on an innovative methodology for conducting business process improvement projects, known as Lean Six Sigma, which constitutes its operating philosophy on the effective and efficient use of company resources and skills, to guarantee to the company the achievement of a lasting and defensible competitive advantage over time. Lean Six Sigma has been presented in this research as a methodology for improving business productivity, which operates through the reduction of the constraints and inefficiencies of each production and transactional process, aspiring to the maximum satisfaction of the internal and external customer and is configured as a real strategy, which offers to the human resources an innovative way of thinking and working based on training growth, data culture and the use of problem-solving methodologies that allow the improvement of quality, the reduction of costs and company complexities. In this detailed case study, the DMAIC technique was applied in a project to stabilize the procurement process of a pull-type production cell, which experienced some problems in terms of delays in supply lead times.

Thanks to the analyses carried out and the results obtained with the processing of the DMAIC phases, it was possible to highlight the potential causes of the problems that the business partner could have presented in their process of managing the supply of the production cell. Furthermore, some inefficiencies in the internal process of fulfillment of supply orders have been intercepted, the optimization of which has allowed the generation of an automatic system for sending supply orders, coming directly from the production line; a small tweak that will undoubtedly have a positive effect on the consolidation of the process under consideration, as the purchase department will be able to both keep order fulfillment under control and develop a more efficient measurement of business partner performance indicators.

With the development of the project, it was possible to structure the initial guidelines for the subsequent in-depth analysis of the critical issues identified. In particular, for the stabilization of the entire process, Schnell S.p.A. will have to develop an intense relationship of collaboration and mutual growth with his supplier to identify and implement the best solutions to the variability of the supply order fulfillment process.

The practical implementation of the Lean Six Sigma project confirmed the validity and power of the principles professed by this improvement methodology: the importance of customer orientation and the elimination of waste of resources; the value of a work team and the continuous search for qualitative and quantitative data that support and facilitate the decisions of each member of the group.

It was particularly fruitful to discover how collaboration and involvement within an LSS working group amplifies the skills and knowledge of each participant and generates a widespread climate of enthusiasm and strong determination for continuous improvement in every area, both at work and personal level.

Another practical implication that emerged from the study was the high importance to be attributed to the process of measuring company performance. From a consistent database and their level of reliability, it is possible to identify important opportunities for improvement and savings in terms of company resources; the data make it possible to highlight significant problems and inefficiencies, otherwise not recognizable, which are the result of high company costs that impact on company profitability.

The research shows how Lean Six Sigma can offer companies high advantages in achieving the highest quality in the value creation process, however, to ensure the successful success of projects, the desire for change must arise from the depths of top management; it will have to assume the role of promoter of the LSS culture and philosophy, so that the tools of the methodology are effective in managing and guiding the improvement and transformation actions, one step at a time, with rigor and discipline, but with the involvement of all own resources, with the greatest possible efficiency and effectiveness.

The main limitation of the study derives from the qualitative methodology adopted, that while it permits to analyze in depth and broadly all the phases of implementation of the LSS in the company, highlighting the difficulties encountered during the activities and the benefits obtained, these results should be integrated with an analysis on a large sample of companies that have developed similar projects to be more generalizable. Future research should be oriented on developing a quantitative analysis on LSS implementation. In any case, a qualitative study of this depth can give ideas for improvement and development for companies similar in structure and dimension to Schnell S.p.A.

Gantt Chart of the project

Project charter

SIPOC diagram – supplier, input, process, output, customer

Flow Chart: Diagram of the procurement process through the Kanban system

Value stream mapping of the procurement process of the In-Lining line with Kanban system

Population stratification

Graphical summary statistical analysis of Lead Times recorded in the period 01/01/2018–31/10/2019. Population with numbers N  = 74

Graphical summary statistical analysis of Lead Times recorded in the period 01/01/2018–31/10/2019. Population with numbers N  = 70

Frequency of deliveries with centered and delayed lead time (a) and boxplot lead time (b) for sub-category

Frequency of deliveries with centered and delayed lead time (a) and boxplot lead time (b) for sub-category type

Composition of the project team

Project risk analysis

Project risk and calculation of the Risk Priority Index

Process sigma calculation

Report of the performances analyzed in the period November 2018–October 2019

Five why matrix

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Acknowledgements

The authors acknowledge Schnell S.p.A. for supporting the research providing the data that allowed the realization of the case study.

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The Definitive Guide to Six Sigma Project Charters

By Kate Eby | June 14, 2022

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In Six Sigma, a project charter is the first step toward the successful completion of a project. We’ve gathered expert tips and examples to help you understand why and how to get the most out of Six Sigma project charters. 

On this page, you’ll find the fundamentals of Six Sigma project charters and learn how to prepare one effectively . Plus, download free Six Sigma project charter tools, including a customizable template and pre-filled industry examples .

What Is a Project Charter in Six Sigma?

A project charter in Six Sigma is a two-page document that outlines a process improvement project. The charter contains data-driven information explaining the need for the project. Once approved, the document becomes the Six Sigma team's primary reference.

Like traditional project charters , a Six Sigma charter is the initial document that communicates a project’s purpose. It is also a living document that the team will update and review throughout the lifecycle of the project. 

Both traditional project charters and Six Sigma project charters share these key elements:

• Agreement: Document an agreement between the project team and management.
• Alignment: Align project goals with the goals of the entire organization.
• Business Case: Present the business case for the project. 
• Outline: Provide a broad outline of the project.
• Overview: Describe the project’s objectives, necessary resources, and timeline. 
• Project Scope: Define the project scope. 
• Reference Point: Act as a reference point throughout the project. 

Unlike a traditional project charter, a Six Sigma charter requires a team certified in Six Sigma methodology to prepare and execute it. 

In addition to achieving the goals outlined above, the Six Sigma project charter will contain: 

• Six Sigma Certifications and Roles: Designate the  team members assigned to the project, and include their Six Sigma certification and project role.
• Six Sigma Methodology: Identify the Six Sigma tools and methods you plan to use to refine the business processes.
• Six Sigma Statements: Identify the process improvements the project will accomplish, and outline any potential implementation issues.

What Is a Lean Six Sigma Project Charter?

A Lean Six Sigma project charter looks the same as a Six Sigma charter. Some experts believe that there is no significant difference between the two. Others explain that Lean charters focus on preventing issues rather than making incremental improvements. 

The difference between the two is subtle. Similar to a Six Sigma charter, Lean Six Sigma methods and tools help teams eliminate waste in a process. The Lean charter reflects this approach in the goals. 

“Both charters are the same in the structure, but they are different in the goals,” explains Mahmoud Al-Odeh, Professor of Operations and Technology Management at Bemidji State University. “The Lean Six Sigma charter includes goals related to eliminating waste and non-value-adding activities. The Six Sigma project charter includes reducing variation in the process to reach a Six Sigma level, or 3.4 defects per 1 million opportunities.” 

To prepare a Lean Six Sigma project charter, start with a standard Six Sigma project charter template . Craft a Lean goal statement that targets issue prevention or preemptive waste avoidance. A Lean goal statement might say, “We will identify and remove all non-essential steps between intake and examination, such as repetitive forms and paperwork, to reduce patient wait time by 10 minutes.” 

However, George Eckes , the author of five books on Six Sigma who has over 30 years of consulting experience in Lean Six Sigma, process management , and process improvement , does not believe there is a significant difference between the two charter types. 

“To some purists, Six Sigma is aimed at reducing variation exclusively, while Lean is aimed at improvement,” he explains. “I am not a purist. Of the thousands of project teams I have coached, 100 percent of their charters reflected an improvement of effectiveness (i.e., reduction of variation around some target), while at the same time improving efficiency (e.g., reducing cycle time). Thus, there is no difference to me between a Lean Six Sigma Charter and a Six Sigma charter.”

Who Prepares a Six Sigma Project Charter?

A project champion prepares the Six Sigma project charter. This team member owns the process and coordinates a team of certified Six Sigma Green and Black Belts. They also rely on subject matter experts (SMEs) to provide relevant project information. 

With the exception of the SMEs, all team members working on the charter must have a Six Sigma certification . 

These are the different team roles, according to Eckes: 

• Project Champion: The project champion is the process owner and a liaison between management and the project team. The assigned champion’s primary responsibility is creating the charter. Eckes suggests calling the charter the preliminary charter in order to reinforce the concept that “the charter is a living document and will be modified by the champion over time with newly collected data.” 
• Black Belt or Green Belt: The project champion designates one Black Belt or Green Belt as the team leader. A Black Belt leads projects full-time, whereas a Green Belt leads projects part-time. Eckes explains that “more resources are needed for companies to have Black Belts. Most teams do not have these resources, so they use Green Belts. The Green Belts hold down regular jobs and become a Green Belt for the duration of the project.” 
• Team Members: Many of the team members who contribute to the Six Sigma charter do not train in Six Sigma methodology. These team members are SMEs and conduct most of the project work. They work closely with the team leader and project champion. 
• Master Black Belt: A Master Black Belt advises the organization on Six Sigma practices. “Most organizations have a handful of Master Black Belts who can act as ad hoc team members assisting each team member, Black Belt, or Green Belt with the more difficult Six Sigma tools,” says Eckes. 

Each organization will have a unique team structure depending on their resources. For example, some businesses might have several Green Belts and no Black Belts. In this case, the Green Belts will work with the project champion and Master Black Belt.

How to Prepare a Six Sigma Project Charter

A Six Sigma project charter takes up to six weeks to prepare, depending on the project size. The project champion organizes the team and assembles the data into a short document. Champions liaise with management and stakeholders for each activity.  

The steps to writing a Six Sigma project charter are similar to the process for other project charters. A key difference is that Six Sigma project charters will designate roles and responsibilities based on Six Sigma methodology.

As they would for any project, the champion organizes and assembles the charter during the first project phase. This is true whether they are using either of the Six Sigma methodologies : DMAIC (define, measure, analyze, improve, control) or DMADV (define, measure, analyze, design, verify). 

DMAIC is the most popular method for Six Sigma projects. During the define phase, the project champion leads the following activities:

Collect Data

The project champion assigns data collection responsibilities to Green or Black Belts. This team works for a few weeks to gather any data that supports the project. The champion then inputs the gathered information into a charter template and works with the team to fine-tune the document.

Weigh Competing Priorities

The team identifies, weighs, and prioritizes all project tasks. This activity helps to maximize the team’s time and to manage scope creep . Teams use a quadrant chart, called a PICK chart (possible, implement, challenge, and kill) or a payoff matrix, to determine which actions deliver the highest payoff while using the fewest resources. 

To use a PICK chart, create a chart with four quadrants, as you see in the image above. Then discuss and place each project activity on the chart. 

These are the four quadrants of a PICK chart and what they represent:

• Possible: Low-difficulty, low-payoff items that are possible to accomplish. 
• Implement: Low-difficulty, high-payoff items that are a must for the project. 
• Challenge: High-difficulty, high-payoff items that will be a challenge but might be worth the risk. 
• Kill: High-difficulty, low-payoff items that do not make sense to take on and should be killed.

Include any items in the Implement section in your project activities. Remove any items in the Kill section. Finally, lead a team discussion on the items in the other two areas before deciding which to include in the project.

Before presenting the document to management, the project champion edits and reviews the charter and requests any further supporting data from stakeholders.

Submit for Approval

The champion submits the finalized charter to the project sponsor. The sponsor seeks consensus from all stakeholders before signing off on the project.

Schedule Formal and Informal Updates

Once management approves the project, the champion must be diligent about revisiting the charter regularly. Eckes stresses the importance of keeping the document up to date. “It is important for the project champion to constantly revisit the charter to make changes so that it remains a vibrant, living document rather than something that is done early in the project team lifecycle and gathers dust,” he says.

Eckes recommends scheduling formal and informal updates to the charter: “Once the team collects the data, about four to six weeks out, the project champion should formally revisit the charter and make modifications based on the collected data.”

What to Include in a Six Sigma Project Charter

A Six Sigma project charter includes six major elements: business case, problem or opportunity statement, goal statement, scope, timeline and milestones, and team members. Some charters combine the timeline, milestones, and team members into a single category. 

Six Sigma project charter elements use the same titles as traditional project charter elements . These are overviews of the different project charter elements with expert tips on writing each one.

Six Sigma Business Case

A Six Sigma business case describes the issue the project will address. It’s an argument for why the company should take on the project. The case includes how the project impacts the organization and what will happen if the project is not selected. 

A business case is a non-quantitative statement establishing the Six Sigma team’s purpose and direction. It details the project’s necessity and the opportunity cost of declining the project. A compelling business case is brief, usually a two-sentence statement, and articulates the project vision. 

According to Eckes, a business case should answer the following questions: 

• How does this project impact the strategic business objectives of the organization?
• Why is this project worth doing now?
• What are the consequences of not doing this project now?

Tip: Eckes cautions against using data in the business case. “Most champions try to do too much and start sharing data in the business case. The business case is non-quantitative,” he says.

Six Sigma Problem Statement

A Six Sigma problem statement articulates the central problem the project will solve. The statement quantifies an existing process issue. If the statement identifies a new improvement opportunity instead of an existing pain point, it is called an opportunity statement . 

Eckes encourages teams to create the problem statement, even if they’re missing some information. “It’s totally fine to have blanks in the problem statement since the team may not have specific data at the beginning of the project,” he says. “For example, here is a problem statement from one of our clients: Since______, Gamma Alpha has spent __________ processing loan applications with an accuracy of ________. This has resulted in _______increase in labor costs, ________negative achievement of growth objectives and ________ operating margin.”

He also discourages teams from trying to identify the source of the issue in the problem statement. “One of the most common mistakes a project team will experience when creating the problem statement is not stating the problem in neutral terms,” he says. “They will jump to include their experience of what is the cause or perceived solution. Any time you see the phrase due to, the team has jumped to root causation.”

Six Sigma Scope Statement

The scope statement defines the project boundaries for the Six Sigma team. It details what is in and out of scope. An effective scope statement is precise about what work the team will and will not do for the project. 

A poorly constructed scope statement leads to scope creep, which Eckes says is the second most common reason projects fail, after poor team dynamics. Use a scope statement template , include the deliverables, and state what is inside and outside the project team’s boundaries. 

Eckes also recommends including information the project team should know so that they can quickly recognize when they are working on something outside the boundaries of the project. Brainstorm the criteria first (i.e., geography, types of suppliers, types of customers, types of products, elements of the process), then divide the criteria into an inside scope group and an outside scope group. Be specific about what is outside the scope. For example, if geography is a criterion, the scope statement needs to specify which countries are inside and outside the scope

Six Sigma Goal Statement

A Six Sigma goal statement pinpoints the project’s target and articulates what will occur once the team solves the problem. This portion of the project charter should include quantifiable, measurable information. 

Your goal statement should focus on the anticipated result of the project, not on the approach you will take to solve the problem. Write the goal using a tool such as SMART goals . 

Eckes emphasizes the importance of making sure each charter element has a clear connection to the preceding elements. The goal statement should refer back to the problem statement and business case. “In our business case example,” says Eckes, “we stated we had a problem with loan decision accuracy and loan decision time. Therefore, our goal statement should reflect improvement in accuracy and decision time.”

Six Sigma Timeline and Milestones

A Six Sigma timeline outlines the schedule and identifies all project team members. Divide the timeline into phases and milestones. This will help you track progress once you begin the project.

Apply the DMAIC framework when estimating the timeline. For each phase, include a high-level overview of the relevant resources and people who influence the work. Determine major milestones within and at the end of each phase. 

If you are the project champion, set a reasonable timeline with realistic team expectations. Eckes reminds leaders that “their team is not only working on a project but learning new tools and techniques. Give them proper time to complete the project successfully. Project teams members have day jobs that are not going away, and they now have the responsibility of doing two things. They can expect to spend 20 to 30 percent of their time on the project, given that they have some project management experience or knowledge.”

Six Sigma Team Members

Six Sigma team members are everyone working on the project. Document each member’s role, responsibility, and contact information. Team members include Green Belts, Black Belts, sponsors, and subject matter experts. 

Pro Tip: Al-Odeh recommends developing a communication plan to pre-emptively influence effective team dynamics and project success.

Additional Project Charter Elements

Like traditional charters, the Six Sigma charter will include:    

• General Information: Note the project title, start date, and anticipated end date. Add any clarifying information the team may find useful.
• Critical Success Factors: List potential factors that might impact your project’s successful completion (i.e., financial, resource, or time constraints or time to train and develop the team). 
• Financial Benefits: Specify any financial benefits the project will have for the company, as well as the opportunity cost of not completing the project.  
• Risks, Constraints, and Assumptions: Forecast potential events or dependencies that might impact the project’s execution, timeline, budget, or quality. Assess the team’s assumptions.

Six Sigma Project Charter Format

You can format a Six Sigma project charter in several ways. The team usually collects data in the order presented on the charter. All charter formats contain the general project information, business case, milestones, stakeholders, scope statement, and problem statement. 

Al-Odeh recommends using the following format:

Tip: Use the DMAIC framework to help break your timeline into the following phases:  

• Define: Articulate the project goals, scope, and how to fix a problem.  
• Measure: Collect data to measure the current state of the process. 
• Analyze: Analyze the collected data in order to understand the root causes of the problem.
• Improve: Make changes to the process to improve productivity. During this phase, the team tests and verifies any changes to monitor their effectiveness. 
• Control: Ensure future projects implement the process changes.

Six Sigma Project Charter Industry Example Templates

We’ve assembled a comprehensive list of sample Six Sigma project charters, as well as a blank template. Each charter includes an industry-specific example of a business case, problem statement, scope, and goal statement for a Six Sigma process improvement project

Healthcare Six Sigma Project Charter Example

Download Healthcare Six Sigma Project Charter Example — Microsoft Word

This sample healthcare Six Sigma project charter describes an initiative to improve patient discharge time rates from a hospital’s cancer care unit.

Manufacturing Six Sigma Project Charter Example

Download Manufacturing Six Sigma Project Charter Example — Microsoft Word

This sample manufacturing Six Sigma project charter sample describes a project that aims to fix a defect-causing process for a general assembly line.

Pharma Six Sigma Project Charter Example

Download Pharma Six Sigma Project Charter Example — Microsoft Word

This sample pharma Six Sigma project charter demonstrates how you can use Six Sigma methods to improve procurement processes and requisition documents between distributors and companies.

Retail Six Sigma Project Charter Example

Download Retail Six Sigma Project Charter Example — Microsoft Word

This sample retail Six Sigma project charter describes a national retail store’s plan to modify on-floor sales tactics and training methods in order to improve regional sales conversions.

IT Six Sigma Project Charter Example 

Download IT Six Sigma Project Charter Example — Microsoft Word

This sample IT Six Sigma project charter describes an effort to improve an internal IT department’s work order ticketing system.

Aviation Six Sigma Project Charter Example

Download Aviation Six Sigma Project Charter Example — Microsoft Word

This sample aviation Six Sigma project charter outlines a plan to update and scale an airline’s voucher program.

Nonprofit Six Sigma Project Charter Example

Download Nonprofit Six Sigma Project Charter Example — Microsoft Word

This sample nonprofit Six Sigma project charter sample shows how a social impact organization uses Six Sigma to capitalize on a youth program expansion opportunity.

Higher Education Six Sigma Project Charter Example

Download Higher Education Six Sigma Project Charter Example — Microsoft Word

This sample higher education Six Sigma project charter describes an effort to streamline a small private college’s admissions funnel process in order to increase prospective student engagement and enrollment.

Restaurant Six Sigma Project Charter Example

Download Restaurant Six Sigma Project Charter Example — Microsoft Word

This sample restaurant Six Sigma project charter outlines a local restaurant’s plan to improve a disorganized and wasteful supply ordering process in order to increase profit margins.

Real Estate Six Sigma Project Charter Example

Download Real Estate Six Sigma Project Charter Example — Microsoft Word

This sample real estate Six Sigma project charter describes an effort to improve a real estate agency’s document signing and client onboarding processes.

Media Six Sigma Project Charter Example

Download Media Six Sigma Project Charter Example — Microsoft Word

This sample media Six Sigma project charter outlines a plan to make a growing media company’s marketing campaign and channel selection process more efficient.

Construction Six Sigma Project Charter Example

Download Construction Six Sigma Project Charter Example — Microsoft Word

This sample construction Six Sigma project charter describes a project that aims to make a construction company’s build crew work more efficiently.

Six Sigma Project Charter Blank Template

Download Blank Six Sigma Project Charter Template Microsoft Excel | Microsoft Word | Microsoft PowerPoint  

Create a Six Sigma charter for your project with this comprehensive Six Sigma project charter template. Include your business case, problem statement, goal statement, timeline, team, and scope statement. Download the template in Microsoft PowerPoint to create a visually dynamic presentation of your Six Sigma project charter.

For more ideas, check out this selection of traditional project charter templates .

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Home > Learn More About Six Sigma Green Belt > Coca-Cola Case Study: The Six Sigma Process in 2024 [Updated]

Coca-Cola Case Study: The Six Sigma Process in 2024 [Updated]

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Six Sigma process leads us to one conclusion that“Customer is the King”. Customers are the most important aspect of your business. Without the customer, you wouldn’t have a business. Companies have to understand that customers can make or ruin them completely.

One of the large companies like Coca – Cola tried to rule the market according to their wish, which lead to mammoth loss for the company.

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The Coca-Cola Company  ( TCCC) is a leading manufacturer, retailer, and marketer of beverages, which sells beverage products in more than 200 countries. It is an American multinational beverage corporation headquartered in Atlanta, Georgia.

The Coca-Cola Company is into the manufacturing, retailing and marketing of nonalcoholic beverages. The company produces Coca-Cola, invented in 1886 by pharmacist John Stith Pemberton. In 1889 the formula and brand were sold for $2,300 to Asa Griggs Candler, incorporated The Coca-Cola Company in Atlanta in 1892.

Coca-Cola is the most popular soft drink in the world. It’s sold almost everywhere, and its brand name is known in most languages. 

The Coca-Cola Company manufactures and sells not only Coca-Cola itself, but also offers a wide range of other beverages, like Fanta, Sprite, water, juices, and energy drinks. The brand owes its success primarily to the product itself and then to its iconic marketing campaigns that position Coke as a drink with a fun and active lifestyle – “Open Happiness”

It was April 23, 1985 when the Coca-Cola Company changed their Coke recipe. A national poll conducted showed that only about 13% of beverage’s fans liked the new Coke. The company observed a steep downfall; their customers weren’t upset, they were transparently angry.

The customers of Coca-Cola took it upon themselves to initiate the launch of a campaign to bring back the original Coca-Cola back. These passionate customers did everything, from setting up hotlines to signing petitions, and were outspoken in their quest to get the original Coke back.

In this duration, the Coca-Cola Company took a major hit. They spent $4 million in development, and then after deciding to pull it back from the market, they had over $30 million worth of unwanted new Coke concentrate. This was the worst mistake that the Coca-Cola Company had ever made, and it is still referred to as the worst gaffe a company has ever made.

Let’s first understand the Supply chain of TCCC: How it Works

In a nutshell, Coca-Cola beverages go through the following destinations in their journey:

• Manufacturer
• Distributor

The classic workflow within Coca-Cola supply chain:

• The Company has its headquarters in Atlanta. The manufacturing of the concentrated syrup is done here and then sold it to Coca-Cola Enterprises (CCE) or another bottling partner, which is responsible for selling the product in North America and Canada.
• The bottling partner sends it to a manufacturing facility, which mixes the syrup with other ingredients, such as filtered water and sweeteners. After that, the bottler packages the final product and distributes it to retail partners (stores, restaurants, vending machines, etc.)
• The Coca-Cola Export Corporation (TCCEC) partners with local bottlers across the world and distributes the drink to the corresponding local markets.

Other things that contribute to Coca-Cola’s supply chain:

Coca-Cola Enterprises flawlessly integrates modern technologies into its supply chain. For instance, it uses 3D printing to manufacture bottles and cans for its drinks.

    2. People

Logistics team consists of more than 100 people to ensure the safe journey of each bottle from factory to fridge. 

    3. Long-term relationships with retail partners

Over the past few decades, Coca-Cola has proven to be one of the most valuable and reliable suppliers for its retail partners. For instance, the company has been growing together with McDonald’s since 1955.

4. Strict quality control

The company has strict quality requirements for its manufacturing practices. For instance, Coca-Cola HBC, a bottling franchise partner of Coca-Cola Enterprises, requires quality, environment, and health safety certifications from its suppliers.

5. Global Supply Chain Council

The Coca-Cola Company is a beverage giant which has established the Global Supply Chain Council, which consists of subcommittees that focus on adhering to its established supply chain strategy. The Council has its own centralized portal where the employees and supply chain participants share their experiences and best practices.

6. Close collaboration with bottlers

The Coca-Cola Company provides a standard set of guidelines for all of its bottling partners and suppliers. As a result, most of the strategic decisions are centralized. The headquarters controls most of the bottling partner’s operations.

Coca-Cola Logistics

Logistics is an integral part of any supply chain, and Coca-Cola’s logistics expertise undeniably contributes to its supply chain success. Here are some of the logistics-related best practices executed by Coca-Cola:

• Manufacturing products on a more frequent basis
• Connecting with core team weekly worldwide
• Shifting the production plants closer to customers
• Introducing daily interaction among the main sites
• Introducing seamless processes that are shared between all supply chain participants.

Implementation of Six- Sigma process by The Coca-Cola Company

The Definition of the problem was based on Customer’s complaints. The complaint was mostly about the delay in responding to their questions instead of using various lines of customer care. Others had complaints about the lack of consistency of answers given to various customers related to questions like effects of this drink on toddlers. After so much Research, Customer Care department has authorized use of DMAIC project plan to get rid of delay in answering to customer’s query.

The Measure phase analyzed the reason for the delay in responses. Various hotline numbers were inspected along with the various Customer care departments. Machines and other technical issues were examined thoroughly to check whether they played any sort of role for the delay in responses or not. List of Common questions were also shared among the entire customer care department so as to make sure regarding the consistency of answers given to the customers.

The Analyzing Phase , data was presented more in the mathematical form. Uses of graphs, charts were recommended for easy interpretation. This was done to examine why some hotline numbers performed better than others. It also examined why there was delay in responses from customer care department to the customers.

The Improvement Phase was the phase where focus was on the how to solve the identified problems. Employees whose call numbers had better performance were requested to guide other employees so that all the employees are in the same level. Employees were also briefed on how to group questions to be able to give consistent answers to the customers.

The Coca-Cola Company required issuing some Goodwill message to the customers to clarify the matters which customers asked frequently. This will help the customer care call center to get rid of some of the questions which caused delays. Only the uncommon queries were attended by customer care department and therefore the loading on system reduced, which further resulted in better performance of customer care department.

The Control Phase was to ensure that the new standards were followed and maintained. Customer care department was required to submit the weekly reports to Coca-Cola Management to show the progress.

DMAIC project plan has worked in many companies and also worked for Coca-Cola Company. 

Now, let us understand what is “SIX-Sigma ”?

Six Sigma is a methodology which provides tools and techniques to define and evaluate each step of a process. It provides methods to improve efficiencies in a business structure improve the quality of the process and increase the bottom-line profit.

Six Sigma is ranked among the important approaches for making business processes more effective and efficient. In addition to establishing a culture dedicated to continuous process improvement, Six Sigma offers tools and eliminates defects and helps to identify the root causes of errors, allowing organizations to create better products and services for consumers.

Six Sigma is : A Business Strategy:  Using Six Sigma approaches, a business can make strategies along with plan of action and drive revenue to new heights, cost reduction and process improvements can also be done in all parts of the organization.

A Vision:  Six Sigma approaches are helpful for the Senior Management to create a vision which provide defect free, positive environment to the organization.

A Benchmark:  Six Sigma approaches help in improving process metrics. Once the improved process metrics achieve stability; we can use Six Sigma methodology again to improve the newly stabilized process metrics.

A Goal:  By using Six Sigma approaches, companies can keep a rigid goal for themselves and work towards achieving them throughout the year. If any company uses proper approaches of six sigma then it often leads these organizations to achieve these goals.

A Statistical Measure : Six Sigma is a data driven approach. Statistical Analysis is used to identify root-causes of the problem. Additionally, Six Sigma approach is highly used to calculate the process performance using its own unit known as Sigma unit.

A Robust Methodology : Six Sigma is the only approach available in the market today which is a documented methodology for problem solving. If used in the right manner, Six Sigma improvements are bullet-proof and they give high yielding returns.

While most people associate Six Sigma with manufacturing, but the methodology is applicable to every type of process in any industry. An organization uses Six Sigma approach to set up a management system that systematically identifies errors and provides methods for eliminating them.

Watch this video for a complete understanding of Six Sigma.

The Importance of People in Six Sigma

A key component of successful Six Sigma implementation is buy-in and support from executives. This methodology does not work well when the entire organization has not engaged in.

Further, another vital aspect is the training of personnel at all levels of the organization. White Belts and Yellow Belts typically receive an introduction to process improvement theories and Six Sigma Terminologies.

Green Belts typically work for Black Belts on projects, helping with data collection and analysis. Black Belts lead projects while Master Black Belts look for ways to apply Six Sigma across an organization.

People develop expertise in Six Sigma by earning belts at each level of accomplishment. These include Yellow belts, Green Belts, White Belts, Black Belts and Master Black Belts.

The martial arts belt structure is used to recognize proficiency in training and application in Six Sigma, using the following colors:

• White Belt  – Overview DMAIC, Define Phase
• Yellow Belt  – White Belt + process mapping, data collection and charting, assisting with a project
• Six Sigma Green Belt Certification  – Yellow Belt + Project leader, core Six Sigma tools, change management, hypothesis tests and more
• Six Sigma Black Belt Certification  – Green Belt + advanced statistical analysis and experiments, change management,
• Six Sigma Master Black Belt Certification  – Black Belt + Design for Six Sigma, more advanced statistical analysis, unique tools for specific industries and processes, working with leadership, implementing successful improvement programs

Formal certification is recognized at the Green Belt, Black Belt and Master Black Belt level based on one or more of the following criteria:

• Completion of training covering the body of knowledge
• Years of work experience with the body of knowledge
• Passing an exam covering the body of knowledge
• Completion of one or more Six Sigma projects

Process of Six Sigma

There are two major approaches used within Six Sigma:

• DMADV : The DMADV method is typically used to create new processes and new products or services. The letters stand for:

Define the project goals

Measure critical components of the process and the product capabilities

Analyze the data and develop various designs for the process, eventually picking the best one

Design and test details of the process

Verify the design by running simulations and a pilot program, and then handing over the process to the client

• DMAIC : The DMAIC process is used primarily for improving existing business processes. The letters stand for:

The DMAIC project methodology has five phases:

• Define  the system, the voice of the customer and their requirements, and the project goals, specifically.
• Measure  key aspects of the current process and collect relevant data; calculate the ‘as-is’ Process Capability.
• Analyze  the data to investigate and verify cause-and-effect relationships. It also attempts to ensure that all factors are considered.
• Improve  or optimize the current process based upon data analysis using techniques such as design of mistake proofing, and standard work to create a new, future state process.
• Control  the future state process to ensure that any deviations from the target are corrected before they result in defects. A control check is created to monitor the progress of the process.

The DMAIC framework, Six Sigma can utilize several quality management tools:

Seven Basic Quality Tools (Quality core tools):

1. Cause and Effect Diagram:

Also, known as Fishbone diagram. The diagram has its shape similar to a fish skeleton. Hence, named as Fishbone diagram. This tool is used to explore causes to a single effect (or event) through brainstorming. These causes are put under different common categories known as 5 M or 6 M. Where, 6 M expands as – Man, Material, Method, Machine, Measurement & Mother Nature.

2. Flow Chart: It suggests the process flow in a diagrammatic way. It outlines a pictorial representation of processes or process steps to understand their flow upstream or downstream.

3. Pareto Chart:

Also, known as 80:20 principle. The Principle states, 80% of the outcome is a result of 20% causes. It’s a kind of bar chart showing the frequencies of different causes or factors in descending order. The main purpose of this chart is to highlight the most significant factors among a number of factors.

4. Histogram:

It’s a bar chart to study the frequency distribution of data set. It’s used to understand nature of data.

5. Check sheet:

It is used for data collection. A frequency of factorized data is collected in check sheet.

6. Control Chart:

These charts are used to check, whether process data remains under control for the shorter time span. They involve process control limits and sometimes customer specification limits as operational ranges or bands. The aim of these charts is to ensure process data doesn’t go beyond control limits. However, some exception rules are also there to ascertain the condition of a process going out of control, while well within control limits.

Six Sigma strategies seek to improve the quality of the output of a process by identifying and removing the causes of defects and minimizing impact variability in manufacturing 

Each Six Sigma project carried out within an organization follows a defined sequence of steps and has specific value targets, for example: reduce process cycle time, reduce pollution, reduce costs, increase customer satisfaction, and increase profits.

The application of Six Sigma has the ability to reduce the variation of the characteristics of the product or service from the target by using either continuous improvement or a design/redesign approach.

Interesting Facts

It wasn’t that the Coca-Cola Company didn’t do their research; in fact over 53% loved the new Coke over the original. In the blind taste test, the subjects were just asked which one they liked best. So they didn’t have a choice. If they had been told that in choosing the new Coke the original would be moved out from the market, then the result of research would have been something else.

According to the grapevine, customers make their purchasing decisions on habit, longing, and loyalty.

This decision could have destroyed a great company. Luckily they listened to their customers and went back to the original Coca-Cola, and today with Six Sigma methodologies implemented, they are $182.9 billion strong!

Does Coke’s Supply Chain Management Inspire You?

Coca-Cola’s manufacturing and supply chain management have inspired many other companies to learn from their gaffe which resulted in steep lose for the company.

But businesses today had scale growth at a much rapid rate than you could back in the early 1990s because of the new software and automation techniques.

If you too are motivated to learn the Six-Sigma Process, what are six-sigma approaches, what is Six Sigma DMAIC etc. then there is certification courses which is available online and offline. You can pursue the Six- sigma course and earn belts as you accomplish each phase.

Frequently asked Questions and Answers

Q. What is Sig Sigma?

A. Six Sigma is a measurement-based strategy for process improvement. It’s a methodology, which aims at improving process and increasing customer satisfaction (Both internal & external). The concept behind this approach is to reduce the variation in processes. This reduction leads to consistent and desired outcomes from processes. Hence, Continuous process improvement with low defects is the goal of this method.

Q. How Coca-Cola Company used Six-Sigma process?

A.  The Company used the most Common and applicable to almost all the companies Six-Sigma approach to bounce back in market in no time. Refer BSI Case Study Coca-Cola Enterprises Ltd , for more clarity.

Q. What is Six-Sigma DMAIC?

It is an integral part of Lean Six Sigma process, but can be implemented as a standalone quality improvement process. Indeed, it is the most preferred tool that can help improving the efficiency and the effectiveness of any organization six- Sigma Approach DMAIC

Q. Which is the best online platform for Six Sigma Course?

A . Sig Sigma Course from Henry Harvin Education is ranked as top online platform to pursue Six-sigma Course.

Q. Career benefits after Six-Sigma course?

A. After completing the six sigma course certification you become eligible for jobs demanding analytical background, you Open doors to Job Opportunities Abroad demanding specialization. Or you can also Support a Startup with improved Process and Performance that leads to high-quality products and services.

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Multi-Vari Chart: Powerful Tools for Process Analysis and Improvement

May 6th, 2024

One of the most flexible and revealing tools in the Six Sigma toolbox is the multi-vari chart. This graphical method lets you see and study the different causes of variation in a process.

The multi-vari chart is a handy diagnostic that helps pinpoint and fix the root sources of process inconsistencies.

This article will give you the know-how to correctly build, read, and use multi-vari charts to your advantage. You’ll gain the skills needed to analyze processes and fuel continual upgrades.

Let’s jump in and explore how multi-vari charts work their magic. I’ll show you how to construct them, decipher what they’re revealing, and leverage their insights to transform your business.

Key Highlights

• Understand the fundamentals of multi-vari charts, including their definition, benefits, and applications across various industries.
• Learn the step-by-step process of creating multi-vari charts, from collecting data and determining factors and levels to manual construction and software-based approaches.
• Gain insights into interpreting multi-vari charts, analyzing within-piece, piece-to-piece, and time-to-time variations.
• Explore case studies that illustrate the practical application of multi-vari charts in manufacturing process optimization, quality control, and root cause analysis.
• Discover best practices for using multi-vari charts effectively.
• Understand the role of multi-vari charts in Six Sigma and Lean Six Sigma methodologies.
• Address common questions, compare multi-vari charts with other graphical techniques, and learn how to avoid common pitfalls.

What is a Multi-Vari Chart?

In the process improvement and Six Sigma methodologies, the multi-vari chart stands as a powerful diagnostic tool that enables us to visualize and analyze the sources of variation in a process. 

Definition of Multi-Vari Chart

A multi-vari chart is a graphical representation that illustrates the relationship between factors (input variables) and a response (output variable) in a process. 

It is a two-dimensional chart where time is plotted on the horizontal axis, and the process output measurement is plotted on the vertical axis. 

The chart is designed to display three distinct sources of variation: within-piece variation (positional), piece-to-piece variation (cyclical), and time-to-time variation (temporal).

Benefits of Using Multi-Vari Charts

1. Visualize Multiple Sources of Variation

One of the primary advantages of multi-vari charts is their ability to simultaneously visualize and analyze three distinct types of variation within a single graphical representation. 

This comprehensive view allows for a more holistic understanding of the process and the factors contributing to its variability.

2. Identify Root Causes Quickly

By examining the magnitude of variation across different sources (positional, cyclical, and temporal), multi-vari charts can provide valuable clues about the potential root causes of process variation . 

This visual analysis can significantly accelerate the root cause identification process, leading to more targeted and effective improvement efforts.

3. Simplicity and Accessibility

Multi-vari charts can be constructed manually, making them accessible to operators and frontline personnel. This hands-on approach fosters engagement and ownership among those directly involved in the process, enhancing their understanding and commitment to the improvement efforts.

Applications of Multi-Vari Charts

Multi-vari charts have widely applied across various industries and processes, including manufacturing, healthcare, finance, and service operations. 

They are treasured in situations where multiple factors influence a critical process output, and identifying the sources of variation is crucial for process optimization and quality improvement. Some specific applications of multi-vari charts include:

1. Manufacturing Process Optimization

In manufacturing environments, multi-vari charts can be used to analyze variations in critical product characteristics, such as dimensions, strength, or performance metrics. 

By identifying the sources of variation, manufacturers can implement targeted process improvements to enhance product quality and consistency.

2. Quality Control and Assurance

Multi-vari charts are valuable tools in quality control and assurance initiatives. 

They can help identify sources of variation that impact product or service quality, enabling organizations to take corrective actions and maintain high standards of quality.

3. Root Cause Analysis

In problem-solving and root cause analysis efforts, multi-vari charts serve as powerful diagnostic tools. 

They can provide insights into the underlying causes of process variations, guiding teams towards effective solutions and preventing the recurrence of issues.

How to Create a Multi-Vari Chart

Creating a multi-vari chart is a straightforward process that can be accomplished both manually and with the aid of statistical software. 

However, before diving into the construction methods, it is essential to understand the key components and data requirements for effective multi-vari chart creation.

Factors and Levels in Multi-Vari Charts

Multi-vari charts are designed to analyze the relationship between factors (input variables) and a response (output variable). 

Factors can be any process parameter or condition that may influence the output, such as machine settings, operator techniques, environmental conditions, or material characteristics.

Each factor can have multiple levels, which represent the different values or settings that the factor can take. 

For example, if we are analyzing the impact of three machines on a particular output, the “machine” factor would have three levels (Machine 1, Machine 2, and Machine 3).

It is generally recommended to limit the number of factors to a maximum of six to maintain the interpretability and clarity of the multi-vari chart. 

Additionally, each factor should have at least two levels to enable the analysis of variation.

Collecting Data for Multi-Vari Chart

Effective multi-vari chart creation relies on the collection of high-quality data that accurately represents the process being studied. Here are some key considerations for data collection:

Sample Size

Determine an appropriate sample size that captures the inherent variation in the process. Typically, a minimum of three consecutive units or samples is recommended for each factor combination, but more may be needed depending on the process’s complexity and variability.

Measurement Procedure

Establish a consistent and standardized measurement procedure to ensure data integrity and reliability. 

This may involve the use of calibrated measurement instruments, proper sampling techniques, and adherence to standard operating procedures.

Data Organization

Organize the collected data in a structured manner, typically in a tabular format. This will facilitate the construction of the multi-vari chart and ensure that all relevant factors and levels are properly represented.

Manual Construction of Multi-Vari Chart

While statistical software can streamline the creation of multi-vari charts, it is valuable to understand the manual construction process, as it can provide deeper insights into the underlying principles and foster a better understanding of the tool.

Plot the Measurements

On a two-dimensional graph, plot the individual measurements for each unit or sample, using a consistent symbol or color to represent each measurement within the unit. Connect these measurements with a solid line to illustrate the within-piece variation.

Calculate and Plot Unit Averages

Calculate the average value for each unit or sample and plot these averages using a different symbol or color. Connect the unit averages with a long-dashed line to represent the piece-to-piece variation.

Determine and Plot Overall Averages

Calculate the overall average for each set of consecutive units or samples and plot these averages using a distinct symbol or color. Connect the overall averages with a short-dashed line to represent the time-to-time variation.

Indicate Time Breaks

Use vertical lines or other visual cues to indicate breaks in time or shifts between sets of consecutive units or samples.

Creating Multi-Vari Charts with Software

While manual construction can be valuable for understanding the principles of multi-vari charts, statistical software can significantly streamline the process and provide additional analytical capabilities. Two commonly used software tools for creating multi-vari charts are:

Microsoft Excel, with its powerful charting and data analysis capabilities, can be used to create multi-vari charts. Third-party add-ins or macros may be required to automate the chart creation process and incorporate advanced features.

Minitab is a comprehensive statistical software package that includes dedicated tools for creating multi-vari charts. Its user-friendly interface and specialized features make it a popular choice among Six Sigma practitioners and quality professionals.

Regardless of the software used, the key steps involved in creating a multi-vari chart remain similar: importing or entering the data, selecting the appropriate chart type, specifying the factors and response variable, and adjusting the chart settings and formatting as needed.

Interpreting a Multi-Vari Chart

Once a multi-vari chart has been constructed, the next crucial step is to interpret the graphical representation effectively. 

By analyzing the patterns and variations displayed in the chart, valuable insights can be gained regarding the sources of process variation and potential areas for improvement.

Analyzing Within-Piece Variation

Within-piece variation, also known as positional variation, refers to the variability observed within a single unit or sample. This type of variation can be visually assessed by examining the spread or range of the individual measurements plotted for each unit.

A larger spread or range of measurements within a unit indicates a higher degree of within-piece variation, which may be attributed to factors such as inconsistent measurement techniques, non-uniform material properties, or localized process variations.

By analyzing the within-piece variation, you can identify potential issues related to measurement processes, operator techniques, or inherent material or product characteristics that may require attention.

Analyzing Piece-to-Piece Variation

Piece-to-piece variation, also known as cyclical variation, represents the variability observed between consecutive units or samples. This type of variation can be evaluated by examining the pattern and magnitude of the long-dashed line connecting the unit averages.

A more erratic or fluctuating pattern of the long-dashed line indicates higher piece-to-piece variation, which may be attributed to factors such as machine settings, tooling conditions, or batch-to-batch variations in raw materials or processes.

By identifying and addressing the sources of piece-to-piece variation, you can improve the consistency and reproducibility of your process, leading to higher product or service quality and reduced waste or rework.

Analyzing Time-to-Time Variation

Time-to-time variation, also known as temporal variation, refers to the variability observed over longer periods of time or across different production runs or shifts. This type of variation can be assessed by examining the pattern and magnitude of the short-dashed line connecting the overall averages.

A more pronounced or fluctuating pattern of the short-dashed line indicates higher time-to-time variation, which may be attributed to factors such as environmental conditions (temperature, humidity), equipment wear and tear, or changes in personnel or operating procedures.

By addressing the sources of time-to-time variation, you can enhance the long-term stability and robustness of your process, ensuring consistent performance and quality over extended periods.

Identifying Interactions and Root Causes

While analyzing the individual sources of variation is crucial, it is also important to consider potential interactions between factors. Interactions occur when the effect of one factor on the process output depends on the level of another factor.

Multi-vari charts can provide visual cues about potential interactions by revealing patterns or trends that deviate from the expected behavior. 

For example, if the within-piece variation increases or decreases systematically over time, it may indicate an interaction between positional and temporal factors.

By identifying these interactions, you can gain deeper insights into the root causes of process variation and develop more comprehensive and effective solutions. 

It is essential to complement the visual analysis of multi-vari charts with statistical techniques, such as Analysis of Variance (ANOVA), to quantify the significance of main effects and interactions.

Case Studies of Multi-Vari Chart

To illustrate the practical application and power of multi-vari charts, let’s explore some real-world examples and case studies from various industries. 

These scenarios will demonstrate how multi-vari charts can be used to identify sources of variation, pinpoint root causes , and drive process improvements.

Manufacturing Process Optimization

In a manufacturing facility producing automotive components, engineers were tasked with reducing the variability in the dimensional tolerances of a critical part.

By constructing a multi-vari chart, they were able to visualize the sources of variation in the production process.

The multi-vari chart revealed that the most significant source of variation was piece-to-piece, with the long-dashed line connecting unit averages displaying a highly erratic pattern. Further investigation revealed that the root cause was related to inconsistent machine settings and tooling wear.

Armed with this information, the engineers implemented preventive maintenance schedules, standardized machine setup procedures, and introduced statistical process control (SPC) monitoring. 

As a result, the piece-to-piece variation was significantly reduced, leading to improved product quality and reduced scrap rates.

Quality Control in Baking

In a commercial bakery, maintaining consistent product quality was a top priority. However, the bakery was experiencing significant variation in the width of cookies, leading to customer complaints and potential waste.

To identify the sources of variation, a multi-vari study was conducted, and a multi-vari chart was constructed. The chart revealed that the most significant source of variation was within-piece, with a large spread of measurements observed for individual cookie sheets.

Further investigation traced the root cause to temperature inconsistencies within the ovens, as well as variations in the placement of cookies on the baking sheets. 

Frequently Asked Questions about Multi-Vari Charts

As with any powerful tool, multi-vari charts can raise questions and concerns, particularly for those new to the technique or encountering specific challenges in their application.

Advantages Visual Representation : Multi-vari charts provide a clear and intuitive visual representation of process variation, making it easier to identify patterns and potential sources of variation. Comprehensive Analysis : By simultaneously displaying within-piece, piece-to-piece, and time-to-time variations, multi-vari charts offer a holistic view of the process, enabling a more thorough analysis. Accessibility : Multi-vari charts can be constructed manually, making them accessible to operators and frontline personnel, fostering engagement and ownership in improvement efforts. Diagnostic Capabilities : Multi-vari charts serve as powerful diagnostic tools, providing valuable clues about potential root causes and guiding further analysis and investigation. Disadvantages Interpretation Challenges : While the visual representation is intuitive, interpreting multi-vari charts and identifying patterns can be challenging, especially for complex processes or when interactions are present. Limited Statistical Rigor : Multi-vari charts are graphical representations and do not provide statistical measures of significance. They should be complemented with statistical techniques like ANOVA for a more rigorous analysis. Data Requirements : Constructing accurate multi-vari charts requires sufficient data collection, which can be time-consuming and resource-intensive, especially for processes with high variability or numerous factors. Potential Limitations : Multi-vari charts may not be suitable for certain types of data or situations where the assumptions underlying their construction are violated (e.g., non-normal distributions, non-continuous data).

While multi-vari charts are powerful tools, they are not the only graphical techniques available for process analysis and improvement. It is important to understand how multi-vari charts compare to other commonly used graphical methods, such as scatter plots and histograms. Scatter Plots Scatter plots are useful for visualizing the relationship between two continuous variables, such as a process input and output. They can help identify potential correlations or patterns but do not provide insights into the sources of variation within the process. In contrast, multi-vari charts are designed to analyze the relationship between multiple factors and a single response variable, while simultaneously visualizing different sources of variation (within-piece, piece-to-piece, and time-to-time). Histograms Histograms are graphical representations of the distribution of a single continuous variable, such as a process output. They can provide insights into the central tendency, spread, and shape of the distribution but do not directly reveal the sources of variation or the impact of multiple factors. Multi-vari charts, on the other hand, are specifically designed to analyze the impact of multiple factors on a single response variable and identify the sources of variation within the process. While scatter plots and histograms can provide valuable information, multi-vari charts offer a more comprehensive and diagnostic approach to process analysis, particularly when multiple factors are involved and understanding the sources of variation is critical for process improvement.

Despite their effectiveness, multi-vari chart analysis is not without potential pitfalls and common mistakes that can lead to erroneous conclusions or ineffective improvement efforts.  Ignoring Measurement System Variation Failing to validate the measurement system and account for potential measurement variation can lead to inaccurate multi-vari chart interpretations and misguided improvement efforts. Insufficient Data Collection Inadequate sample sizes or insufficient time intervals can result in incomplete or inaccurate representations of the process variation, leading to incorrect conclusions and suboptimal solutions. Overlooking Interactions While multi-vari charts can provide visual cues about potential interactions between factors, overlooking or failing to investigate these interactions can result in an incomplete understanding of the root causes and ineffective improvement strategies. Overreliance on Visual Interpretation While the visual representation of multi-vari charts is intuitive, overreliance on visual interpretation without complementary statistical analysis can lead to subjective conclusions and potentially miss significant effects or interactions. Lack of Process Knowledge Effective multi-vari chart analysis requires a deep understanding of the process being studied. Lack of process knowledge can lead to incorrect assumptions, misinterpretations, and ineffective improvement efforts. To mitigate these pitfalls, it is crucial to follow best practices, such as conducting thorough measurement system analyses, collecting sufficient data, and incorporating statistical techniques.

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