lean six sigma supply chain case study

Advances in Sustainable and Competitive Manufacturing Systems pp 1475–1487 Cite as

Lean Six Sigma Supply Chain Case Study: Aircraft Shipment Improvement in a Pharmaceutical Company

• Luis Rocha-Lona 2 ,
• Silvia Edith Alvarez-Reyes 2 ,
• Steve Eldridge 3 ,
• Jose Arturo Garza-Reyes 4 &
• Vikas Kumar 5  
• Conference paper
• First Online: 01 January 2013

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Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Distribution is an important activity in the integrated supply-chain management for pharmaceutical products, especially when these goods have to travel long distances from manufacturing facilities to the consumer markets. This paper presents the case of a pharmaceutical company in which the quality assurance and the management teams set an objective of reducing their distribution costs to less than 0.16 Euros per unit. The quality assurance (QA) team has decided to optimize sample shipments as a high priority in order to reduce costs. The methodology used in this study was supported through a series of experiments using a Lean Six Sigma approach that implemented the Define Measure Analyze Improve Control (DMAIC) phases. The QA team analyzed the previous state of sample shipments and then suggested improvements based on an optimized process. The results showed a set of non-value added activities specifically in transportation, motion, waiting, defects, and the sub-utilization of people. Based on Lean tools, the improvements achieved a 26 % reduction in the cycle time spent and no complaints from customers have been reported since implementation of the new process. In addition, a control plan was also developed to track shipments and maintain open and close communication with the customer. Finally, the resulting processes that have been implementation have a significant impact on reducing distribution costs.

• Quality Designee
• Distribution Cost
• European Economic Area
• Total Productive Maintenance
• Sample Shipment

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Luis Rocha-Lona & Silvia Edith Alvarez-Reyes

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Steve Eldridge

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Rocha-Lona, L., Alvarez-Reyes, S.E., Eldridge, S., Garza-Reyes, J.A., Kumar, V. (2013). Lean Six Sigma Supply Chain Case Study: Aircraft Shipment Improvement in a Pharmaceutical Company. In: Azevedo, A. (eds) Advances in Sustainable and Competitive Manufacturing Systems. Lecture Notes in Mechanical Engineering. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00557-7_119

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• Introduction Lean Six Sigma Overview Case Study Introduction Define Phase Measure Phase Analyze Phase Improve Phase Control Phase Conclusions Lean Six Sigma Glossary Index.
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• Introduction. Case Study Overview. Define Phase. Measure Phase. Analyze Phase. Improve Phase. Control Phase. Conclusions. Glossary. Bibliography.

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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.

Corresponding author

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Improve Your Supply Chain with Lean Six Sigma

• Lean Six Sigma Applications

15 May, 2021

With so many moving parts that need to mesh perfectly together, supply chain management is a delicate process. A seemingly small adjustment can have far-reaching consequences throughout the production cycle. This is why Lean Six Sigma can be such a powerful force. When applied by experts in its use, Six Sigma methodologies, paired with the Lean approach, help quality control officers and managers identify issues that would otherwise remain hidden.

Lean Six Sigma for Supply Chain Management

Supply chain optimization is a never-ending challenge, as it should be. Today’s businesses need to constantly seek out more efficient methods and processes. Lean Six Sigma provides an excellent framework for this endeavor, combining the defect prevention focus of Six Sigma with the emphasis on waste reduction and streamlining offered by Lean thinking.

There are a number of ways that companies around the world have used Lean Six Sigma methodology to improve supply chain performance.

Decrease waste

Reducing the 8 potential wastes that can affect a supply chain (defects, overproduction, waiting, non-utilized talent, transportation, inventory, motion, and extra processing) is one of the central objectives of the Lean methodology. But what’s more important is how supply chain analysts determine what’s truly wasteful and not a necessary part of the process. For Lean businesses, this distinction is made based on one variable: value to the customer.

A Lean business aims to deliver the highest quality product at the lowest possible price, which means using few resources as effectively as possible to bring that product to market. Any part of the process that doesn’t actively and directly contribute to that goal is considered waste. Using the Six Sigma DMAIC/DMADV approach combined with the Lean method can help identify these wasteful elements, keeping costs low for the business and the customer.

Prevent defects

Lean thinking has its role to play in this, as well. Any complex, convoluted, time-consuming process leaves more room for failure, opening up opportunities for human or technical error. By integrating the Lean method with Six Sigma analysis , processes can be simplified and streamlined. This means fewer defects, which helps maintain quality standards and decreases the waste caused by defective products.

Improve performance

The combined Lean and Six Sigma methods are uniquely suited to optimizing a supply chain. Together, these philosophies provide a unified focus on two fundamental aspects of manufacturing: efficiency and quality. Every stage of the DMAIC/DMADV approach is an excellent opportunity to refine processes, solve problems, and reduce waste. The result? A stronger bottom line.

The Lean Six Sigma method can help supply chain managers ensure that every part of their process isn’t just defect-free, but focused on their customer. By defining their customer base and needs early on in the DMAIC/DMADV process, businesses can align all of their process improvements to the goal of serving their customers with distinction. Every team member can stay focused on the ultimate goal, which is to make customers happy with their purchase.

This simultaneous focus on the customer and the process is what makes Lean Six Sigma such a valuable, high-impact skill-set. When everyone unifies to serve the customer, businesses thrive.

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Using Lean Six Sigma to Redesign the Supply Chain to the Operating Room Department of a Private Hospital to Reduce Associated Costs and Release Nursing Time to Care

Lisa o’mahony.

1 Beacon Hospital, UCD Beacon Academy, Beacon Court, Bracken Road, Sandyford Business Park, Sandyford, D18 AK68 Dublin, Ireland; [email protected] (K.M.); [email protected] (J.O.)

Kerrie McCarthy

Josephine o’donoghue, seán paul teeling.

2 UCD Centre for Interdisciplinary Research, Education and Innovation in Health Systems, School of Nursing, Midwifery and Health Systems, University College Dublin, D04 V1W8 Dublin, Ireland; [email protected] (S.P.T.); [email protected] (M.M.)

3 Centre for Person-Centred Practice Research, Division of Nursing, School of Health Sciences, Queen Margaret University Drive, Queen Margaret University, Musselburgh EH21 6UU, East Lothian, Scotland, UK

4 Centre for Innovative Human Systems, School of Psychology, Trinity College, The University of Dublin, Dublin 2, Ireland; [email protected]

Martin McNamara

Associated data.

The data presented in this study are available in the paper.

Continuity of the supply chain is an integral element in the safe and timely delivery of health services. Lean Six Sigma (LSS), a continuous improvement approach, aims to drive efficiencies and standardisation in processes, and while well established in the manufacturing and supply chain industries, also has relevance in healthcare supply chain management. This study outlines the application of LSS tools and techniques within the supply chain of an Operating Room (OR) setting in a private hospital in Dublin, Ireland. A pre-/post-intervention design was employed following the Define, Measure, Analyse, Improve, Control (DMAIC) framework and applying LSS methodology to redesign the current process for stock management both within the OR storage area and within a pilot OR suite, through collaborative, inclusive, and participatory engagement with staff. A set of improvements were implemented to standardise and streamline the stock management in both areas. The main outcomes from the improvements implemented were an overall reduction in the value of stock held within the operating theatre by 17.7%, a reduction in the value of stock going out of date by 91.7%, and a reduction in the time spent by clinical staff preparing stock required for procedures by 45%, all demonstrating the effectiveness of LSS in healthcare supply chain management.

1. Introduction

This paper outlines a case study in a private hospital in Ireland. The hospital operates as a full-service acute hospital with over 200 inpatient beds, 8 Operating Rooms (OR), 1400 healthcare professionals, and 300 consultants. The hospital has an established education and training academy with links to a university-accredited Lean Six Sigma (LSS) training programme. The academy is central to the hospital’s ongoing improvement journey, which is working toward a system-wide deployment of LSS led by its LSS-trained staff. The hospital choose LSS for its approach to improvement as it has been shown that in addition to improving efficiency that it has evidenced a positive impact on patient outcomes, and patient and staff experiences of care [ 1 , 2 ].

The term ‘Lean’ has been used to describe the philosophy of the Toyota Production System (TPS) [ 3 , 4 , 5 , 6 ] developed in the car manufacturing industry. Syrett and Lammiman [ 7 ] claim that Lean can be seen as a ‘coherent philosophy’ that introduces new ways of working or doing things that can be considered ‘leanness’. Lean is based largely on Taiichi Ohno’s [ 8 ] insights, where production activities are either classified as value-adding or waste (non-value-adding), with the purpose to increase the proportion of value-adding activities in a process using methods such as pull, flow, standardised work, leveling, and continuous improvements. Value is based on the end customers’ perception giving an outside reference to a process [ 3 ]. Dos Reis Leite and Vieira [ 6 ] suggest that health services, as with any service, have issues with quality that are a real challenge for managers and staff, and which lend to Lean for improvement.

Six Sigma is a data-driven process improvement methodology designed to improve process capability and enhance process throughput through the introduction of improvement projects [ 9 , 10 , 11 ]. It is a quality improvement methodology and management system, focusing on data and costs [ 12 ]. Six Sigma is a systematic, data-driven approach using the Define, Measure, Analyse, Improve, and Control (DMAIC) process and utilising design for the Six Sigma method [ 13 ]. In the DMAIC model, stakeholder or ‘customer’ engagement is sought from the outset at the Define stage. This stage aims to create value for the customer by identifying problems or issues that need solutions early on [ 14 ], utilising the extensive knowledge base of customers and other stakeholders [ 15 ]. Both Lean and Six Sigma have a strong focus on the customer, the employee, management support, and teamwork [ 16 ].

A hybrid of Lean and Six Sigma as LSS appears in the healthcare literature from 2010 onwards [ 17 ] following Lean and Six Sigma integration for project delivery from early 2002 and increased use by 2008. One of the key strengths of LSS is that it seeks to find the ‘root cause’ of problems in a process, which means that it utilises real-time observational data collection [ 18 , 19 ], the process of which is referred to as ‘Gemba’ in Lean terminology [ 20 ]. Langabeer and colleagues [ 21 ] see Lean as promoting a ‘doing the right thing’ approach (value-added) while Six Sigma focuses on ‘doing things right’ (no errors). LSS focuses on the value desired by the end customer, maintaining continuous flow, continuous improvement, and the elimination of waste/non-value-added activity (e.g., waiting/idle time, excess motion, excess or useless inventory, over-processing, and overproduction [ 8 ]. Emerging literature on the benefits of LSS in healthcare can be seen across the health system including but not limited to, improvements in patient length of stay and waiting times [ 22 , 23 , 24 ], earlier access to diagnostics and treatment [ 25 , 26 , 27 ], and with an associated reduction in costs and waste [ 28 ].

The focus of this paper is on an improvement project within the Operating Room (OR). The OR is where all the elective and emergency surgical activity takes place for specialties including cardiology, neurology, gynaecology, urology, orthopaedics, and gastroenterology. The OR is one of the most resource-intensive areas of a hospital accounting for 52% of its overall expenditure (consumables include a broad range of medical surgical supplies from gauze, syringes, and scissors to sterile customised procedure packs and implantable medical devices). OR consumables rapidly expanded from the hospital opening in 2006 to 2018 in response to new procedures, changes in surgeons, and a more complex case mix. The sharp rise in consumable demand within both the existing defined space and processes led to sporadic storage of stock and inconsistent reordering classification. The Periodic Automatic Replacement (PAR) level is defined as setting a certain quantity and maintaining that level. PAR levels had not been amended in the hospital since 2015. A 2017 December stocktake by the procurement team revealed €27,000 worth of out-of-date stock within the OR which prompted a more detailed examination of the process for stock management and was the catalyst for this improvement project. The hospital had limited insight into out-of-date or wasted stock within the OR clinical working ‘clean’ areas, that are physically demarcated by red lines on the floors, to alert non-OR staff against access and prevent potential cross-contamination. This lack of stock visibility in the existing process for stock management could be attributed to OR procurement staff managing stock only as far as the main OR store room which was located outside the sterile area, effectively beyond the red line. Once the stock was moved over the OR redline to the clinical area, it was no longer monitored. The OR redline was highlighted as a barrier of entry for the procurement team/a move from clean or non-sterile to sterile, with staff required to change clothes and don surgical scrubs and designated footwear to cross the redline.

Overstocking has been shown to significantly drive up annual costs in healthcare systems, with one LSS case study demonstrating excess stock levels in 69 Emergency Room (ER) locations with an associated value of $1,040,000 [ 29 ]. The case study identified expired products as a key factor to address in inventory management, estimating that savings of approximately $213,000 yearly could be achieved. It was clear from the literature that over-processing of stock and stock hoarding is a common occurrence in healthcare settings, the fear of supply shortage can create a ‘hoard’ mentality amongst both clinical and supply chain staff, which is in effect a compensatory behaviour for running out of stock [ 30 ]. However, it is important to understand that from the clinical staff perspective that out-of-stock situations are undesirable, and not having the correct supplies at Point of Use (POU) when needed can impact on the quality of care [ 30 ] and in a worst-case scenario can lead to a loss of life [ 31 ], which leads operating theatre staff to err on the side of overstocking. Ensuring stock levels are right is therefore not just an issue of cost or process efficiency, but as indicated, of patient safety. Within the study site, an additional factor was that collating stock for use in surgical cases took an OR nurse on average 4.52 min per case, with the OR nurse pulling up to 11 cases per surgical list, effectively 53 min per day. Given that many OR had 2 lists per day, this time could be doubled. This posed the question ‘Can the use of LSS reduce incidences of overstock, reduce associated costs and release nursing time to care?’

2. Materials and Methods

One OR suite which was newly refurbished was chosen as a pilot site to test the use of LSS in reducing overstock, associated costs, and releasing nursing time. The findings of this pilot were subsequently used and translated across all of the other seven ORs in the Hospital.

We utilised a team-based approach with a pre-and post-intervention design employing LSS methods. The team consisted of a multi-disciplinary group of LSS-trained staff involving procurement, quality, and allied therapy professionals.

Aims of this study included

• Standardisation of stock handling over the sterile area redline,
• A reduction in the value of stock going out of date by a minimum of 50%,
• Providing POU stock to avoid out-of-stock situations,
• Creation of dedicated storage areas by surgical and anaesthesia specialty in the main OR stores,
• Remove non-value-added (NVA) activity for nursing staff and release time to care,
• Development of a proof of concept in a pilot OR suite to roll out to the other OR suites, and
• Demonstrate the effectiveness of LSS, with its proven ability to transcend healthcare silos [ 1 , 2 , 19 ], in improving OR stock issues as part of a whole-system approach to improvement.

We used the Define, Measure, Analyse, Improve, Control (DMAIC) framework to understand and approach the issue of stock and financial waste, raised by the end of year stocktake. Within the framework, we made use of the following LSS tools ( Table 1 ):

LSS tools used by the team.

We now elaborate on each stage of the improvement using the DMAIC framework to outline our methods.

2.1. Define

LSS speaks to ascertaining the Voice of the Customer (VOC) in any process improvement. The VOC in healthcare is considered that of any service user (patient) or provider (staff) or any end-user [ 1 , 2 ], and specifically addresses customer expectations [ 35 ]. Obtaining the VOC has also been shown to be synergistic with person-centred approaches to understanding the needs of the person [ 1 , 2 ]. We sought the VOC to firstly identify customers, gather customer needs and then determine issues critical to quality. Stakeholders were identified (Materials manager, OR procurement staff, Chief Financial Officer, OR director of nursing, nurse manager, nurse coordinator, and OR staff nurses). A Responsible, Accountable, Consulted Informed (RACI) tool was used to identify those responsible, those accountable, those who needed to be consulted, and those who need to be kept informed at the different stages of the DMAIC process [ 38 ]. For our qualitative semi-structured interviews, we drew on a purposive sample from two main groups working with the stock process—clinical staff in the OR (OR nurse managers, co-coordinators, and staff nurses) and procurement stores staff. The purposive sample was designed to enable data generation and draw inferences and credible explanations from the data that were generated and to be as efficient as practical [ 39 ].

The interviews took two forms:

• A duration of 30 min working alongside individual OR nurses [n = 12] and procurement staff [n = 2] opportunistically (interviewing OR nurses as they dealt with supply and stock for surgical cases).

These interviews took place in the OR, and staff often physically demonstrated issues within the stock room such as the same product in multiple locations or unused stock left in bags or trollies throughout the OR. The open-ended format in which these stakeholders were asked about issues with stock in the OR yielded many comments and these were transcribed and thematically analysed (waste, health, and safety, space, and layout). For example, “thousands worth of aortic cannulas were dumped yesterday and we’re ordering more” (waste) and “we have trollies of stuff everywhere” (space). Concerns were raised about stock remaining exposed in a sterile OR room, and potential blocking of exit doors due to the volume of stock trollies (Health and Safety). When we interviewed the procurement stores staff they reported accountability and ownership issues “we’re relying on busy nurses to return stock to the right place, trollies are wheeled in and left full of stock”. They also reported that once the stock goes over the sterile OR ‘redline’, they do not know what happens to that stock.

• 2. 40 min meetings with OR managers [n = 8], co-ordinators [n = 4] and OR procurement staff [n = 2]. These interviews were semi-structured and facilitated an interview format that allowed pre-determined topics to be covered (waste, health, and safety, space, and layout) that had been found in the 30 min interviews; however, it also afforded the flexibility to discuss individual participant’s experiences in more detail [ 40 ].

Data analysis was carried out using thematic analysis of interview outputs, a common analysis technique for qualitative research [ 41 , 42 ].

A further issue that emerged during VOC 40 min meetings was the over-stocking of sutures. Sutures were in multiple sites and locations within stores and throughout trollies. Stocktake in September 2018 found 1112 boxes of sutures. Having engaged with the supplier, who estimated adequate suture stock for the hospital’s OR needs at 260 boxes, the cost of this over-stock was calculated to be €61,000. Therefore, sutures, originally not considered as part of our improvement, came into the scope of the project following VOC.

Carrying out the VOC enabled us to define factors that were Critical to Quality (CTQ). The CTQ is a tool that structures information collected from customers and translates it into critical and specific process requirements that are measurable [ 34 ]. See Figure 1 .

Critical to Quality Tree (CTQ).

The VOC and CTQ exercise identified that the key metrics to focus on for data collection were related to:

• Nursing time to prepare stock for cases,
• End of year stocktake, and
• Value of location of stock within the pilot OR (OR 6).

2.2. Measure

To support our data collection, we carried out Gemba walks to fully understand the processes involved from the perspectives of both the nursing staff OR Procurement staff.

A Gemba walk is a technique used to observe and understand how work is being performed with the following elements: observation (watching people perform the work in-person), location (observing people at the actual location where work is performed), and teaming (interacting with people performing the work) [ 36 ]. To ascertain what the current process was we carried out Gemba walks with the OR procurement team (consisting of two staff members) to understand how they managed stock. This enabled us to develop a process flow map of how the OR stock was supplied, stored, collected, prepared, and monitored. Process flow mapping is the graphical representation with illustrative descriptions of how things get done. It facilitates the visualisation of the details of the process and guides decision-making. The process map can identify the major areas of strengths and weaknesses in the existing process, such that the contribution of individual steps in the process. Further, it helps to reduce the cycle times and defects in the process and enhances its productivity [ 43 ]. Our current state process map following Gemba illustrated that the OR procurement staff replenished stock twice a day at seven (7) and two (2). See Figure 2 .

Procurement OR Staff Process Flow Map for Stock Replenishment.

OR nurses gather and collate sterile supplies and materials for every surgical case for each individual consultant surgeon’s operative list. This process is known within the OR as ‘pulling for cases’. Additional Gemba walks were undertaken to observe the process for OR nurses pulling for cases in the main OR storeroom. OR nurses pulled the stock required for each case (listed by individual consultant surgeon preference card) the day before surgery. Over four days, we asked the nurses to document start and end times when pulling stock for cases. See Figure 3 .

OR Nursing Staff Process for Picking and Returning Stock.

2.3. Analyse

In reviewing the OR procurement staff process map we identified the process of the OR procurement staff traveling to the main stores ( Figure 2 ), searching for stock, and collecting it on a trolley. We identified two return journeys per day and 27 min per journey, a total of 56 min per day. We used an Ishikawa fishbone diagram ( Figure 4 ) to view cause and effect visually. Root causes for over-processing and stock waste included environmental issues (lack of structure in the Main store, overstocked trollies, the same product in multiple locations), lack of formal stock management over the redline, and lack of defined ownership. There was no scanning report for stock once it moved over the redline.

Fishbone for OR Stock Management.

2.4. Improve

1. In the improvement phase, we engaged with the key stakeholders from the OR to develop an agreed list and quantity of stock to be held in the pilot OR—number 6. These stakeholders included the clinical nurse manager, deputy clinical nurse manager, and staff nurses (n = 5) from OR 6 (the pilot site). It also included the OR department manager and the OR procurement team (n = 2). OR 6 was chosen as it had recently been refurbished and the improvement in stock management was seen by the OR staff as a way of looking at maximising the new layout of the OR suite. During this engagement, we highlighted the benefits of standardisation of the stock holding in terms of ease of locating stock, having a designated storage space for each item, and agreed minimum reorder points for each item so that supply shortages could be avoided. A stockholding list of products and quantities was agreed and the supply chain management stripped out all the stock, put in place new shelving to create dedicated space for each of the agreed products, and restocked to the agreed quantities.

2. To complement solution 1, Lean 5S was used to organise stock. A key component of our improvement was to organise inventory and facilitate the identification of OR supplies through visual management, specifically colour coding and labeling. The Lean process of 5S is a system to reduce waste and optimise productivity through maintaining an orderly workplace and using visual cues. It is a cyclical methodology of ‘Sort, Set in Order, Shine, Standardise and Sustain the Cycle’ [ 37 ]. Lean 5S made it easier and more efficient for staff to identify the products using colour coding and labeling. The stock was organised by discipline, for example, White = Orthopaedics, Blue = Urology and Gynaecology, Green = General Surgery, Yellow = Anaesthetics, and Red = Cardiac. The labeling font on the baskets was increased so that it was more easily identifiable.

3. The hospital procurement manager agreed to remove the collection process of stock from the main store from the OR procurement team that we had identified in the process map. They felt that the return on investment on this change of process would be that the 27 min identified per day per OR procurement team member (n = 2) could be used to better effect managing the stock across the OR redline and obviate out-of-date stock occurrences. The OR procurement team introduced ‘returns baskets’ to manage unused stock returns post-surgical case lists.

4. Our review of stock included a review of suture supplies. We reviewed the ‘as-is’ or current state process of suture storage and found sutures were stored in multiple locations within each of the operating theatres and also held on several different stock trollies across the OR redline. Engaging with the key stakeholders in OR it was agreed to establish one centralised suture storage area in the theatre main corridor. During the engagement, we referred back to our CTQ and VOC to highlight the benefits of centralised storage in addressing their needs to reduce stock hoarding and enable ease of access to stock for case preparation. It was agreed that we would work with the supplier representative to review the need for such a wide variety of suture codes to streamline the codes and reduce stock holding. Following the current state review the supplier representative estimated for our number of theatres, cases, and case-mix we should be holding approximately 408 boxes and 180 codes. The supplier representative engaged with the consultants to discuss their current suture preferences explained the similarity between codes and got consensus from consultants to move to a condensed list of codes.

5. The Red Line demarcating the sterile of clean areas was, with the agreement of the Infection Prevention and Control Team, moved to allow the main OR storeroom to become part of the sterile environment. This, with their agreement and endorsement, effectively moved the OR Procurement team into the sterile area and surgical scrubs. This was seen as being inclusive and person-centred and synergistic with the Lean philosophy of respect for person [ 1 , 2 ].

Identified and implemented solutions are summarised in Table 2 .

Identified and implemented solutions.

Having put in place the process improvements outlined above, we reanalysed the data examined in our Define and Measure phases to determine the real impact of the changes put in place and how they addressed the aims in our project charter.

3.1. Reduction in Stock Holding Value

One of the key issues highlighted in our data analysis was the lack of insight into stock handling over the OR red line. As discussed in our solutions above we analysed the stock holding in one of the eight OR suites and developed a proof of concept for roll out across the other seven OR suites. A full stocktake was carried out in the pilot OR and there was a total value of €221,052 worth of stock in that OR store, with the same product found in multiple locations (see Table 3 ).

Stocktake value in pilot OR pre-and post-intervention.

When the annual stocktake was repeated in December 2018 the stock holding was valued at €181,913, a 17.7% reduction.

Pre-intervention suture stock was stored in multiple locations within each OR. A full stocktake of all sutures across the eight OR suites was conducted to establish the quantity and range of product codes, a total of 1112 boxes and 247 codes was recorded (see Table 4 ).

Suture stock value.

Following the creation of centralised suture storage, there was an initial 33% reduction in stock.

A further stocktake was carried out six months post-intervention to analyse the impact of the improvement and stock holding had reduced again to 53% reduction from pre-improvement.

3.2. Reduction in OR Nursing Stock Prep Time

Pre-improvement, the pulling of consumable stock for cases took on average 4.52 min per case. The OR nurse could pull stock for up to 11 cases per surgical procedure list. Post-5S, where a colour-coded dedicated storage area for each discipline was created, we asked the nursing staff to repeat this exercise (see Figure 5 ). The average stock preparation time per case was reduced to 2.5 min per case, a 45% reduction in time utilised for this non-clinical task. Based on post-intervention VOC with OR nursing staff we established that this released time did not directly translate into the earlier finish of OR operative lists, due to the variation, complexity, and specific requirements in surgical specialties. However, they expressed that the released time was valuable to nurses in caring for peri-operative patients within the department.

Virtual Gemba Data.

3.3. Reduction in Value of Stock Going out of Date

Our initial goal was the reduction of stock going out of date by at least 50%. During the annual end-of-year stocktake in December 2017, it was revealed there was €27,000 worth of out-of-date stock located in the OR main storeroom; see Table 5 . Post-5S, there was a dedicated space for stock items, with clearer labeling and colour coding for ease of identifying products. The stocktake in December 2018 revealed €2231 worth of out-of-date stock, a reduction of 91.7%; see Table 5 .

Main storeroom end-of-year stocktakes.

4. Discussion

We established that over-processing of stock and stock hoarding occurs commonly in healthcare [ 30 ]. However, we also identified that having stock at POU is essential to ensure the quality of care [ 30 , 31 ]. There is therefore a cost to healthcare organisations both in monetary terms of over-purchasing stock/stock going out of date and also the human cost of over-processing of orders and in the case of our study nursing time spent on non-clinical tasks. This study was successful in both reducing stock going out of date, releasing time to care, and used Lean 5S, shown to be effective in clinical settings [ 44 ], to facilitate visual management and place stock at POU.

Early engagement with key stakeholders, particularly those on the ground carrying out the stock management tasks (both clinical and non-clinical) is critical to getting buy-in to any change. Following the DMAIC process enabled the team to present data-driven areas for potential improvements and highlight the impact these improvements made in their day-to-day tasks. We found that stakeholder engagement required a deep appreciation of the system [ 45 ], in which inquiries are conducted and improvements implemented, which was critical to the effective use of the LSS improvement approach in this project. These approaches enabled us to build team relationships among ourselves as an improvement team, enabled collaborative working with our stakeholders towards a shared vision and future, and provided a coherent and structured framework to identify and address the problems faced by the team. LSS tools provided an invaluable way to clarify and detail the problem at hand, and to pinpoint where solutions should be focused. Throughout the process, they served to keep the focus on what would add the greatest value to the team and the service. To avoid reducing our engagement with our stakeholders to a checklist exercise, we continuously drew on person-centred collaborative, inclusive, and participatory (CIP) principles [ 46 ] to inform our thinking about how we could work with colleagues to evaluate and improve our service.

The feedback gathered in the VOC pre-and post-implementation showed that while the new stock layout post-5S would “take getting used to”, staff could clearly see the benefits of a streamlined approach to storage. A key learning from our study is that early and frequent engagement with the stakeholders carrying out the day-to-day tasks was critical to success and highlights the benefit qualitative data-gathering exercises such as VOC can bring. Much of the literature we reviewed on stock management in clinical settings relied heavily on the quantitative data only [ 29 ]. Having said that, the quantitative data were very beneficial in highlighting to senior management the financial and time-saving benefits of the application of LSS in our OR department.

Having successfully implemented the proof of concept for stock management within OR suite 6, this has now been rolled out to the other seven ORs. This upscaling from one OR to all eight ORs was only possible by removing the task of the procurement staff traveling to the warehouse to pick and collect the stock, a time saving of 54 min per staff member. Being able to show the time saving of removing this task from procurement staff to utilise in the management of stock across the eight theatres created buy into the mindset of a change in practice rather than additional workload. A further success factor from this project is that it served as a platform for future improvement, with a 2nd generation project undertaken to further release nursing time resulting in a 55% decrease in overall nursing time spent in gathering and preparing materials for surgical cases. The overall OR nurse time saved in the process for surgical preparation per case was 16 min 45 s or 55%. Building on our own work, the number of storage locations (touchpoints) the OR nurse had to access to collect materials was reduced by 66% from a total of 98 touchpoints to 38 touchpoints. This 2nd generation project is currently in publication. The results of both studies indicate that LSS has provided a platform for continuous improvement and contributes to the literature on the use of LSS for process and quality improvement in hospitals [ 47 ]. This study is not without limitations. While the process improvement was evaluated and piloted within only one OR, the research findings offer opportunities for reflection, learning, and development for teams working within busy OR departments. Additionally, since the completion of this project, the pilot has had an incremental role out to the 7 other OR suites, and as discussed, there has been second generation LSS work within the OR on further improving stock management and releasing nursing time to care. We also acknowledge that this process improvement, although impacting on patients through releasing nursing time to care and access to stock, did not engage with surgical patients.

5. Conclusions

The results realised from our study demonstrate the benefits LSS principles can bring to stock management within the OR and indeed wider hospital settings. In particular, the application of the 5S approach to storage within our OR main stores and pilot OR highlights the efficiencies that can be achieved in terms of time savings for clinical staff and reduction in stock wastage. It also illustrates that although stock management may seem divorced from the role of the OR nurse, it has implications for nurses in the time they have to spend with their patients and on their nursing role. It demonstrates that LSS methodologies can be seen as more than what McNamara and Teeling [ 48 ] refer to as a decontextualised toolkit, and emphasises its use for engaging with all people involved in the complex processes inherent in healthcare across the entire health system.

Acknowledgments

The authors acknowledge staff members involved in this project; Mark Keogh, Eamon O’Riain, Keith Madden, Luke Keating, Kelly Marshall, Eileen Moriarty, Kate Fitzpatrick, James Byrne, Daragh Kavanagh, all procurement stores staff, and all OR nursing staff. We thank other Beacon Hospital Green Belts for their invaluable support and advice. We would also like to thank the UCD Mater Lean Academy and the Beacon Hospital.

Author Contributions

Conceptualisation, L.O., K.M. and J.O.; methodology, L.O., K.M., S.P.T. and J.O.; formal analysis, L.O., K.M. and J.O.; data curation, L.O., K.M. and J.O.; writing—original draft preparation, L.O., K.M. and S.P.T.; writing—review and editing S.P.T., M.W. and M.M.; visualisation, L.O., K.M. and J.O.; supervision, S.P.T. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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3PL Integration: Building an Expandable and Resilient Orchestration Solution

JUNE 14, 2023

Read More: Top 5 Challenges in WMS Implementation ] Real-life Case Studies of 3PL Integration To illustrate the benefits of outsourcing logistics services to a third-party provider and how a 3PL integration orchestration solution can improve a company’s logistics operations, let’s look at some real-world examples: Amazon.

The future of Manufacturing from an IT perspective

Infosys Supply Chain Management

MARCH 26, 2015

During my MBA days, I had the opportunity to learn a lot about Manufacturing, Operations, Supply Chain management and of course a lot of other courses in the form of lectures/ case studies /web/books.

Top 10 TikTokers to Take Off your Supply Chain

AUGUST 21, 2023

Through immersive case studies and real-world anecdotes, she kindles a revolution in supply chain practices, fostering a vibrant community of enthusiasts. Her educational content, brimming with impact, imparts newfound clarity to intricate concepts, equipping businesses with actionable strategies.

10 CEOs Reveal Favorite Operations Management Book

JULY 15, 2014

However, classic textbooks seem to have the same teaching approach, content outline and even case studies . Operations Management is a subject taught in business school anywhere in the world. The most important point is that even Bill Gate reads OM book.

Supply Chain Education: What Skills Do Your Staff Need?

Logistics Bureau

DECEMBER 3, 2017

SCLA includes case studies and examples of network-design problems and solutions, as well as tips and techniques for improving and optimising distribution networks. Continuous improvement methodologies such as Lean and Six Sigma . Warehouse and distribution centre process improvement. Inventory management.

Operations Management: CEOs Reveal 10 Favorite Books

How the Internet of Things Can Help You Lower Inventory Levels

JANUARY 28, 2018

They support key manufacturing philosophies like Lean, Theory of Constraints, and Six Sigma . Read the full case study . In a series of posts, we’re going to focus on IIoT projects that meet several criteria: They don’t require a major overhaul of processes or retooling the factory floor. Capital outlay is often minimal.

Supply Chain Management:Knitting Agile with Asset Maintenance.

SEPTEMBER 11, 2013

Case Studies . |. Visualizing the benefits of various new techniques such as Just in Time, Business Process Re-engineering, Kaizen, Lean, Six Sigma , ISO 9001, etc., Mobile Banking. Payments Treasury. Wealth Management. View all Infosys blogs. Supply Chain Management. Features & Opinions. |. Offerings. |.

7 Acronym-Based Methods for Effective Supply Chain

JUNE 20, 2013

Case Studies . Six Sigma practitioners have invented this acronym to help them remember easier. Supply Chain Case Study : Executives Guide. A Case Study . 7 Acronym-Based Methods for Effective Supply Chain. This article will show you 7 simple analysis methods based on easy-to-remember acronyms.

SCMDOJO’s Supply Chain and Operations Expert Marketplace

MAY 18, 2023

The core objective of this business case study is to provide a comprehensive context and background that sets the foundation for the launch of our new Supply Chain Expert Services Marketplace. Dr. Muddassir has received a PhD in Management Science from Lancaster University Management School.

VTech: A Story of a Supply Chain Leader

NOVEMBER 14, 2016

Through the next two months, I am focusing on writing and sharing case studies of success. I will write the case studies here, and share the dialogue with the supply chain leaders in our podcast series, Straight Talk with Supply Chain Insights. I have personally experienced the failure. ” This is my new mission.

The Industrial Internet of Things (IIoT) and the Modern Marketer

JULY 8, 2015

The Orbital ATK case study is a good example.) We draw from various tools – Lean Manufacturing, Theory of Constraints and Six Sigma – to drive a demand-driven change. Case studies provide a great vehicle for communicating service value. Where demand equals actual customer need.).

No Supply Chain Strategy? Here’s How to Develop One

JULY 18, 2022

We’d love to help your enterprise too, but perhaps you’d like to learn a little more about our approach and methods, so please check out our supply chain strategy services page for lots more detail and some case studies highlighting past projects we’ve completed for our clients. Lean supply chain practices.

Dr. Muddassir Ahmed on Innovation in Supply Chain Education

SEPTEMBER 24, 2020

I’ve always been very practical, which is why my PhD thesis was a research topic, not a case study . I have an engineering background; my first degree was a BE in Textile Engineering. I like to solve problems. I’ve worked in roles everywhere from the shop floor to demand planning and other leadership roles.

6 Sigma Supply Chain: The Brief Introduction for Non-Statisticians

JUNE 7, 2013

Case Studies . 6 Sigma Supply Chain: The Brief Introduction for Non-Statisticians. Even though there are so many articles about six sigma supply chain, most of them are all related to the application within certain functions in supply chain. Literature Review. They also incorporated SCOR model into this project.

TOC for Electric Utility industry.Part 1 - Infosys Blogs

JUNE 25, 2012

Case Studies . |. The objective of all other improvement initiatives like TPM, RCM, Lean or even Six Sigma is to improve your system efficiency thereby increasing the throughput. Mobile Banking. Payments Treasury. Wealth Management. View all Infosys blogs. Supply Chain Management. Features & Opinions. |. Offerings. |.

Why a Product-Centric Approach to Quality Matters

Arena Solutions

NOVEMBER 4, 2022

Angenette has more than 24 years of experience in quality assurance, quality control, Lean Six Sigma , and supply chain. And there’s been a case study done and a real-world example, the earthquake and tsunami in Japan in 2011. Our final panelist is Angenette Nordqvist. She is the Director of Quality Assurance at SomaLogic.

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Top Six Sigma Case Study 2024

Home Blog Quality Top Six Sigma Case Study 2024

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.

Enroll in the  Lean Six Sigma Green Belt certification online training to advance your career! Gain expertise in process improvement and organizational transformation with expert-led training and real-world case studies. Start now to become a certified professional in quality management.

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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Everything About Process Decision Program Chart (PDPC)

March 29th, 2024

To detect and mitigate potential problems in their processes, organizations can use Process Decision Program Chart (PDPC).

PDPC enhances process reliability, improves quality, and prevents costly mistakes by systematically mapping out tasks, anticipating possible failures, and developing countermeasures.

PDPC is an approach derived from Six Sigma that has proven to be universally applicable to a wide range of industries, including manufacturing, healthcare, finance, and information technology.

It has become essential for quality professionals, process engineers, and project managers to master the PDPC methodology in the pursuit of operational excellence and continuous improvement .

Key Highlights

• Understand the purpose and importance of the Process Decision Program Chart (PDPC) in process improvement and quality assurance
• Learn the step-by-step methodology of constructing a PDPC, including process mapping , risk identification, and countermeasure development
• Explore how PDPC can be integrated with other quality improvement frameworks like Six Sigma and Lean
• Discover best practices for implementing PDPC, such as stakeholder engagement, change management , and continuous monitoring
• Analyze a real-world case study on applying PDPC to a chronic illness management program

What is the Process Decision Program Chart (PDPC)?

At its core, the PDPC is designed to provide a structured framework for process improvement and quality assurance . By mapping out the key steps or tasks involved in a process, the PDPC encourages teams to brainstorm potential problems that could derail progress.

For each identified problem, the PDPC then prompts the development of specific countermeasures or solutions to prevent the problem from occurring or minimize its impact.

The applications of the PDPC span a wide range of industries, from manufacturing and supply chain management to healthcare and software development. Wherever there are complex processes that require careful planning and risk mitigation, the PDPC can be a valuable tool.

For example, in the healthcare sector, PDPCs are often used to enhance patient safety and improve the quality of chronic illness management programs.

In the manufacturing realm, PDPCs help organizations identify and address potential defects or disruptions in their production workflows.

Ultimately, the PDPC is a versatile and proven methodology that enables organizations to take a proactive, data-driven approach to process improvement and quality assurance.

By systematically identifying and addressing potential problems, teams can enhance their overall process reliability, reduce costly errors or delays, and drive continuous improvement throughout the organization.

Understanding the Process Decision Program Chart (PDPC) Methodology

The core of the Process Decision Program Chart (PDPC) methodology involves thoroughly examining the process or task at hand to identify potential problems and develop corresponding countermeasures.

This structured approach helps organizations proactively address risks and improve overall process reliability.

Process Mapping and Task Analysis

The first step in creating a PDPC is to map out the process or task in detail. This involves breaking down the process into individual steps or task, and clearly defining the objectives, inputs, outputs, and key activities for each.

Process mapping provides a comprehensive visual representation of the workflow, which serves as the foundation for the PDPC.

Brainstorming Potential Problems and Risks with Process Decision Program Chart

With the process clearly defined, the next step is to brainstorm all the potential problems or risks that could occur at each step. This involves tapping into the collective knowledge and experience of the team to identify both obvious and more obscure issues that could arise.

Common techniques used in this phase include root cause analysis , failure mode and effects analysis (FMEA), and structured brainstorming.

Developing Countermeasures and Risk Mitigation Strategies

For each potential problem identified, the team must then develop appropriate countermeasures or risk mitigation strategies.

These could include preventive actions to stop the problem from occurring, detective actions to identify the problem early, or corrective actions to address the problem if it does occur.

The goal is to create a comprehensive set of measures that can effectively address the full range of potential risks.

Criticality Assessment and Prioritization

Once the potential problems and countermeasures have been identified, the team should assess the criticality of each issue.

Factors to consider include the likelihood of occurrence, the severity of the impact, and the detectability of the problem.

This criticality assessment allows the team to prioritize the most significant risks and focus their efforts on developing the most impactful countermeasures.

By thoroughly mapping the process, brainstorming potential problems, developing countermeasures, and assessing criticality, organizations can build a robust PDPC that serves as a valuable tool for proactive risk management and process improvement .

Constructing a Process Decision Program Chart

The first step in creating a Process Decision Program Chart (PDPC) is to clearly define the objective and main activities that need to be addressed. This involves carefully mapping out the process or workflow that you want to analyze and improve. 

Once the objective and key activities are defined, the next step is to identify potential problems that could occur for each task or step in the process. This is where the power of brainstorming and process mapping comes into play.

By thoroughly examining each activity, you can uncover a wide range of potential issues, from equipment failures and resource constraints to human errors and external disruptions.

After identifying the potential problems, the next critical step is to develop countermeasures or actions that can be taken to mitigate those risks.

For each potential problem, the PDPC requires you to think through potential solutions, backup plans, and contingency measures. These countermeasures should aim to prevent the problem from occurring in the first place, or minimize the impact if it does happen.

Finally, the PDPC calls for evaluating the practicality and feasibility of the proposed countermeasures. This involves assessing factors such as cost, complexity, lead time, and ease of implementation.

The goal is to identify the most effective and realistic countermeasures that can be effectively deployed to address the identified risks.

By systematically working through this process of defining objectives, identifying potential problems, developing countermeasures, and evaluating their practicality, organizations can create a comprehensive PDPC that serves as a roadmap for anticipating and addressing process-related risks and challenges.

Implementing PDPC in Process Improvement Initiatives

The Process Decision Program Chart (PDPC) is a powerful tool, but it is most effective when integrated with other quality improvement frameworks and methodologies.

For example, PDPC can be seamlessly incorporated into Six Sigma projects, where it can help identify and mitigate potential problems during the Define, Measure, Analyze, Improve, and Control (DMAIC) phases.

Similarly, PDPC can be used in conjunction with Lean principles to proactively address waste and variability in processes .

By aligning PDPC with established quality frameworks, organizations can leverage synergies and create a more comprehensive approach to process improvement.

This holistic integration allows teams to address both tactical and strategic considerations, ensuring that potential problems are identified and addressed at multiple levels of the organization.

Stakeholder Engagement and Change Management

Successful implementation of PDPC requires active stakeholder engagement and effective change management. PDPC is not just a technical exercise; it involves key stakeholders from across the organization, including process owners, subject matter experts, and end-users.

Engaging these stakeholders throughout the PDPC process ensures that their perspectives and concerns are incorporated, leading to more robust and practical countermeasures.

Change management is also crucial when implementing PDPC, as the process may require adjustments to existing workflows, roles, and responsibilities.

By proactively addressing the human and organizational aspects of change, leaders can facilitate the adoption of PDPC and ensure that the benefits are realized across the organization.

Continuous Monitoring and Process Optimization

PDPC is not a one-time activity; it requires continuous monitoring and process optimization to ensure its effectiveness over time. As processes evolve and new challenges arise, the PDPC should be regularly reviewed and updated to reflect these changes.

This ongoing evaluation and refinement help organizations stay agile and responsive to emerging risks and opportunities.

By continuously monitoring the implementation of PDPC and its associated countermeasures, organizations can identify areas for further optimization, make adjustments as needed, and capture valuable lessons learned.

This iterative approach to process improvement enables organizations to build a culture of continuous learning and adaptation, ultimately enhancing their overall organizational agility.

Organizational Agility with Process Decision Program Chart

The insights and experiences gained through PDPC implementation can serve as a valuable source of organizational learning.

By documenting and sharing the lessons learned, organizations can build a knowledge base that informs future process improvement initiatives.

This institutional memory can help teams anticipate and address potential problems more effectively, fostering a culture of continuous improvement .

Moreover, the PDPC process itself can contribute to the development of organizational agility. By proactively identifying and mitigating risks, teams become better equipped to respond to unexpected challenges and adapt to changing market conditions.

This agility allows organizations to stay resilient and competitive in an ever-evolving business landscape.

PDPC Case Study: Chronic Illness Management Program

Chronic illnesses, such as diabetes, heart disease, and asthma, require comprehensive and coordinated care to manage symptoms, prevent complications, and improve patient outcomes.

When designing a new chronic illness management program, the Process Decision Program Chart (PDPC) can be a valuable tool to identify potential problems and develop effective countermeasures.

By applying the PDPC methodology, the program planners can map out the key processes involved in the chronic illness management program, from patient intake and assessment to ongoing care coordination and follow-up.

This process mapping exercise helps uncover potential pain points, bottlenecks, and risks that could hinder the program’s success.

Identifying Potential Problems and Developing Countermeasures with Process Decision Program Chart (PDPC)

Once the program’s key processes are mapped out, the PDPC team can engage in a thorough brainstorming session to identify potential problems that could arise at each stage.

This could include issues such as delayed patient appointments, lack of patient engagement, inadequate staff training, communication breakdowns, and insufficient data tracking and reporting.

For each potential problem identified, the team can then develop corresponding countermeasures or mitigating actions.

These countermeasures might include implementing a robust patient scheduling system, designing engaging patient education materials, providing comprehensive staff training on chronic illness management, establishing clear communication protocols, and implementing a comprehensive data management and reporting system.

Ensuring Patient-Centered Care and Goal Setting

At the heart of a successful chronic illness management program is a focus on patient-centered care. The PDPC process can help ensure that the program is designed with the patient’s needs, preferences, and goals in mind.

By involving patients and their caregivers in the PDPC process, the program planners can gain valuable insights into the challenges and barriers that patients face, and then develop targeted countermeasures to address these issues.

Additionally, the PDPC process can facilitate the development of personalized care plans and goal-setting mechanisms.

By collaborating with patients to identify their specific health goals and then aligning the program’s processes and countermeasures to support those goals, the chronic illness management program can be tailored to meet the unique needs of each patient.

Addressing Staff Training and Organizational Change

Implementing a new chronic illness management program often requires significant organizational change , including the adoption of new processes, technologies, and roles.

The PDPC process can help address the challenges associated with this change by identifying potential problems related to staff training, communication, and resistance to change.

For example, the PDPC team may identify the need for comprehensive training on chronic illness management best practices, motivational interviewing techniques, and data-driven decision-making.

Countermeasures could include the development of training programs, the creation of job aids and reference materials, and the implementation of ongoing coaching and support for staff.

Additionally, the PDPC process can help the program planners anticipate and address potential organizational resistance to change.

By involving key stakeholders, such as healthcare providers, administrators, and patient advocates, in the PDPC process, the program can be designed in a way that aligns with the organization’s culture, values, and strategic priorities, thereby increasing the likelihood of successful adoption and implementation.

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