A key takeaway from each year's Engineering Lean & Six Sigma Conference is how revelations coming down the pike will affect future research, your industry sector, and your job.

The following track descriptions provide additional details about the topics and resources that attendees will be able to explore during the  Lean Six Sigma and Data Science Conference.

Track Descriptions

Process Improvement – Process improvement initiatives rely on fully integrated systems for communication, waste reduction, responsiveness, as well as effective inventory management, etc. This sub-track invites research that explores innovative strategies for improving existing processes that utilize approaches such as modeling and simulation, effective performance measurement and evaluation, benchmarking, and enhanced value change management.

Creating and Sustaining a Lean Six Sigma Culture – A 2007 Industry Week survey suggested that over 70 percent of Lean implementation attempts result in failure. This failure is often attributed to focus solely on tool implementation at the expense of cultural change. This sub-track invites research that explores strategies for introducing and maintaining a culture of Lean, Six Sigma, and/or continuous improvement. Consideration includes, but is not limited to, the integration of cross-disciplinary strategies for change management, conceptualization and learning, behavioral, and related theories for socio-technical systems management.
Healthcare – Healthcare organizations are not new to quality and cost-control initiatives, but powerful Lean Six Sigma tools are, in most organizations, only beginning to be applied. The purpose of this sub-track is to share the fundamental challenges, success factors, and benefits in the implementation of Lean Six Sigma tools and techniques in the context of healthcare.

Manufacturing / product design & development – This sub-track showcases how Lean Six Sigma or Design for Lean Six Sigma are utilized in the manufacturing world to incorporate the voice of the customer (value maximization) and eliminate wastes of time, money, materials, energy, and other resources, as well as to eliminate waste due to variation and rework. Talks in this track will focus on waste reduction, value specification and optimization, as well as flow optimization and continuous improvement, and real-world examples of implementations by those directly involved.

Logistics and Supply Chains – Today's Logistics and Supply Chain industry suffers from inefficiencies in freight movement, materials management, inventory control, quality sustainment, information management, and many other areas. Lean Six Sigma application in the supply chain sector or Retail (which is one of the most competitive of businesses in the U.S.) has the potential to revolutionize the industry. Experts from various segments of the supply chain or retail sector are invited to share their successful lean Six Sigma implementation stories and know-how with conference participants.

Service Systems, Government and Nonprofit – Service Systems (such as food service, technical service, banking service, telecommunication service, repair services & other business services) and Governments at all levels are under intense pressure to use resources more efficiently, and they have both been adopting Lean Six Sigma concepts to improve their bottom line. Nonprofit organizations face the same challenges as the for-profit sector regarding quality and productivity, but the nonprofit world has constraints that are not present in the general business world. This sub-track will include case studies and lessons learned in services, government and nonprofit organizations that supports collaborative discussions and feedback from different perspectives among all practitioners.

Lean Six Sigma and Data Science in the Age of Big Data – With different phases of DMAIC, data is critical for finding solutions. Thanks to their flexible nature, Lean and Six Sigma methodologies allow organizations and practitioners to combine data science with other tools in order to yield even better results. In this sub-track, we invite presenters to share case studies and lessons learned from projects where they included the use of Data. This can include types of data science used in the measure and analyze phases, along with dashboards used in the control phase and other data science ideas that can be incorporated in lean and six sigma.

Artificial Intelligence and Lean Six Sigma – The use of machine learning (ML) and Artificial Intelligence (AI) is becoming widespread across all industries and for most organizations it’s a question of when, not if, they will adopt AI in their processes . Practitioners believe that AI can be leveraged to increase the value of Lean Six Sigma. This track will showcase how AI and ML can be used in Lean Sigma projects to provide advanced solutions to complex problems. 

Emerging Topics & the Future of Lean Six Sigma – The future of continuous improvement methodologies has often been questioned; current methodologies may be losing inertia within academia and industry. This trend could be an opportunity for promoting innovation within this field. This sub-track welcomes research focused on creating new ideas for the development of successful tools and methods including the use of Cloud computing, Internet of Things (IoT), blockchains, business automation, etc. in lean Six Sigma projects.

Lean Six Sigma / Data Science Training & Education – The next generation of workers and managers are increasingly being exposed to Lean Six Sigma and Data Science. In many ways, education professionals in industry must build a bridge between learning in the "gemba" (where the work takes place) and the classroom. The use of seminars, workshops, and continuing education are key elements for building a learning organization. In this sub-track, we invite presenters to share their unique approach to supporting Lean Six Sigma training, including the use of games and simulations to advance the education process, as well as applications of Lean Six Sigma within academic organizations.