The Use of AI In Process Improvement Will Increase in the Coming Years

One hallmark of businesses in all industries is the continuous focus on process improvement.  Traditionally led by human experts, the quest to improve efficiency and better serve customers and clients is undergoing a radical transformation, thanks to the rising prominence of artificial intelligence (AI) tools, particularly generative AI.

These tools, faster and more cost-effective than their human counterparts, are ushering in a new era of innovation and efficiency. At least to a point.

The Harvard Business Review (HBR) reported that AI is already used in some areas of process improvement. The use of technology - including generative AI - will grow. That’s because it can perform tasks faster and much less expensively than humans alone. But, HBR added, “It will never fully replace people, which poses management challenges.”

Can AI Support Lean Six Sigma?

Deciding how AI will support Lean Six Sigma remains an ongoing process. One area where Lean Six Sigma practitioners are placing focus is on using AI to better analyze and interpret data. This supports a structured approach to identifying operational problems, devising remedies and ensuring those improvements continue.

While process improvement requires the contextual awareness and creativity humans bring to projects, AI offers support in helping people “correctly interpret external data, learn from such data, and use those learnings to achieve specific goals and tasks; such as “problem-solving” and “learning” through flexible adaptation,” according to a report from the Institute of Industrial and Systems Engineers (IISE).

The IISE experts write that AI will accelerate Lean Six Sigma projects in “a number of profound and novel ways.” AI systems, for example, can help Black Belts and Green Belts quickly get a deeper understanding of the relationship between dependent and independent variables within a process. IISE also notes the ability of Natural Language Process (NLP) systems to help businesses draw more insights from unstructured data that will give them more insight into the Voice of Customer. 

“In the very near future, the role of the LSS Green Belt and Black Belt will merge with that of the data scientist, the result of which will be healthier businesses with happier customers,” IISE wrote.

AI's Integration into Process Improvement

AI integration into process improvement is not just a future possibility but already a reality. Companies like Johnson & Johnson and Voya Financial exemplify this shift, leveraging AI in their initiatives to automate processes and enhance productivity, resulting in substantial cost savings, according to HBR.

To show the potential of AI, HBR provides a look at its use in one of the most popular Lean Six Sigma tools, DMAIC, an acronym for Define, Measure, Analyze, Improve and Control. 

Define: AI excels at understanding processes by analyzing large data sets to find common patterns. This is exemplified by companies such as Siemens, BMW, and Merck employing process mining for broad-scale improvements.

Measure: AI's ability to measure process performance using various technologies like IoT devices, barcodes and visual AI systems brings unparalleled accuracy. High-volume industries, such as food production, benefit from AI's capability to inspect every item on a production line efficiently.

Analyze: AI's computational prowess allows for the extraction of patterns more efficiently than traditional methods. It reduces false positives and accelerates the identification of root causes, supporting methods like the "Five Whys."

Improve: AI systems outshine traditional brainstorming by swiftly identifying "best performance" configurations. AI also allows for customization based on product and context.

Control: AI's real-time monitoring capabilities, identifying outliers. HBR wrote that this is exemplified by Danske Bank's significant improvement in fraud detection using AI-based outlier identification.

Future Possibilities with AI

As generative AI systems, such as those that power ChatGPT and Wolfram Alpha, become more sophisticated, Lean Six Sigma practitioners will likely increasingly use them to execute more complex task automation. This could include everything from writing reports and presentations to training systems to provide better data analysis.

The concern among Lean Six Sigma experts is that AI could pose a threat to their positions. However, much like generative AI’s limitations in writing, it also still requires a human to provide complete context and creativity needed to solve complex challenges. Black Belts and Green Belts will need to adapt by learning how to use AI to support Lean Six Sigma projects. They also will need to understand AI’s limitations.

One Black Belt had a conversation with ChatGPT about the future of AI in Lean Six Sigma, reporting that the generative AI concluded that “Lean Six Sigma Black Belts bring a unique set of skills, experience, and expertise to organizations, and their roles are more likely to evolve in conjunction with AI technologies rather than be replaced by them.”

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