Lean Six Sigma is acknowledged as a proven method for identifying problems, finding their root causes and developing solutions. But what if you could make the process better?
That’s the question proponents of artificial intelligence are asking. The use of AI and machine learning has become more widespread across all industries, particularly in the areas of data collection and analysis. Machine learning, which refers to the ability of machines to “learn” as they do a task without further programming, is most often associated with taking on important but routine tasks.
Those who use Lean believe AI can apply to the methodology. It’s already getting put to use in areas such as improving Voice of Customer.
At the 2021 Lean Six Sigma World Conference, Adam Gilley, a financial consultant with Intuit in Orlando, Fla., will address AI in Lean Six Sigma. In an article about the presentation, Gilley wrote that AI is set to impact business in many important ways
“The future is brightest for those who evolve with trends rather than chase after them,” Gilley wrote.
The use of AI in Lean projects also took centerstage at the 2020 Engineering Lean & Six Sigma Conference. Presentations focused on how AI can quickly find patterns in complex systems and data that traditional analytics might miss.
The Potential of AI and Machine Learning
So much is written about AI and machine learning that it’s easy to become lost in a sea of opinions about their potential.
At the most basic level, AI and machine learning provide systems that can take on many of the routine tasks now handled by humans. This has applications in almost all phases of an operation. Examples of the application of AI include fraud detection in banking, online customer support in retail and cybersecurity.
Gilley writes that AI already makes a difference in handling routine data collection tasks, freeing up employees for more creative endeavors. He also notes AI has led to much faster “speed to innovation” because of the ability to extract valuable insights quickly from large data sets.
For most businesses, it’s a question of when, not if, they will adapt AI in some phases of the operation. But how will that play out with Lean Six Sigma?
AI Can “Turbocharge” Lean Projects
In a column for McGraw Hill, Michael George, CEO of AI Technologies, said that the use of AI combined with Lean is necessary “to keep American manufacturing and engineering competitive in the world market.” He wrote that AI can “turbocharge” Lean.
During the data collection and analysis portion of projects, George argued AI can detect common patterns in non-manufacturing applications such as product development and project management. “AI yields greater reduction of cost and cycle time than was possible with only Lean Six Sigma to attain competitive advantage,” he wrote.
AI and machine learning particularly come into play in complex situations. In an example published on LinkedIn, machine learning is needed when there are a large number of key process parameters, many unknown parameters or if parameters change over time. Again, it’s the ability to quickly analyze vast amounts of complex data that makes AI essential in these instances.
In the example from LinkedIn, a pharmaceutical company that distributes medication to treat chronic diseases wanted to predict which chronic disease patients were most likely to stop taking medication. By using AI, the company was able to successfully find warning signs in vast patient data sets and improve patient adherence to their medication-taking schedule.
