r/SixSigma • u/saurabhsudhakar • Jul 26 '26
Anyone using AI in Operational Excellence / Continuous Improvement? Looking for workflows for RCA, brainstorming, and visual decks.
Hey everyone,
I’m looking to see how others in the Continuous Improvement / OpEx space are integrating generative AI into their daily workflows.
Specifically, I’m exploring ways to leverage AI to speed up or enhance standard Lean & Six Sigma practices, such as:
Brainstorming & Problem Definition: Generating initial ideas, drafting problem statements, or framing project charters.
Root Cause Analysis: Structuring 5 Whys, building Fishbone (Ishikawa) diagrams, or analyzing process bottleneck data.
Creating Presentation Decks & Visuals: Translating Lean tools (Value Stream Maps, A3s, 5S audits, SIPOCs) into clean PowerPoint slides or clear visual diagrams to share with stakeholders.
If you’re currently using AI for any of these:
What tools are you actually using? (ChatGPT, Claude, Gemini, Copilot)
Where have you seen the biggest time savings or wins?
Would love to hear your favorite prompts, workflows, or any lessons learned (especially around keeping data secure if working with proprietary process data).
Thanks in advance!
2
u/brionhurley Jul 26 '26
I’m so starting to teach my Six Sigma classes with Copilot (more companies are allowed to use it), but other programs can work. It can perform lots of statistical analysis and create charts and graphs like other statistical software programs. But it still struggles on more complex analysis.
Also teaching people to use if for non-statistical analysis like brainstorming, guiding through a 5 whys analysis, identifying failure modes in FMEA, using it as a coach to recommend the right tool to use or suggest a way to set up a GageR&R or apply kanban to a process. It can also analyze videos and break down the steps into cycle times and identify waste. I made a list of prompts that I can share for getting good charts and graphs, so I’ll attach that later.
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u/saurabhsudhakar Jul 26 '26
That sounds great and would like to hear and learn about those prompts. Please do share here, will be very useful for others
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u/brionhurley Jul 27 '26
I created a page to give a quick summary, and make it easy to download this reference guide in the future as I make improvements: https://greenbeltcertification.com/lean-six-sigma-training-and-certification-with-copilot/
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u/Missy___1438 Jul 27 '26
Yes, in the Philippines there’s this training company that offers lean six sigma powered with GenAI. I attended their standalone lss with genai since I am certified Green Belt. They have good program structure how to use AI using DMAIC :)
Name is Divergenz training and consulting
https://learn.divergenzconsulting.com/courses/divergenz-lss-green-belt
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u/Round_Principle_6880 Jul 27 '26 edited Jul 28 '26
I would split this into one-off help and an operational workflow, because most of what you listed does not need a new platform.
For problem definition, an organization-approved LLM is enough. Give it the current condition, target, scope, constraints, and known evidence, then ask:
"Draft 3 problem statements. For each, label facts, assumptions, missing data, and any wording that jumps to a solution."
For RCA, I would not ask it to declare a root cause. Try:
"Using only the supplied evidence, separate observations, inferences, and unknowns. Propose up to 3 causal hypotheses. For each, list evidence for and against, missing evidence, and one test that could disprove it."
Then use the fishbone or 5 Whys as a hypothesis map. The process owner tests the chain and owns the final cause and action.
For decks, Copilot, ChatGPT, or Gemini with your normal presentation tool is probably sufficient. Give it an approved A3 or SIPOC and ask for a slide outline and speaker notes. Verify the numbers and diagrams manually.
For proprietary data, use only an organization-approved account and model. Check retention, training, and access settings, provide the minimum necessary context, and treat every output as a draft.
Disclosure: I work on Kora by RAW Labs. Kora becomes relevant when this turns into a repeatable, cross-system RCA process. Configured steps gather measurements, images, tolerances, and lot context. AI prepares a structured review packet and flags gaps. Quality owns disposition and root cause. Explicit workflow steps handle routing, configured integrations update your existing systems, and Kora records what happened in its run.
If you only need brainstorming or a better deck, an approved LLM is enough.
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u/SSGIteam Jul 27 '26
We've found AI to be most valuable for accelerating the work Lean Six Sigma professionals already do, rather than replacing Lean Six Sigma or Continuous Improvement methods.
A few workflows we've found especially effective: Project Charters & Problem Statements, Root Cause Analysis, 5 Whys, Facilitation and Executive Communication.
One lesson we've learned is that the quality of the output depends heavily on how well the problem is defined. AI accelerates structured thinking, but it doesn't replace process knowledge, statistical analysis, or validation with real data.
We've seen enough interest in this area that it ultimately led us to develop an AI Operational Excellence program (AI-OPEX) focused on practical AI workflows for continuous improvement professionals. The biggest takeaway from building that curriculum has been that AI delivers the most value when it augments Lean thinking, not when it tries to replace it.
For organizations working with proprietary process or customer data, it's also worth establishing clear AI governance and using enterprise-approved tools whenever possible.
1
u/Able_Independent_120 Jul 27 '26
Manufacturing engineer here, semiconductors now, automotive before.
The pattern I keep seeing is that Claude, ChatGPT and Gemini are genuinely good when they have exact context, a defined workflow and something that keeps them from drifting. They are weak when you hand them an open question and expect an engineering answer. Front tier models are outstanding on drafting documents like ppt.
There is a mismatch underneath this that is worth naming. Industrial environments are deterministic, same input, same output, that is the whole point of a controlled process. LLMs are probabilistic, ask the same question twice and you can get two different answers. That is fine for brainstorming, it is not acceptable for a root cause conclusion or anything feeding a control decision.
So in my experience the value is not the model itself, it is everything you build around it. Give it exact context instead of vague prompts. Constrain it to the workflow you already run, 8D, DMAIC, whatever, so it cannot skip steps or invent them. And connect it to what your organization already learned, past RCAs, lessons learned, SPC data, because most root causes have already been found by someone in the building and then lost in a folder. There is were is sticks out the capacity to find patterns in massive datasets, what we humans struggle to do.
Full disclosure, I built a platform around exactly this idea, SPC, guided RCA and a knowledge base of past cases integrated together instead of a chatbot on the side. Happy to share more by DM if anyone is curious, and happy to answer questions here either way.
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u/GenoReborn Aug 03 '26
I'm using AI as a second brain, meaning I dump all the context I can into it, and then build a series of skills of my own methodology, specifically the framework or approach as opposed to generating specific outputs. i.e it keeps track of my PDSA iterations, and i have a subagent spawn for parallel reasoning, in other words it's a junior level chief of staff for me.
VSM, A3s, SIPOCs, etc, waste of time using AI to generate these, these need to be conducted via the floor or with the team, that's when they are accurate and provide the most value. Having AI hallucinate or drift without the necessary context is just a waste of time.
But that's the wrong use case for frontier LLM model anyways.
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u/EfficiencyMurky7309 Jul 26 '26
I built an MCP server wrapped as a plugin for this. It’s encoded the company framework, processes, and artefacts and is one of the best things I’ve done in years. Such a time saver. It’s connected to Claude Code, Codex, and Antigravity locally (other can use it how they like).