AI in the daily work
of your teams
A workshop for manufacturing companies. We teach teams to analyze data from ERP, MES and spreadsheets, and to build their own tools and simple applications. On your data, for your processes.
Let’s start with the math
This is not a technology problem. The tools are already here — in most companies, nobody has taught people how to use them. It’s a competence gap, not a software gap.
What we establish before we enter the room
An “AI training” without this stage ends in enthusiasm that fades within a week. The diagnosis decides whether the workshop changes anything.
- Where the time goes. Which reports, summaries and presentations are built by hand, how often, and how many people are involved.
- What data you really have. What can be pulled from ERP and MES, in what form and how often. What lives only in spreadsheets.
- Who will actually use it. The participants’ level, their daily tasks, and the constraints on the IT and data security side.
- What the outcome should be. Specific tools to be built during the workshop, agreed with you before we start.
Four skills
Multi-source data analysis
A dozen files from ERP, MES and spreadsheets at once — one coherent analysis. Plus a way to check whether the result is true.
Projects and repeatability
A project where the context and calculation logic stay written down. The knowledge stays in the company, not in one person’s head.
Your own tools
Dashboards, calculators, checklists, report generators. Excel and PowerPoint get done many times faster.
Simple applications
Tools that work on the shop floor and in the office from tomorrow. No developer and no deployment project.
We work with Claude and ChatGPT — tools you already have or can have within a week. No system rollout, no integrations, no IT budget to get started.
Data and tools
The most hands-on part of the workshop. This is where every participant builds something to take back to their own department.
- Excel spreadsheets. With working formulas, pivot tables and validation — not just numbers pasted into a grid.
- Combining sources. Exports from ERP, MES and spreadsheets pulled into one coherent analysis, with a check that the totals add up.
- Dashboards. With file upload and result download, usable by the whole team without asking the author for help.
- Calculators and tools. For calculations you repeat every week or every shift — built once, they keep working on their own.
- Presentations. From raw data to finished slides, without copy-pasting charts and formatting late into the night.
A photo instead of retyping
Most data in a factory is still born on paper. This module teaches how to move it into a spreadsheet without retyping and without buying anything.
- A photo of a board or a sheet of paper. Notes from a workshop or a meeting turned into a spreadsheet with proper columns, ready for sorting and calculating.
- Shop-floor photos as a data source. Labels, meter readings, control cards, forms filled in by hand during the shift.
- Printouts and scans. Paper documents turned into numbers that can be compiled and compared across periods.
- A sketch on paper. A hand drawing turned into a presentation, a spreadsheet or a working tool — within a single meeting.
- Digitizing documentation. A binder becomes a database you can search. No retyping and no hiring someone to do the retyping.
The team’s everyday work
The things that eat time every single week and that nobody counts, because “it only takes a minute”. This is where you reclaim the most hours with the least effort.
- Meeting minutes. Decisions, task owners and deadlines, sent out before people leave the room. A list of commitments, not a summary of the discussion.
- Project sheets. Scope, milestones, risks and status in one place, updated without copy-pasting between files.
- A3. Problem, root cause analysis, action plan and metrics on a single page — in the format you already know from Lean.
- Brainstorming. Generating options and structuring what came up in the meeting, instead of a board of sticky notes nobody ever transcribes.
- Action tracking. What happened to that task from last quarter, who was supposed to close it and why it’s stuck.
Not just “faster”. Exactly this much
Four reports that take half a day or a full day today. Below, the time they take after the workshop — from typing the prompt to the finished file.
- 70 sLine downtime report Pareto of causes, ranking, table of shift events.
- 120 sWeekly attendance report Shift grid, staffing gaps, a summary for the manager.
- 40 sSkills matrix update Levels for the whole team, gaps visible at a glance.
- 140 sOvertime report — 250 people, one month A named list, department totals, limit overruns.
These are not sales-deck numbers — this is how long generating a report takes once the data is prepared and the project is configured. We teach the configuration in module 01 and the data preparation in module 02.
We shape the program around roles
The same workshop, different applications. Everyone works on tasks from their own area.
Production managers
Shift reports, downtime analysis, OEE, preparing data for management meetings.
Engineers and technologists
Scrap analysis, measurement data, technical documentation, process variant comparisons.
CI and quality managers
Pareto, root cause analysis, corrective action tracking, 8D and audit reports.
HR, logistics, finance
Staffing and absence, delivery planning, inventory levels, cost summaries.
Adam Fieduk
25+ years of operations management in international manufacturing plants. Greenfields, optimization, Lean transformations — across nine countries and eight industry sectors.
For the past two years he has been actively deploying AI in manufacturing companies across Europe — as an expert collaborating with a technology startup that builds digital products for industry. Creator of the LEAI concept: Lean, TOC and OPEX combined with AI.
A consultant and transformation leader. Not a lecturer — someone who has laid out lines himself, fought bottlenecks and built those reports late at night.