Four problem areas in mechanical engineering
Purchasing, sales, material planning and controlling, where scattered Excel islands and SAP exports cost the most.
Excel data that calculates with AI instead of guessing
A practical guide for purchasing, sales, material planning and controlling in mechanical and plant engineering. It describes the four biggest problem areas, why Excel and generic AI assistants fail on large tables and the path in four steps from file to verified analysis.
Request the guide 13 pages, practical guide, version 2.1, June 2026
What the guide covers
German mechanical and plant engineering is under efficiency pressure in 2026. According to the PwC mechanical engineering barometer Q4/2025, 83 percent name cost pressure as the biggest obstacle to growth. According to VDMA 2025, only 7 percent have scaled generative AI across the company. The reason is rarely the technology but the data. Knowledge sits in Excel islands, SAP exports, quote folders and bills of materials, fragmented and impossible to analyse across files.
The guide describes the problem areas that weigh most heavily on purchasing, sales, material planning and controlling, and a concrete way forward. The existing Excel files become a verified data model that a person confirms. Calculated rather than estimated, with a source.
Figures from the guide
- 83%
- of mechanical engineering companies name cost pressure as the biggest obstacle to growth in 2026according to PwC mechanical engineering barometer Q4/2025
- 7%
- have scaled generative AI across the companyaccording to VDMA and Strategy& GenAI study 2025
Chapters
- Industry situation, efficiency pressure instead of a fresh start
- The problem areas in purchasing, sales, material planning and controlling
- Why Excel and generic AI assistants fail on large tables
- The better way, from Excel file to verified analysis in four steps
- What it delivers, measurable contributions to savings
- Next step and appendix on tabular hallucinations
Who the guide is for
For purchasing, sales, material planning and controlling in mechanical and plant engineering, where knowledge sits in Excel files, SAP exports, quote folders and bills of materials.
The path in four steps
From scattered files to a consolidated, verified data model, confirmed by a person.
Protecting calculation data
Why large tables with calculations do not belong in a generic cloud AI.
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