Forklift carriages are awkward to cost. They are heavy welded structures with up to 15 individual components, lifting capacities from a few hundred kilograms to 8 tonnes, and a documentation mix of 2D drawings and 3D models. A leading German special-purpose logistics OEM wanted reliable target costs across the whole category, €4.2M of spend and 75 assemblies, without putting a value engineer on each one.
COVALYZE Analytics built a statistical cost model across the 75 assemblies and reached a coefficient of determination above 92%, which is a strong result for parts this complex. More useful than the fit was what the model isolated: three drivers explain most of the cost variance. Mast upright thickness accounts for 33%, front plate design type for 27%, and front plate height for 13%. Width, length and supplier carry the remainder.
Engineering and the CTO reviewed those drivers and confirmed they were technically interpretable, which is what made the model usable in practice. The same analysis was then re-run through COVALYZE PartIQ directly from the files. A full cost structure per assembly now takes seconds, against roughly one week of manual bottom-up costing by an internal value engineer.
That speed changes what procurement can do with the category. Retrospective cost transparency across the whole parts portfolio becomes practical, target prices come with CO₂ values attached for relocation discussions, and the analysis shows which parts are overpriced and which are actually underpriced.
