📋 Building a Procurement Checklist: Why Material Names Are Not Enough
When you build a small internal procurement checklist, material names are not enough. A row called "polyurethane adhesive" does not tell the engineer whether the product is suitable for rubber crumb, mineral aggregate, artificial grass, roll flooring or primer-related work. The data model needs context.
🧩 Suggested checklist structure
I usually split the checklist into fields:
application area
substrate
package size
working temperature
curing behavior
expected load
surface preparation
storage limits
This structure helps avoid the common mistake where price is compared before technical compatibility.
🔗 Real-world data source example
As a real-world data source example, a catalogue like https://sostav.pro/products-categories/poliuretanovyj-klej-i-svyazuyushchie/ is useful because product groups are separated by application. For a procurement table, that is better than a single flat list of adhesives.
📊 The next step: scoring
The next step is scoring. A product can get points for matching the substrate, climate, load and process. Price becomes only one column, not the whole decision. This is especially important when a wrong material creates rework, delays or rejected batches.
If you would like me to add a sample scoring table or expand the checklist into a downloadable format, just let me know.
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