Manufacturing
Is production keeping pace with demand?
Sales demand and production capacity usually live in two systems that do not talk to each other, so the gap between them shows up as a stockout or an excess only after it happens. FactSmith puts both sides side by side so you can see the gap before it becomes one.
Why this matters
Reconciling sales orders against production output today usually means someone manually cross-checking two reports on a schedule, not continuously.
What data is needed
Production or output facts and sales-order or demand facts on a comparable time grain -- weekly, for most operations -- by product line.
The evaluation copy runs against PostgreSQL. SQL Server is on the adapter path for a customer warehouse; that path is not what the package proves end to end today.
How the analysis works
Planned or actual production volume is compared against demand for the same product and period, flagging where the gap is widening rather than only where it currently stands.
What can go wrong
Lead time and work in progress complicate a naive same-period comparison -- output today reflects demand from weeks ago, not this week's orders. The analysis needs to account for that lag rather than compare same-period numbers directly.
Example
A multi-product manufacturer asks which product lines have demand running ahead of production for two consecutive periods. Ask returns them ranked by the size of the growing gap.
How FactSmith approaches it
Ask is what is available now. Easy Data -- turning messy sources into that dimensional foundation -- is in early development.
FactSmith calls this the Fact Layer: a data integration (ETL) step, a knowledge base, and a business ontology, working together underneath the answer. On screen it stays simple -- ask a question, get a trusted answer -- with the layer-by-layer detail available to anyone who wants to see how the answer was built.
Permissions are enforced beneath the AI, not by it -- see Trust and security.