Floor-ready entry
Record job, machine, shift, operator, planned and actual runtime, scrap, and downtime reason in less than a minute.
Illustrative manufacturing scenario
A focused SharePoint application can turn difficult ERP exports and floor observations into fast data entry, operational trends, exception flags, and better job-cost estimates.
THE PROBLEM
Supervisors need to know why one job performs differently across machines and shifts. They also need to understand whether an operator is unusually effective on a particular machine and whether a certain order type is showing early signs of degraded performance.
When the current system is slow to update and difficult to analyze, those questions are answered from memory, ad hoc spreadsheets, or time-consuming exports. That weakens improvement work and makes estimating future jobs less reliable.
The Workshop application does not need to replace the ERP. It can provide the fast operational interface and analysis layer the existing system does not provide, while using ERP exports as a starting source.
THE WORKING APPLICATION
Record job, machine, shift, operator, planned and actual runtime, scrap, and downtime reason in less than a minute.
Filter trends by similar job and order type so differences are not hidden inside broad averages.
Flag degraded performance and use historical results to adjust assumptions for future estimates.
STARTING PROMPT
“Build a SharePoint app for production supervisors to record each completed job by machine, shift, operator, order type, planned runtime, actual runtime, scrap, and downtime reason. Make floor entry take less than a minute. Show machine and shift trends, operator-machine fit, and flag degraded performance for similar orders. Add an estimating view that uses historical performance to adjust future job costs, starting with exports from our ERP.”
RESULT
The team can identify machine and shift trends, see operator-machine combinations worth learning from, and investigate degraded performance before it becomes an accepted norm.
Because those findings are connected to order types and historical runtimes, estimators gain better evidence for jobs that consistently require more time, setup, or scrap allowance.
This is an illustrative scenario. Actual outcomes depend on data quality, process consistency, adoption, and the operating environment.
We’ll show how Workshop can turn it into a focused SharePoint application.