Orders-to-Capacity Summary
A management view focused on plan variance, capacity pressure, delivery risk, and recommended action.
Planning window
Four-week fictional planning horizon.
Stabilise machining before treating revenue variance as a demand problem
The headline shortfall in forecast revenue appears to be driven more by capacity execution and order timing than by weak demand. The first management decision should be whether to absorb overload through overtime, resequencing, or delivery re-commitment.
Production: Review machining overload in weeks 3 to 5 and decide whether to add overtime or resequence lower-priority jobs.
Supply Chain: Investigate aged stock concentrated in low-demand product families before raising replenishment on adjacent SKUs.
Finance: Track revenue timing impact separately from demand weakness so management can distinguish execution variance from market variance.
Executive view
A small KPI set focused on decision pressure rather than report volume.
Mock shortfall driven by late machining output and deferred dispatches.
Open demand still scheduled inside the next eight weeks.
Orders whose required dates are exposed by current capacity pressure.
Average across constrained work centres for the next four weeks.
Mock on-hand value across raw material, WIP, and finished goods.
Stock with low recent movement and weak near-term demand coverage.
The first work centre where planned hours exceed stable available hours.
Average slippage against standard cycle time in the current mock period.
Capacity view
The deeper operational lens focuses on where demand stops being deliverable.
| Work centre | Available hours | Planned hours | Utilisation | Gap | Current signal |
|---|---|---|---|---|---|
| Casting | 240 | 214 | 89.2% | +26h | Stable. |
| Extrusion | 180 | 188 | 104.4% | -8h | Overloaded during demand spike. |
| Machining | 320 | 356 | 111.3% | -36h | Primary bottleneck. Late jobs now stacking. |
| Quality | 140 | 132 | 94.3% | +8h | Tight, but manageable if upstream flow improves. |
Inventory view
Inventory is shown here as a planning variable, not just a stockholding total.
Stock cover is healthy for high-volume families but weak for one fast-moving line expected to spike next month.
Aged inventory is concentrated in two families with declining historical usage.
Recommended action is review-first, not blanket replenishment, because capacity and mix are changing together.
Variance analysis
This view links plan variance to management implication.
| Measure | Current | Plan | Variance | Management implication |
|---|---|---|---|---|
| Forecast revenue | $5.76M | $6.01M | -$250K | Delivery timing pressure is suppressing near-term revenue recognition. |
| Production output | 1,184 units | 1,260 units | -76 units | Machining and extrusion overload reduce output against schedule. |
| Inventory aged over 90 days | $318K | $250K | +$68K | Cash is tied up in slow-moving lines not aligned to current demand mix. |
| On-time order completion | 88% | 95% | -7 pts | Customer delivery risk is rising before financial plan recovers. |
Scenario examples
A small set of examples to show planning logic.
If demand rises 10% with no extra machining hours, the weekly capacity gap widens from 36 to 68 hours.
If machining downtime improves by one shift per week, at-risk orders fall before inventory needs materially increase.
If alloy cost rises 6%, gross margin pressure appears even if revenue stays near forecast.
Implementation note
The model is designed around shared business definitions so the same logic could later sit on top of SQL data sources and feed Power BI, Excel, Jet Reports, or Crystal Reports.
Data model
A simple shared model across Sales, Production, Inventory, and Finance.
Sales Orders
Demand signal, required dates, order value, and customer-facing delivery commitment.
Production Jobs
Scheduled workload, actual hours, process stage, and delay reasons used to explain output variance.
Inventory
Current stock, value, movement recency, and usage assumptions used to detect ageing and stock risk.
Work Centres
Available hours, downtime, utilisation, and bottleneck pressure by process area.
Finance Forecast
Budget, forecast, and cost signals used to connect operational variance with financial impact.