Settings
These parameters drive safety stock, reorder points, excess classification and carrying cost across every screen.
Service level targets
Drives the safety factor in the safety stock formula97.0%
95.0%
90.0%
Financial and coverage policy
7.5%
3 months
180 days
270 days
40
Language and role
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Metric definitions
Shown as tooltips throughout the platform- Total Inventory Value
- Value of all on-hand stock across the network, at average unit cost.
- Σ (on_hand_qty × avg_unit_cost)
- Forecast Sales (next 3 months)
- Ensemble forecast quantity for the next three months valued at standard price.
- Σ (forecast_qty × standard_price × market price index)
- Forecast Gross Profit
- Forecast revenue less forecast cost of goods sold for the next three months.
- forecast_revenue − forecast_cogs
- Gross Margin %
- Gross profit as a share of net revenue over the trailing twelve months.
- (net_revenue − cogs) / net_revenue
- Inventory Turnover
- How many times inventory is sold and replaced per year.
- trailing 12m COGS / average inventory value
- Stock-out Risk
- Gross profit exposed to demand that cannot be served from projected stock.
- Σ (expected unmet demand × unit gross profit × stock-out probability)
- Excess Inventory Value
- Value of stock above the lower of the maximum level and three months of forecast demand.
- Σ max(0, on_hand − min(max_level, 3m forecast)) × unit_cost
- Working Capital Opportunity
- Cash that could be released by clearing excess and dead stock.
- excess inventory value + dead stock value
- Forecast Accuracy (MAPE)
- Mean absolute percentage error of the forecast against actual demand.
- mean(|actual − forecast| / actual)
- Service Level
- Share of forecast demand expected to be served from stock without delay.
- 1 − (expected unmet demand / forecast demand)
- Days of Inventory
- How many days current available stock covers at the seasonally adjusted demand rate.
- available_qty / average daily demand
- Safety Stock
- Buffer stock protecting the target service level against demand and lead-time variability.
- Z(service level) × √(LT × σ²demand + demand² × σ²LT)
- Reorder Point
- Stock level that should trigger a replenishment or production order.
- average daily demand × lead time + safety stock
- Stock-out Probability
- Likelihood of running out before the next replenishment arrives.
- 1 − Φ((projected available − demand over lead time) / σ over lead time)
Audit trail
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Demonstration dataset. All figures are simulated for illustration and do not represent actual ISOMAT results.