Supply chain
When recovery takes longer.
Where is the delay, and will the buffer last?
Connect a ranked view of inventory exposure with a stress test of how disruption and recovery interact.
Explore the walkthroughA manufacturing team needed help after flooding disrupted supply despite existing continuity measures. They needed to understand where parts delays could affect production and how long assembly could continue without replenishment.
I led the team reviewing inventory and potential sources of delay. I chose a risk-universe view to connect regional exposure with affected parts, then built on that work with a simulation of how long assembly could survive if parts did not arrive.
- Transactional analysis
- Full populationOrders, receipts, stockouts and transfers
- The view I chose
- Risk universeRegional exposure connected with affected parts
- Continuity model
- TTS / TTRTime to Survive compared with Time to Recover
01 / The approach
From regional exposure to assembly continuity.
Map where delays could affect parts availability, then stress how long assembly can continue while supply recovers.
- 01
Examine the records
Review lead times and inventory movements across the network.
- 02
Rank the exposure
Identify the supplier, part-family and regional delay drivers.
- 03
Stress the buffer
Compare inventory coverage with possible recovery durations.
- 04
Inform the decision
Present the exposure and assumptions for leadership discussion.
02 / Explore in practice
Explore the delay analysis and continuity stress test.
Inspect the lead-time analysis, then adjust the continuity scenario to examine the relationship between inventory coverage and recovery.
The narrative describes the work and its decision context. Interactive records, assumptions and simulation outputs are illustrative and contain no client source data.
Case 01
Delay analysis
Post-flood review · regional exposure and parts availability
I led the inventory review after flooding exposed gaps in the manufacturer's existing measures. I chose a risk-universe view so management could see how exposure in each region could affect different parts. The analysis fed a ranked risk pack for executive discussion.
Explore 18 illustrative part–supplier–region records. These are sample summaries, not the original transaction population.
Northern region — stockout + low cover
Northern depot SKUs with stockout events and fewer than 20 days on-hand — typical post-flood pattern when inbound lanes recover slower than assembly demand.
18
2
Follow-up needed
| Part | Family | Cover (d) | Stockouts | Lead (d) | Recommendation |
|---|---|---|---|---|---|
| RUB-1109 | Rubber & seals | 12 | 16 | 24 | Shift 15% volume to alt vendor |
| TRF-9001 | Cross-depot transfer | 6 | 8 | 9 | Inter-depot SLA breach — Northern |
What this suggests and what comes next
2 sample records match this lens. Northern depot SKUs with stockout events and fewer than 20 days on-hand — typical post-flood pattern when inbound lanes recover slower than assembly demand.
Validate before acting. Check current stock, assembly demand, confirmed delivery dates and the affected parts with inventory, production and logistics owners. The suggested actions in the table are options for review.
Next decision. Use the regional risk view to prioritise the exposure, then test whether the affected parts can sustain assembly until replenishment arrives.
Explore the continuity stress test →What leadership received
A ranked view of exposure and its regional context. Illustrative pack; USD figures are not client results.
Priority risks
Risk universe
Select a cell to inspect the regional signal.
Selected risk / Northern depot stockout cluster
Post-flood: 4 SKUs under 20 days cover with active stockouts — assembly already stalling on brake & body trim.
Decision for review
Approve emergency transfer from Central + temporary safety-stock lift for Northern depots.
Why it mattered
- One page for leadershipA ranked view of exposure gives executives a starting point for prioritisation.
- Risk universe placementHeat map ties supply chain to the enterprise register by region and category.
- Decision-ready asksExposure, mitigation status, and a concrete ask on every top risk.
- A basis for the stress testRegional and parts exposure frames the next question: how long can assembly continue without replenishment?
Case 02
Continuity stress test
How long can assembly continue if parts do not arrive?
We extended the risk-universe work into a simulation: how long could available inventory support assembly, and how much delay could the factory withstand before parts ran out? Compare inventory coverage with recovery time below to explore that question.
This reconstruction illustrates the stress test. Change the parts delay to explore whether inventory can keep assembly running until supply recovers.
Scenarios exceeding coverage
84.2%
Inventory lasts · median
23.7d
Supply recovers · median
30.2d
Time to Survive (TTS) is how long inventory can sustain assembly. Time to Recover (TTR) is how long supply takes to recover. Each dot is a simulated scenario; dots above the diagonal represent recovery taking longer than inventory coverage. The percentage uses all 1,000 scenarios; the chart displays a subset for readability.
What this scenario means
With a 21-day parts delay, recovery exceeds inventory coverage in 84.2% of the simulated scenarios. Median coverage is 23.7 days and median recovery is 30.2 days.
Decision to explore. Review the limiting parts and compare additional stock, transfers, alternative supply or faster recovery. Confirm availability and feasibility with production and logistics owners before choosing a response.
The tolerable delay depends on each critical part's coverage and demand. These scenarios explore that boundary; they do not establish a single guaranteed maximum delay for the factory.
Model assumptions and limits
The illustrative model starts with normally distributed inventory coverage (24-day mean, 4.5-day standard deviation), adjusted for demand variation (2.2-day standard deviation). Recovery adds an average 10 days to the selected delay, with 3.5-day standard deviation. A simulated expedite option applies in 25% of runs, reducing recovery by an average 6 days.
Draws are independent and seeded for repeatable results. Coverage is floored at 5 days and recovery at the selected delay plus 2 days. A coverage shortfall occurs when TTR exceeds TTS. These are demonstration assumptions, not calibrated client estimates; the model does not represent the full bill of materials or correlated supplier disruptions.