Depot utilisation
- A 110.9% · B 108.9% · Overflow 950 pallets a day.
Executive Intelligence · Advanced Executive Intelligence
Enterprise Digital Twin
A model of the organisation's entities, processes, systems and flows built from recorded data and used for what-if analysis.
Demonstration: Brightwater Logistics (fictional) · Logistics. Fictional data and a scripted answer.
The situation
- Organisation
- Brightwater Logistics (fictional)
- Who is asking
- Chief operating officer
- Industry
- Logistics
- What happened
- Demand is expected to grow, and the COO wants to test how the two depots cope before committing to a third.
The question asked
If demand grows and we shift more traffic to the larger depot, which depot overflows first?
What it reads, and who can see the result
- Network model registerDepots, capacities and routing rules.
- Demand forecast exportPallets per day.
- Reads
- The network model and the forecast.
- Does not read
- Individual shipments or customers.
- Permission
- Network planning access.
- Who sees it
- The COO and the network planners.
Try it
Change the assumptions. Every result and the answer below are recomputed from them, and a warning appears when a result crosses a stated limit.
- Total daily demand
- 10,350Today 9,000 pallets a day.
- Load on depot A
- 6,210
- Load on depot B
- 4,140
- Depot A utilisation (capacity 5,600)
- 110.9%
- Depot B utilisation
- 108.9%
- Pallets a day that overflow
- 950
At this demand and routing one depot is over capacity: the overflow has to be rerouted, delayed or housed elsewhere.
The answer
Simulated answer. Written for this fictional case, not produced by a live model. Only the figures in it are computed, from what you decided above.
At 15% growth the network carries 10,350 pallets a day; 950 overflow.
The twin applies the routing rule to the forecast [S1][S2]: depot A takes 6,210 (110.9% of its capacity) and depot B takes 4,140 (108.9%). Where the two utilisations differ most is where re-routing helps before any building does.
A twin tests a design; it does not know what would happen on a bad day. The useful question is how much growth the network absorbs before the first depot overflows, and the sliders answer that directly.
Relies on: S1 · Network model, two depotsS2 · Demand forecast, next year
No approval is needed for this result: it is read-only insight, and nothing consequential happens because of it.
What it produces
Before committing to a third depot
- Test re-routing and shift patterns first; they cost far less.
Limits of this example
- Daily averages; peaks and the day-to-day mix are not modelled.
- A model of the network as described, not as it is operated.
- This is a scripted demonstration on fictional data. No model was called and no real organisation, person or result is shown.
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