How much milk can the cold hub actually serve?
Bound reachable daily demand by effective service capacity.
The question
This fictional Kenyan collection area has 500 farms. Each farm has the stated average output. The target is daily litres handled by one hub and handling-fee revenue, under a simplified planning model. Every number is invented.
| Value | |
|---|---|
| Farms | 500 |
| Inside collection area (%) | 50 |
| Willing among reachable farms (%) | 70 |
| Litres per farm per day | 20 |
Reach and willingness are separate filters. Farms outside the collection area are not served.
| Value | |
|---|---|
| Nameplate throughput (litres/day) | 6000 |
| Planning availability (%) | 70 |
| Handling fee per litre (KES) | 5 |
One cycle per day, no storage accumulation or extra shift. Use planning-average effective capacity; this is not a guarantee of daily uptime.
Test willingness from 50% to 90%, with other inputs fixed. Fee revenue applies only to litres actually served.
“Explain the estimate, the assumption range and the next check.”
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A strong answer, step by step
Open each step in turn. This is one strong answer, not the only one.
Step 1: Find reachable demand
What would you do here? Open the move you’d make.
Apply reach and willingness before sizing service.
The strong move. Total category production is not the hub’s serviceable demand.
Use all 10,000 litres as hub demand.
Tempting, but it misses something. That ignores both the collection boundary and willingness to use the hub.
See how a strong candidate says it
“500×50%×70%×20 = 3,500 litres a day. Total farm production is 10,000 litres, but much of it is outside the reachable, willing audience.”
Why it works: Total category production is not the hub’s serviceable demand.
Step 2: Apply the capacity bound
What would you do here? Open the move you’d make.
Use the lower of serviceable demand and effective capacity.
The strong move. Revenue is bounded by the lower of demand and capacity.
Book fees on all 4,500 litres at the high end.
Tempting, but it misses something. The high-demand scenario exceeds effective capacity by 300 litres.
See how a strong candidate says it
“Effective capacity is 6,000×70% = 4,200 litres. At 3,500 demand, fee revenue is KES 17,500 a day. Willingness of 50–90% gives 2,500–4,500 demand, but only 2,500–4,200 can be served.”
Why it works: Revenue is bounded by the lower of demand and capacity.
Step 3: Check the peak
Peak-season output rises to 28 litres per farm per day. Reach, willingness, effective capacity and fees stay unchanged.
What would you do here? Open the move you’d make.
Cap peak volume at 4,200 litres.
The strong move. Peak production changes demand without adding capacity.
Keep the baseline capacity surplus during the peak.
Tempting, but it misses something. The updated demand is above the same capacity, so the baseline spare capacity has disappeared.
See how a strong candidate says it
“At 28 litres per farm, demand reaches 4,900 a day. Capacity remains 4,200, so 700 litres are unserved. Fee revenue is KES 21,000, not KES 24,500.”
Why it works: Peak production changes demand without adding capacity.
Step 4: Test before expanding
What would you do here? Open the move you’d make.
Validate peak demand and operating availability.
The strong move. A planning average and gross fees do not establish a reliable expansion case.
Recommend expansion from KES 21,000 of fees alone.
Tempting, but it misses something. The packet supplies no operating cost, investment cost or proven peak uptime.
See how a strong candidate says it
“I would verify collected volumes, peak timing and uptime before sizing another shift or an expansion. At peak output, willingness of 50–90% gives 3,500–6,300 litres of demand, but at most 4,200 served under this model.”
Why it works: A planning average and gross fees do not establish a reliable expansion case.
The answer, in short
- Decision
- Use 4,200 litres a day as the modeled peak service ceiling.
- Because
- Peak reachable demand exceeds effective capacity by 700 litres.
- What would change it
- Measured peak demand, uptime or a feasible additional cycle would change the service estimate.
Common traps
- Calling total production reachable demand.
- Charging for volume the hub cannot serve.
Check your answer
- I separated reach and willingness.
- I derated nameplate capacity.
- I applied the peak change.
- I kept planning capacity separate from a guarantee.
Last reviewed Nov 10, 2026