Every laboratory can tell you its maximum throughput. That number is real, achieved once, under ideal conditions, with everyone available.
What determines whether your project finishes is the ordinary week — and the way to learn that is to ask about the bad ones.
Questions that get useful answers
- How many samples did you process last month, actually?
- When the instrument breaks, how long until it runs again?
- Who else is using this equipment and how is time allocated?
- What is the longest delay you have had in the last year and why?
- These get concrete answers; "what is your capacity" does not.
People, not just equipment
- How many hours per week can each named person genuinely give?
- What else are they committed to during the project period?
- Who does the work if the lead person is unavailable for a month?
- Are the students full-time, and how long do they stay?
Infrastructure that gets overlooked
- Power stability and backup for long runs.
- Cold storage capacity and reliability.
- Internet bandwidth for transferring large datasets.
- Consumables supply chains and lead times for imports.
- Import lead times for reagents are a frequent hidden constraint.
What strong capacity looks like
- They tell you their limits without being pushed.
- They have said no to something before.
- Data from previous projects is organised and retrievable.
- Junior staff can explain the protocol independently.
Designing around real constraints
- Build the protocol around what is reliably available, not what is theoretically possible.
- Add contingency time proportional to the number of dependencies.
- Consider funding the constraint directly if it is small and decisive.
- A protocol that only works on good weeks will not finish.
One thing worth remembering
Ask "what did you actually process last month?" rather than "what is your capacity?"
The first question has one honest answer and it is the number your project will live with. The second invites the best case, which everyone quotes in good faith and nobody achieves twice in a row.
Câu hỏi thường gặp
What questions reveal real capacity?
How many samples were processed last month actually, how long until a broken instrument runs again, who else uses the equipment, and what the longest delay in the past year was and why.
What should you ask about people?
How many hours per week each named person can genuinely give, what else they are committed to, who covers if the lead is unavailable for a month, and whether students are full-time.
What infrastructure gets overlooked?
Power stability and backup, cold storage reliability, internet bandwidth for large datasets, and consumables supply chains with import lead times.
What does strong capacity look like?
They tell you their limits without being pushed, they have said no to something before, data from previous projects is organised and retrievable, and junior staff can explain the protocol independently.
Why ask about last month rather than capacity?
Because the first question has one honest answer and it is the number your project will live with, while the second invites a best case nobody achieves twice in a row.
