How to make a pitch for new lab equipment

You need a new piece of lab equipment and are faced with three problems 1) a lab manager’s budget for new instruments and equipment is $82,0001 2) your colleague has already been gunning for a new confocal microscope for months 3) the new intern dropped a glass round bottom. A big one.

How do you make the case for your request?

The short answer is: data. As scientists, we understand data. If you are trying to convince your boss that your request is the best investment for the lab, give them the data that backs you up. Do the same kind of research you would to plan out a new experiment.

1. Explore whether buying is the best option

Buying a brand new machine is not your only option. See if there are nearby core labs where you can rent time. At the very least you’ll know the cost of instrument time. Plan out the actual experiment you want this machine for. Then approximate the time you’ll need for your experiments and estimate the cost of renting time versus investing in equipment. This way you know the options available. When your boss asks, you can show them the costs for each.

If you work within a large biotech company, send out the bat signal to your colleagues. Someone might be getting an upgrade and have an older one that can serve your purposes. This is especially applicable for high throughput production labs that often need the newest equipment that allows them to increase throughput. If you work in a small scale discovery lab, an earlier generation machine might be all you need.

2. Come prepared with a fully-formed request

If you go to the lab manager and say, “I need a mass spec!” what they hear is not only do they need to find room in their budget for that machine, they need to figure out which mass spec you need and where they need to buy it from. Take the guesswork out of your request and provide as much information as you can upfront.

Figure out exactly what you want. Instead of asking for a machine, tell them you are interested in buying x machine at y price from z company with n attachments. The result is you can get your request approved and in motion faster.

I recently read an interesting example from Argonne national laboratory. When they needed super-strength magnets they were able to find two decommissioned ones from hospital MRIs in Minnesota and California. Instead of spending a million dollars for new magnets, they only paid a few thousand for shipping.

3. Back up your request with data

Here is where your prior homework comes into play. You told the higher ups exactly what you need, now give evidence as to why you need it. Detail the experiment that you want to do and the data you need to collect. Present a comparison of costs as well as capabilities for rental versus buying options. With a clear picture of soft and hard ROI, the lab manager is armed to make decisions.

4. Go with a squad

Talk to your fellow scientists. If multiple people need the same machine, then show that! Go armed with a list of the researchers, projects and experiments that could benefit from a single purchase. If you are looking to get a second or more advanced version of a machine you already have, then check the equipment logs. If you have a list of scientists who are all fighting for the same time slots, they would appreciate another machine as much as you. While you are at it, take the equipment log to your meeting. Show your boss the only time the machine is free is 11 pm on Friday.

5. Offer something back

Nobody wants a new piece of equipment to sit unused. If you are the only one currently interested, offer something in exchange. Agree to write an SOP as a resource for the entire lab or hold a training session on how to use it. That way more people know that it exists and can get trained to use it.

Go forth and make smart data-driven decisions to get the lab equipment of your dreams! Or at least convince your boss to get a second centrifuge so you aren’t always waiting on the guy who does multiple hour-long spins.

Learn how TetraScience Utilization can help you make data-driven decisions around investing in new equipment.

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