Jobs theory around scientific products
jobs theory and the Jobs to be done framework are great tools to identify opportunities and define features for a minimum viable product. I believe science-based startups can greatly benefit from their use but almost no one is using it.
Assuming we focus on scientific products that can be purchased by a single PI (not infrastructure-type of investment).
The Job Executor will have the hands on the product. They are probably a PhD, Postdoc, or technician.
The Product Lifecycle Support Team will either be a distributor, or someone at the institute who needs to handle certifications, installation, trainings, etc.
Purchase decision maker will be the PI.
It is crucial next, to identify the type of job each one will be doing around the instrument.
The core functional job of the executor is relatively clear, extracting some information from our machine. For the lifecycle team, the training of new users could be the core job.
But what is the core functional job for the PI? Since they run on publishing papers, it's a safe bet to assume that's their core job.
Related jobs are an interesting point, because they are the ones that easily drive a product to failure. What does it take to prepare the sample, analyze data, clean up. There are always so many steps with a machine's operation. What about replication and reproducibility? Some of these jobs may be performed by different people at different moments in time. (See: There is always a cost to introducing new technology).
Emotional jobs are greatly responsible for poor adoption. People who spent countless hours solving issues and becoming an expert at a technique, will not easily change to the next shiny thing. There's a given prestige about doing something right, even if it's sub-optimal. Instruments designed like those from iZon appeal in part to that. Or those fancy lasers that require realignments...
Consumption chain jobs, are often not relevant at the moment of defining a minimum viable product, but nonetheless relevant for credibility. How is the maintenance of equipment, up to date software, troubleshooting, replacing components, and eventually the end of life? Does it take 3 days to train a user or few minutes? If the product uses consumables, what about their acquisition, use, and disposal?
Purchase decision job which in many cases comes down to "is it cheaper/faster", for academia it takes a different meaning: grant writing. That's the core job of the PI to lead the sale of equipment. There will be a compromise: buying this equipment means not buying another one, which circles back to the emotional jobs of the PI.
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