What is the cost of bioinformatics? A look at bioinformatics pricing and costs - Karl Sebby

This resource first appeared in issue #109 on 11 Feb 2022 and has tags Strategy: Product/Service Management

What is the cost of bioinformatics? A look at bioinformatics pricing and costs - Karl Sebby

This article is important to ponder even if your team’s work falls completely outside of bioinformatics.

Service delivery models gets very little discussion in our community despite its importance. That’s a shame! It’s a pretty key part of how we interact with research groups. The delivery model determines how easily communicated and sustainable providing the service is, even if there isn’t any kind of cost recovery. How the service is delivered is a key part of the service itself.

Here Sebby investigates the variety of delivery models and prices for the analysis of next-generation sequencing data. This is a pretty specific kind of problem, typically with a clear underlying task and well-defined best practices, and yet it’s still an interesting example. There is both the compute cost and the people-time cost, and it requires expertise and close interaction with the research group.

Even with this extremely well-scoped offering, there are at least four different delivery models described:

  • Bespoke work negotiated per project with hourly rates for people time, and “pay-as-you-go” compute/storage
  • Productized service; e.g. $150/sample for a single whole genome sequencing sample, or even a subscription service for samples
  • Set up some infrastructure for the research group (e.g. the galaxy workflow environment), charge for the node, and let the group run the workflows
  • Sell access to a platform (e.g. the model of DNAnexus, Seven Bridges, etc - and even within this group there are different business models)

There are pros and cons to each approach; they appeal to different potential clients, who have different expectations and different kinds of expertise available internally. The hourly rate is safest for the service provider, but is riskier for the client (how do I know how much will this cost in total?). “Productized service” is easiest for the casual researcher to understand, and transfers some of the risk to the service provider (what if this sample’s data is especially low-quality and takes longer to process?). On the other hand this approach makes it much easier to “sell” a large number of the services, and over time it should average out. Set-up-some-infrastructure is nice and readily automated for the service provider; it’s more work for the researcher but may make a lot of sense for a group that has many samples to run and its own internal expertise. And if your group was doing a lot of similar tooling setup for a lot of different clients, it might make sense to become a platform of some sort.

To be clear, this sort of service design thinking does not hinge crucially on money being charged to cost centres. How researchers know what you can do for them, how that work is packaged up into deliverables, and how do they know what it will ask of them in terms of effort and turnaround time are important questions to work through even if the service is “free”.

And if it’s not free, look at that range of prices and rates quoted - productized services for the same service range by factors of 2-3, in one case 7x; hourly rates vary by a factor of 6. And yet all of these service providers are going concerns. Maybe always being the cheapest option available isn’t the only feasible choice?

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