Before I get into a nuanced and borderline-philosophical discussion of what makes building a digital twin of your biotech lab so difficult, let me first address the biggest pain point for a lot of us: Many of the companies that sell lab data/informatics software rely on manipulative sales techniques whose only purpose seems to be to lock in customers and squeeze more revenue out of them.
I’m not going to name names, but if you’ve been working in biotech for any amount of time, you’ve probably dealt with one or more of these:
Their web page doesn’t really explain what their software is or does.
You have to sign up for their sales funnel and have multiple preliminary meetings before you can even see a demo.
It can take months to get your own instance running, after which you still have to pay them to configure it for you.
Even with this configuration, you’re still locked into a very specific way of working, (probably based on whatever their early clients wanted).
The per-user monthly license costs are high enough that your strategy for assigning licenses becomes a minor obsession.
I’m sure there are more that I missed - let me know in the comments section.
To be clear, I don’t necessarily think that these companies are being malicious or intentionally manipulative. Software engineering is hard and changing large organizations that have been consistently profitable for decades is even harder. Many of their customers are optimizing for consistency, reliability and a large feature set, and these options deliver that.
But for those of us who are optimizing for an intuitive and flexible user experience tightly integrated with a broader digital platform, this just won’t cut it. We need to know what we’re getting, get it up and running quickly, and have the power to manage and customize it ourselves.
The good news is that many of the startups building the new generation of biotech data software are choosing the strategy of focusing on good products instead of just sales funnels. I also think there are opportunities for the community to build and adopt open source tools that will further discourage these bad practices. (More on that soon.) So starting next week, we’ll look at the more fundamental issues with building a digital twin, that are even harder than dealing with manipulative sales funnels.
Scaling Biotech is brought to you by Merelogic. We’ll help you turn your ML prototypes into tangible impact, whether it takes a few small tweaks to how your team operates or larger changes to your tools, infrastructure and projects. If you want to explore what this might look like for your team, send me an email at jesse@merelogic.net
I think there's a lot of vagueness on both sides (mostly unintentional). The vendor doesn't want to pigeonhole their product and limit potential customer base. They also may not have portions of it fleshed out yet and hope that interactions with customers will help with that. And they probably have limited resources to provide pilots/sandboxes for potential customers to kick the tires. On the customer side, the interest in a product may be serious and well-thought out. Or, it could be just someone looking around with a general idea of what they need. I've found mostly the latter - that the customer's actual need for a new system is often unclear. There's uncertainty about cost constraints, expected ROI, what works and does not work in the current system, current workflows that are not nailed down or documented, and the requirements for a new system are not fleshed out. When you layer on the realities of change management, validation, updated process and control docs, logistics and impact of the transition/go-live to a new system, etc., the limitations discussed in the article can be seen as expected.
Having seen the sales and implementation side, I think there is a lack of trust that the customer knows how to evaluate the product. This "high touch" approach (Agreed not malicious or intentionally manipulative) can be to ensure each customer converts to a deal.
Parallels this great overview on how Atlassian sells product: https://www.intercom.com/blog/podcasts/scale-how-atlassian-built-a-20-billion-dollar-company-with-no-sales-team/.