Over the years, we’ve been involved in a number of LIMS/ELN selection projects. In this new series of blog posts, we’ll take a look at some of the lessons learned from those projects.
A common trap that companies fall into is failing to let the data drive the decision. In other words, if the decision is not based on your company’s requirements, priorities and an analysis of vendor applications, the result is often islands of disconnected data and systems, double-entry into different systems, and time spent munging data from one format into another so that another system can ingest it.
Here are some examples of common scenarios where the data didn’t drive the decision.
Relying On A Friends Opinion
Unless your friend is doing exactly the same things you’re doing, has gone through the selection process recently and has staff with similar experience and requirements, relying on their opinion of a system can be a flawed approach to selecting your system. Your selection should be based on your company’s priorities, budget, and the assessment of your scientific staff.
Memories of a Previous System
It’s sometimes tempting to say, “let’s use System X. I used it my last company, and it was pretty easy to use”. There’s no learning curve, and your team can hit the ground running. But doing so, will cost you the opportunity of surveying the current software market and evaluating software that may potentially be a better fit, may be cheaper, better-performing and easier to use.
Focusing On Part of Your Process
It’s often said that the “squeaky wheel gets the grease”, but when making technology selections, this can have unforeseen consequences. This happens most frequently, when a critical part of the process is time consuming to do, or a leader is particularly vociferous about their needs.
But focusing in one area, can create difficulties as you begin to implement additional solutions further down your pipeline. For example, suppose that the most time consuming part of your process is designing plasmid maps. You find a solution that your scientists love and you implement it. The result is a new data island that’s unconnected to any other system in your lab. You now have to create a way to get that data into other systems, or have your scientists do double entry.
Judging A Book By It’s Cover
It’s easy to be seduced by a good user interface. You are, after all, going to be spending a lot of time using the application. You want it to be easy to use. But this can lead you to select a system that while aesthetically pleasing, doesn’t cover enough of your business process. The result will be that the company must purchase multiple solutions to cover the business process, and that each of those solutions must then be integrated together in order to share data. This will result in recurrent revalidation costs as each integration must be re-tested each time an application is updated.
Read more of the ELN/LIMS Blog Post Series
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