How to Tell if Your Computing Partner is Actually Adding Value to Your Research Process: Adaptability

Part Three in a Five Series for Life Sciences Researchers and IT Professionals  

 If you’re still not sure you’ve sourced the ideal scientific computing partner to help your team realize it’s research compute goals, here’s another quality to evaluate: adaptability. 

By this point, we hope you’ve already read the first two installments in this five part series on how to tell if your partner is adding value (if not, start with #1 – Life Sciences Specialization and Mastery and #2 – The Ability to Bridge the Gap Between Science and IT). Here, we will take a look at the importance of adaptability, and why that quality matters to R&D teams (and their IT counterparts). 

Consideration #3: High Level of Adaptability

In today’s world adaptability is a highly sought after skill. Whether it’s in your personal or professional life, the ability to shift and adjust to change is vital. 

In the context of scientific computing, adaptability is less about survival and more about the ability to see things from different perspectives. In a research environment, though the end goal often remains, the process or needs associated with achieving that goal, can often be fluid.  Being able to or evolve to reach new or shifting goals with precision and performance is a skill not everyone one—or every team—possesses. 

In a research environment, scientists are not always able to predict the results their work will yield, thus needing to work hand in hand with a partner that is able to adjust when necessary. Whether you and your team need a few new resources or a new strategy entirely, a good computing partner will be able to adapt to your needs!

There are even more benefits to having a highly adaptable partner including increased level of performance, smoother transition from one project to the next, and more efficiency in your company’s research. A great scientific computing partner should be able to meet these needs using scalable IT architecture and a flexible service model. If your partner’s service model is too rigid, it may indicate they lack the expertise to readily provide dynamic solutions.

A Better Model for Your Dynamic Needs

Rigid service models may be the norm in many industries, but it does not predict success in the world of life science research. And too often, those partners that fall into the “good enough” category (as we mentioned above) follow these strict SLAs that don’t account for nuance or research environments.  

A partner that is not adaptable will inevitably be incapable of keeping up with the demands of shifting research. Choose a scientific computing partner whose services align with your scientific initiatives and deliver robust, consistent results. Prepare for the next year’s challenges by reaching out to a partner that offers highly specialized scientific computing services to life science research organizations like yours.

As you take all of these points into account, be sure to come back for consideration #4: A Service Model that Fits Research goals.