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Looking back on 2022 is like looking back on the past, 3 years since the pandemic began.

And there is, for me at least, one major lesson: the need to be resilient.  

Resilience is about being prepared, as individuals, as companies and as a society, to readily adapt, respond and ultimately recover from unexpected challenges or threats.

We lose site of the need for resilience in good times – lulled into the idea that they will continue indefinitely. While economic cycles ebb and flow practically no one was expecting a pandemic. Who could have foreseen the dramatic changes that followed as a result?  

The great resignation, as it has been dubbed, characterized by employees who have re-evaluated what was important to them leading to shorter tenures. The US Bureau of Labor Statistics data shows that employees between 20 and 34 years of age have a median tenure of just over 2 years.   

How can leaders of companies in engineering and science build resilience? There are three areas of focus that you might want to consider. 

"Resilience is about being prepared, as individuals, as companies and as a society, to readily adapt, respond and ultimately recover..."

First, automation.

Find ways to make even complicated analyses routine so that anyone can conduct them with minimal training. It not only speeds things up but it also reduces errors and allows more flexibility in (re)assigning staff to tasks.  

Second, accelerate your ability to generate knowledge.

Here we continue our research in machine learning for smaller sets of observational and experimental data that has expanded a great deal in 2022. While there is a lot of focus on mining massive amounts of data, an excellent source of knowledge can be mined from smaller sets of just dozens of observations.  

A blend of these first two, our SVEM (Self-Validating Ensemble Modeling) application has made data analysis much easier in part by eliminating the baggage that too often accompanies statistical methods dramatically slowing their adoption.

More engineers and scientists are able to develop accurate predictive models from smaller sets of available data without requiring a PhD in statistics or data science. 

Third, preserve your research knowledge.

The time and resources you invest in research is your competitive edge. Too often companies lose their research knowledge when staff members move on or projects lose momentum – and findings are shelved.

Keep your research knowledge in structured and explicit form so that it can be readily sought, found and re-used, even if the staff that originally generated it are no longer available.

In this area we will be releasing  an expanded CoBase Knowledge Relationship Management system early in 2023. We have learned so much from our current user base and early adopters that will be of benefit to any company engaged in engineering and science.

Looking ahead…

To serve our growing client base in all three areas we have welcomed new members of the Predictum team in 2022. Each quickly latched on to our mission allowing us to contribute to the resilience and success of our clients. 

If you want to stay on top of what we’re doing, follow us on LinkedIn or join our mailing list. 

All of us at Predictum wish you and yours the very best for 2023!

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    For over 25 years, Predictum has enabled companies to achieve higher levels of productivity, operational improvement and innovation, and realize significant savings in cost, materials, and time. Our team of engineers, data scientists, statisticians, and programmers leverages deep expertise across various industries to provide our clients with unique solutions and services that transform data into insightful discoveries in engineering, science, and research. To get in touch with our team, visit www.predictum.com/contact.

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