Predictive Analytics in a Post-Covid World

May 11, 2021 9:49:00 AM / by G2M Team

Just as last year’s global shutdown changed the economic landscape, this year’s transition to the new normal will have an impact on many facets of business and life as we know it. So, what does this mean for data? And, more importantly, for the analytics driving our businesses that are supported by that data?

Last year we shared our 2020 lessons, focused on adapting and thriving in a covid-world. While we can’t argue we are “post-covid” yet, we are certainly approaching a transition period, which will likely have the greatest impact on our Lesson #4: Extract the most value out of your business data. In an article for VentureBeat, Michael Berthold of KNIME writes, “Data scientists have never encountered anything like what we should expect in the coming months,” and he’s right – how do you train models with historical data that supported a completely different business environment? The answer is somewhere in the realm of iteratively and often.


"Ultimately, the companies that will end up on top are those that not only refresh their data and modeling perspective but are not afraid to leverage the insights to transform all facets of the business: from go-to-market, to data infrastructure, to operations and business intelligence."

Our advice can be boiled down to the following principles:

1) Be Proactive

checkbox-16x16Check your data frequently

If you used to train your models once per year, you might need to shift to quarterly, or even monthly, if you have enough data. Fluctuations in market forces require careful monitoring or you could easily miss a major change to one of your assumptions.

checkbox-16x16Reevaluate your data inputs

This goes beyond simple training to a refresh of feature selection, or the optimal data set to train a performant model. Suffice it to say, these may have changed based on current context. The likely solution is to cast a wider net to catch a broader set of features, but it could also mean removing features that are no longer necessary to the underlying model.

2) Be Outcome Driven

checkbox-16x16 Make changes based your insights

Seems almost too simple, but often the simpler a principle is, the more we tend to overlook it. Look at the empirical evidence to understand the extent to which things have changed. Layer this against your current business model to identify gaps or areas for improvement.

checkbox-16x16 Move quickly

Don’t worry if your model is not as elegant as you’d like – either fail fast or build in successful changes once they’ve been proven. Your goal is not to build a perfect model, but to ensure your insights are generating practical guidance to improve the business in real time.

3) Be Flexible

checkbox-16x16 Don't expect all segments to recover uniformly

Some groups will bounce back much quicker as they either were not as affected economically or are more willing to assume risk. The same applies to geographies. We can expect to see an uneven recovery globally, which is going to have an impact on the underlying data. 

checkbox-16x16 Be prepared to explore the unfamiliar

Just because your business has operated a certain way, or against a certain metric for a long time, doesn’t make it the right way to continue to operate. New norms often drive novel approaches, and for good reason.

If any of the above feels daunting - G2M can help.

G2M Insights is a business and technology consulting firm focused on developing tailored solutions that help Enterprise clients leverage their data ecosystem to improve go-to-market strategy, operations, and execution. Our professionals bring deep expertise in sales, marketing, finance and technology to support our clients in all areas at the intersection of go-to-market strategy, digital transformation, and AI enablement. For more information, please visit

Contact us to learn more about how we can support your company’s go-to-market strategy and execution.

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Tags: Go-To-Market, AI, Macro Trends, predictive analytics

G2M Team

Written by G2M Team