Is BIG DATA big enough to beat the big recession?
What’s the first thing you need to do in the COVID-19 economic aftermath? That’s right. Analyze. Analyze big!
December 16, 2020
No recession comes with the same blow. Making decisions based on the experience of prior recessions is foolish and can be misleading. A coronavirus is an unprecedented event and the consequences will be the same – unprecedented. Evolving consumer habits as a result of the explosion in technological advancements over the past few years mean that this will also be hard to predict, and it could be that companies that barely survived previous recessions do better this time. Analytics can anticipate the direction that it will take and allow for responses to be formulated quickly enough to have an impact. So, let’s see how you can use the power of big data and deal with the recession to come.
When in recession start with “recession”
Rather than relying on a few anecdotal bits of evidence, big data allows us to measure exactly how much more frequently words like “recession” have crept back into use. Examining who is talking about a recession can give us insight as to who is potentially worried about economic growth. We can then decide if we should be worried, too. While the word “recession” might have a bit more mind share among the broader community, we’d like to know whether the same is true among the actual economic decision-makers. Are investors and business leaders showing equal concern over a potential recession as the broader public?
Looking back at the post-2008 crash, we see that both investors and management teams used the word more frequently. One interpretation of this comparison is that while investors now have a recession on their minds, management teams are less concerned.
Analyze and you will immunize
By analyzing different applicable social media communications, the company’s machine learning models can recognize and predict emerging trends months in advance, which can give them a tremendous advantage in a competitive market with fewer users.
For example, businesses can utilize an analytics-based predictive model that helps estimate future sales and enable companies to respond more promptly with data-driven insights.
In periods of economic crisis, fraudulent events also become commonplace in businesses, particularly in banking and finance. Business intelligence and fraud analytics can be applied to trace and examine such attempts, and data insights can be utilized to foretell general features of users anticipated to be connected to such activities.
The bottom line is that the application of BI software and analytics should not be deemed extravagant during bad economic scenarios that may come with a Coronavirus. Instead, it should be seen as a much-needed technology tool that should be leveraged across all business actions – from discovering revenue opportunities, preventing frauds, getting rid of fund wastage, optimizing the workforce, and even sales and marketing.