In the 1920s, as the Great Flu Pandemic of 1918 waned, and a synergy of technological process, increased mass marketing, and a surge in employment culminated in a massive economic boom. That period, now known as the Roaring 20’s, was a time of immense optimism and opportunity. And history, as it tends to do, has again come full circle.
In the 2020s, we are again emerging from a pandemic and the U.S. economy, after a year of devastating setbacks, is gearing up for unprecedented growth. And this time around, the Roaring 20’s will bring about not mass manufacturing and increased migration to cities, as it did a century ago. It will bring the power of context to the concept of data discovery with automated analytics set to catapult into the future in an event that will be chronicled in history books for decades to come.
As the economy grows, data continues to grow in tandem. Figures and finances exist on two sides of the same ever-vital coin, with increased efficiency for data harvesting pushing forward the capacity for economic growth, and vice versa. The United States economy is set to surge in the coming months— Deloitte forecasts that 2022 will outperform their prepandemic assumption, and even more so, the setbacks and scars that so many economists warned about in the early months of the pandemic appear to have been sidestepped entirely.
And we’re entering this period of economic growth in a simultaneous technological acceleration. Trends in productivity that were in place before the pandemic, including the concepts of telecommunity and e-commerce, were wildly accelerated during the long periods of pandemic lockdown when we were working, shopping, and entertaining ourselves entirely at home. When the world shut down, data was our lifeline. Our collaboration, communication and commercial transactions all became fully data driven. And even as the pandemic begins to wane, better understanding of our data — and comprehending its status as our most indispensable asset — is only becoming more critical.
The most prominent byproduct of this technological revolution will be a vast expansion in GDP.
Some companies will have a significant advantage over others in this boom. Businesses already using AI across their data functions are best positioned to handle this meteoric growth, because understanding the data that you have is a critical and complex stage of business development, one that must be conquered before that data can be translated into actionable business intelligence.
But most organizations don’t have a complete picture of the data that powers them. They require deeper insights into where their data is sourced from, where it’s being used and who it belongs to. Only with these insights and this intelligence can they use that data to make better decisions across all parameters: in privacy, in security and in data governance.
The faster data grows, the more urgent the need becomes for companies to rethink their data management. This urgency is amplified by a global wellspring of privacy and personal data protection, ranging from the European Union’s GDPR to the California Consumer Privacy Act to new and imminent legislation in Virginia, Colorado and Ohio. Globally, similar regulations are poised to finalize in both India and China, cementing the reality that no matter what corner of the globe you operate from, data privacy and protection regulations are no longer a nagging possibility. They are an absolute certainty.
And as these regulations become more widespread, organizations are being forced to provide greater transparency and choice to their consumers. The immediate result of this shift is a new awareness among organizations about what data they collect, process and share, and an overhaul in their thinking about how exactly they find and manage their data.
The focus now must be on scaling with strategy. This is a moment that calls for triple focus: on implementing digital-first strategies; adhering to new privacy and protection regulations and then maximizing the value of existing data – through better data visibility, data quality, and data management. Machine learning and NLP give organizations the power to accomplish the four c’s: cataloguing, classifying, cluster analysis and correlation. And those four c’s pave the way for the three p’s: privacy, protection and perspective.
The Roaring 20s are back, and businesses are preparing for a boom. But before they can see returns, they must first understand that in this century, data is the foundation for all financial progress and business innovation. And if you don’t know what data you have, you’ll never know the benefits that data can bring.
About the Author
Dimitri Sirota is the CEO and co-founder of BigID, a modern data intelligence platform, and a privacy and identity expert. He is an established serial entrepreneur, investor, mentor and strategist, and previously founded two enterprise software companies focused on security (eTunnels) and API management (Layer 7 Technologies), which was sold to CA Technologies in 2013.
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