The global economy continues to struggle to adapt to the Covid-19 pandemic, and industries across the world are still suffering from increasingly complex and compounding effects. One of them is the unremitting disruption of the global supply chain, which has evolved into a full-blown crisis.
We all recall March 2020 when panic-filled shoppers emptied shelves of toilet paper and PPE across the U.S., causing months-long shortages. Initially, factories worldwide were forced to shut down when workers fell ill with the virus. This remained an issue through 2021 in countries like China and Vietnam, where prolonged labor and parts shortages have caused consumer demand to surpass output, leading to surging inflation and a lack of goods. For example, the global semiconductor shortage forced automakers to increase prices on vehicles, and eventually consumer goods like smartphones, computers and household appliances met a similar reality.
Now, two years into the pandemic, consumers are still spending less on commuting, traveling and services than they did pre-pandemic, and in some countries, consumers are also still receiving government funds in the form of Covid economic assistance. Many are deploying those funds into retail spending, exacerbating demand.
Surging demand is forcing companies and governments to develop solutions to the global logjam, but these will take time. This is why more and more corporate enterprises are looking to one of their most important assets — their data — to help them better navigate these choppy waters. Just as the pandemic has accelerated the adoption of software that enables remote work, it is pushing management teams to invest in technologies that enable them to utilize their data to see over the horizon and better prepare for disruptions. CEOs are challenging business line leaders to anticipate and mitigate risks before they materialize in the trailing data of their financial reports. Advances in machine learning are now enabling this real-time, proactive approach to risk management, by way of billions of pieces of data from public and private sources.
Imagine what you can see when you can instantly connect dots like these: a satellite photo of a storm in the middle of the Pacific; a post on social media from a crew member on a container ship idling off the coast of California complaining about a new delay; and a blog post about an outbreak of Covid at a key overseas factory. These are just a few examples of the insights within hundreds of thousands of publicly available data sources, a global sensor network that enables management teams at forward-thinking (and -looking) companies around the globe to generate real-time understanding and enable faster decision-making. (Full disclosure: my company offers data services like this, as do others.)
As corporate enterprises embrace this unprecedented ability to detect what is happening across the business landscape in real time, leaders are finding themselves able to make informed decisions more quickly than ever before. They are reducing threats across the risk spectrum, reducing crises to issues, and identifying opportunities for course correction in a matter of minutes –– not days or weeks –– creating a competitive differentiator.
That competitive differentiator then becomes a new standard of management differentiation, one that will endure long after both the supply chain and public health crises of today subside. Data competencies developed for business resilience will almost certainly become essential to competing and winning in less overtly challenging times, whenever they return. Then, as now, winning teams will embrace the opportunity to truly see their businesses and to manage them in real time.