If the developments of the last few years are anything to go by, no one would bat an eye if retailers felt like Julius Caesar during the Ides of March. In 2020, the month saw stringent lockdowns imposed to counter the explosive COVID-19 spread, resulting in estimated industry-wide losses of $2.1 trillion in 2020. Businesses had barely begun to come to terms with the outbreak when, on March 23 this year, they were dealt another major blow: a ship sailed into a canal.
This might sound like the setup to a joke, but the global retail ecosystem is unlikely to find humor in it. After all, the ship was the 400-meter-long Ever Given which ran aground in the Suez Canal. The resulting blockage, lasting just over six days, dominated global news cycles and social media memes– all the while causing losses exceeding $9 billion every day by blocking a shipping channel handling 12% of worldwide trade.
The worse bit? Their impact on the global retail ecosystem could have been mitigated.
Much before COVID-19 was categorized as a pandemic, BlueDot, an AI-based outbreak risk prediction, had identified the indicators of an epidemic by analyzing real-time data from thousands of sources. The alert was raised on December 30, 2019, more than two months before countries implemented full-scale lockdowns to combat the rapid spread of the novel coronavirus. Had retail players paid attention and used the data to inform their business decision-making, the losses faced by the industry would have been much less severe.
Even more baffling was the level of unpreparedness for the Ever Given crisis. Experts had been warning about the exponential increase in ship sizes, while port handling capabilities and shipping channel capacities remain quasi-stagnant, for several years. Concerns were also raised about the incremental risks accrued on such mega-ships, where a single delayed vessel can have a cascading impact on trade and business across regions and industries. No one paid any heed until, one fine morning, the worst of predictions came true.
Now, these two situations might seem poles apart. One, after all, was a human-made disaster decade in the making while the other was an unavoidable natural calamity. However, if we look closely, they were connected by data. There was a plethora of information available before and during both these events – something that Active Intelligence, with its focus on hyper-contextual data, could have used to either proactively address or reactively contain the situation and its eventual impact.
Let's consider a real-world example before we venture into the hypothetical: Vancouver International Airport (YVR). Using cutting-edge techs such as AI, real-time data analytics, event stream processing, and IoT, the airport collects and analyses disparate data points to create the situational context that goes beyond operational and transactional data. The insights generated through analytics are relevant to the time, place, point, and need of their use which, in turn, allows for more accurate, optimal, and future-ready decision-making. For instance, by combining wind speeds, size of aircraft, and transfer priorities of incoming passengers, it optimizes gate allotment for each inbound aircraft – a feat that would be impossible if done manually.
But how does this translate to better, more resilient, and future-ready operations for the global retail industry? For instance, in the case of the pandemic, retailers with an Active Intelligence-led framework can look to incorporate healthcare, incidence, and travel data to factor in the impact and spread of COVID-19 along their supply chains. Such real-time, contextual insight generation, based on the current situation and future projections, can help build alternative sourcing and distribution channels to stay ahead of this or future pandemics.
Active Intelligence could also have played a role in either averting the Ever Given crisis or mitigating its impact. For one, it could have identified adverse weather conditions and alerted the port authority against letting mega-ships – with mile-high stacks of cargo containers that often act like canvas sails – enter the channel until the weather had stabilized. Even once the crisis was underway, such a system could have helped retailers contain its impact on their operations by evaluating various factors such as shipment delays, container availability, demand-supply dynamics, and healthcare information, among other factors. The contextual insights thus generated could have helped them to stave off potential disruptions and identify other prospective bottlenecks and challenges, such as the second wave sweeping across many South Asian economies. The result? More resilient, adaptive supply chain frameworks are driven by AI-based predictive analysis.
This is just the tip of the iceberg when it comes to the difference that the hyper-contextualized data enabled by Active Intelligence can make. For instance, it can help retailers implement dynamic pricing based on real-time factors such as demand and supply, procurement costs, etc. It can also help retail players introduce hyper-personalization in marketing and customer re-engagement efforts. Repetitive functions, such as inventory management, can be automated and streamlined to optimize operations and drive better business outcomes.
Saying that the pandemic and the Ever Given blockage are once-in-a-lifetime events will be more than an understatement – it will be a prayer that such cataclysmic events never happen. There is, however, no guarantee, and for retail businesses to prepare for present and future disruptions, they need to become more resilient and adaptive. This, in a world as interconnected and dynamic as ours, can only be achieved with Active Intelligence.
Author:
Varun Babbar, Managing Director, Qlik India
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