Predictive Intelligence for Consumer Goods During a Crisis

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Predictive Intelligence for Consumer Goods During a Crisis

By Eric Hillerbrand - 04/13/2020

By studying historical data, we can often provide new insight into how to combat future viruses, and other health and disease states. That said, according to Dr. Fauci, director of the National Institute of Allergy and Infectious Diseases, there is little understanding of the novel coronavirus.

The inventory of analytics consumer goods and retail industries have previously relied upon for projecting demand forecasting, supply chain and marketing management, are now obsolete. COVID-19 has rendered them useless.

Businesses need advanced data science and artificial intelligence to help them make far more intelligent decisions. In these acutely uncertain times, AI probabilistic models are perfect as they actually model uncertainty.

Moving forward, companies will need a more sophisticated planning mechanism for addressing the residual effects of COVID-19 and the likely reoccurrence of other pandemics in the future. 

For example, Shortest Track has developed an intelligence framework for thinking about insights and intelligence requirements across all business functions and across pandemic lifecycles.

For many businesses, AI is still too much of a novelty. If they don’t understand its value, they will refrain from investing in it. Herein lies the conundrum: an unpredictable phenomenon that benefits from analysis using AI, and a business environment in which AI is perceived as high risk with uncertain rewards.

Meanwhile, the spread of COVID-19 is picking up speed, making time more precious. While AI-based predictive models that align with business needs are prime solutions, they can be cost-prohibitive and time-consuming to implement. 

The bottom line is that companies need AI to solve modeling problems of the complexity of COVID-19 disruption but can’t afford the dollars and the time. Companies are attempting innovative go-to-market and business models.

One such company attempts resolve this dilemma by providing free AI-based COVID-19 solutions, which can create value now, and then provide low cost access to an inventory of intelligence capabilities that leverages the collective buying power and value across a broad number of businesses.

In reality, the more solution utilization through low cost engagement by more users — the better for everyone. A “rising tide lifts all boats” — lower cost, better outcomes and firmer ROI.

A warehouse of AI components will expedite the delivery of cost-effective consumer goods and retail solutions by accessing proprietary datasets and modeling approaches. This approach produces low cost, high impact COVID analytic models.

These models reveal how COVID-19 will impact sales and production, and provide vital hyper-local information to help decision makers with:

  • Demand Forecasting
  • Supply Chain Optimization  
  • System Overload Prediction
  • Staff Allocations
  • Store Closing/Opening
  • Marketing Allocations
  • Digital Media Allocations

Companies need more than partial answers and best guesses when faced with the tragedy of the commons — when individuals rapidly consume resources, resulting in severe shortages. Businesses not only look at the present crisis, but also need help to envision how it will affect their future competitive environment.

Flattening the curve will be a reality but it won’t lessen business disruption. Instead, it extends the length of this disruption. Once any given business is post-peak, accurate data is still critical. A major distributor that is currently down 35% will need to know how much product it should store in its warehouses. Without this granular hyper-local data, it will not be able to forecast. 

Coronavirus will eventually ebb, but businesses need to think beyond, “How do I respond now?” They should be thinking about how to respond post-pandemic — and even beyond that to the next pandemic.

Companies need more than partial answers and best guesses when faced with the tragedy of the commons.

Eric Hillerbrand is CEO of Shortest Track, a company that delivers the broadest set of advanced data science and artificial intelligence solutions tied to relevant business outcomes today using a low risk and low-cost business model by providing clients with the ability to test drive before buying. Before founding Shortest Track, Hillerbrand was founder and CEO of three AI startups, including Talkthree, a cognitive computing company that delivered cognitive computing and artificial intelligence for the purposes of enhancing real time, customer journey based predictive modeling and personalization. He helped design the massive cognitive computing investment undertaken at Sears Holdings for several hundred million dollars, which eventually ran all of marketing and merchandising. Prior to this role, he held leadership positions at McGraw Software, and Enleague – a Coca-Cola Innovations company. Hillerbrand earned his PhD. in psychology from the University of Iowa and was a faculty member at the University of Missouri.

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