Revolutionizing Demand Forecasting in a Post-pandemic Era

In the future, we’ll reminisce about the era of COVID-19 and how it transformed our lives. From wearing masks and practicing social distancing to relying on hand sanitizers and conducting business behind plexiglass, we have adapted to a new way of living. As we emerge from the pandemic, certain aspects of our lives will never be the same. We have learned to adapt both personally and professionally.

When the global lockdown began, many retailers abandoned their forecasting resources and focused solely on survival. Meanwhile, consumer packaged goods (CPG) suppliers made strategic decisions, such as pausing production of secondary product lines to ensure essential items remained available on store shelves. Looking back, could more accurate data intelligence have helped manage the bottom line while still meeting customer demands their favorite products?

Amidst this turbulent period, data-driven demand forecasting became increasingly crucial. While more complex, it was not impossible. The rise of artificial intelligence and machine learning empowered retailers and CPGs to leverage real-time internal and external variables, enabling them to create forecasts that anticipate ever-changing demand.

As we mark the three-year milestone since the pandemic began, it’s a good time to reflect on the evolution of relationships between retail and CPG customers and data-forecasting vendors during the height of the crisis. 

Here are some observations:

  1. Communication is key: During challenging times, daily communication between customers and vendors became more vital than ever. Recognizing the severity of the situation, both parties fostered bilateral transparency, acknowledging the challenges and collaborating to find solutions. The clarity in communication became a guiding principle.
  2. Zigzagging patterns: Despite entering a post-pandemic economy, consumer demand continues to exhibit unpredictable fluctuations influenced by factors like inflation and supply disruptions. Brick-and-mortar stores in the apparel sector abruptly closed, but not all retailers experienced a proportional surge in online sales. Food and beverage CPGs witnessed unexpected spikes and stockouts, while other product categories defied expectations. In this altered landscape, data-driven forecasting needed to adapt. Instead of solely focusing on long-term goals, businesses had to ask themselves: What are the numbers telling us now? Why are they telling us this? Where can we pivot today for better outcomes?
  3. The synergy of AI and human intelligence: AI-driven insights often require human analysis to identify underlying causes. For example, during the pandemic, mascara sales increased while lipstick sales declined due to mask mandates, which drew more attention to consumers’ eyes. Sales of home grooming products surged as barbershops and salons remained closed. The combination of AI and human intelligence offers a comprehensive understanding of market dynamics.
  4. Embracing trials and errors: AI and advanced analytics, like any scientific field, involve experimentation and trial and error. The abnormal conditions brought about by the pandemic naturally led to increased errors. However, these mistakes have accelerated the development of better AI and machine-learning solutions. They have enabled businesses to analyze market influences and synchronize retail inventory with shifting customer demand.

As we enter 2023, there is less anxiety surrounding physical proximity to others. However, the retail economy will still face challenges related to inflation and lingering supply chain disruptions. Data-driven forecasting, supported by proactive relationships between retailers and CPGs, will play a pivotal role in understanding the present, past, and future of the industry.

Conclusion: As we navigate the post-pandemic world, demand forecasting plays a vital role in the success of retailers and CPGs. By leveraging data-driven insights and fostering proactive relationships, businesses can adapt to changing market conditions and optimize their inventory. The combination of artificial intelligence and human intelligence enables a comprehensive understanding of consumer behavior. Embracing trials and errors fuels innovation and improves forecasting accuracy. To thrive in the evolving retail landscape, it is crucial to prioritize communication and stay agile. By embracing data-driven forecasting, retailers and CPGs can position themselves for success in the Caribbean, Central, and South American markets.

Visit or contact us today at +1 800 315 1932 to learn more about how we can help to optimize your supply chain and adapt to the post-pandemic retail landscape in the Caribbean, Central, and South America.

Sivakumar Lakshmanan is head of, the AI forecasting and supply chain business unit of Zebra Technologies.