We started this series by describing how keeping your data and analytics current, accurate and relevant can help navigate uncertain and chaotic times such as the COVID-19 pandemic. In the second installment, we described how artificial intelligence (AI) enables flexible forecasting built on models and data that change as the world does.
Our clients are telling us how necessary and urgent it is to update their analytics processes amid the pandemic. In a recent survey that we conducted in North America, three-quarters of respondents said that their companies had changed their data management and analytics/models during COVID-19. Respondents at companies with more volatile revenue swings were much more likely to have made major changes in data management than those with less volatile revenue.
In our final installment, we describe agile analytics in action and then reveal three essential elements for success.
Shopping, pandemic style
Retailers have had to adapt to two strong shifts in consumer behavior during the pandemic: Fluctuating demand for goods and a move to e-commerce. For example, as governments imposed social distancing rules in early 2020, a leading global convenience store chain found the “basket” of top-selling items changing virtually overnight. With sales falling sharply as customers avoided going out, the chain needed to quickly adjust its inventory and store displays to maximize sales and profits.
To remedy this, we created a robust cloud-based data and forecasting foundation, and then within five days created new models to enhance the convenient chain’s understanding of market dynamics to respond to daily changes in a wider range of parameters. This helped decision-makers see changes like the shift toward bread, milk and eggs over the previous priorities of coffee, cigarettes and muffins. This updated system continued to provide new insights throughout the volatility of the pandemic. Managers responded by making extra efforts to keep those items in stock and placing them near the checkout so customers needed to spend as little time as possible in the store. As a result, our client said average per-customer purchases of these products rose about 25%.