Predicting Retail and CPG Business Futures with AI and Economic Intelligence

Last Updated: September 10, 2021

External forces increasingly impact retail and CPG businesses. With the latest AI-based modeling, it is now possible to identify the leading drivers and incorporate them into predictive micro-economic models. Prevedere’s CEO and chief economist recently discussed this transformative tech at the 2021 Analytics Unite Virtual Experience and its unique ability to systematically identify and quantify the influence of economic factors on future business outcomes. This blog recaps the session and the main takeaways.

The Effects of COVID-19

Throughout the last year and a half, the pandemic has dramatically shifted consumer behavior, and some effects of this shift will have lasting impacts as we move into 2022 and beyond. Even though some aspects of COVID-19 may be starting to fade away, CPG and retail companies need to understand that the business environment is unlikely to ever return to pre-pandemic normal. As Prevedere Chief Economist Andrew Duguay describes in the webinar, businesses “need to be incorporating new consumer data trends and insights into [their] predictions and models…incorporating external data is going to be a critical part of being able to navigate what this post-pandemic economy looks like.”

While CPG and retail businesses are increasingly recognizing the need to incorporate external data, it can be overwhelming to sort through the massive amount of big data available today. That’s where AI and ML can come in and find the most important leading indicators statistically in the same way an economist or data scientist would by hand, but much faster. With advanced technology, automated econometric modeling is more efficient and more cost-effective than ever before. As Rich explains in the webinar, “we can leverage cloud platforms to build predictive models.” The result is that “you can take these leading external signals, [such as] the Weekly Economic Index or the Dodge Momentum Index, and based on your industry, you can turn those into a predictive model and test almost every possible combination today.” 

Intelligent Forecasting

One of the most significant benefits of intelligent forecasting is that it is entirely adapted to a company’s needs rather than a generic model built for a specific industry. In intelligent forecasting, a company’s historical data is used as a dependent variable within the model, which results in leading indicators that are incredibly specific to that company. Moreover, a one-size-fits-all approach to forecasting will not work for CPG and retail businesses but rather a category, region, or product-specific forecast. Rich highlights how intelligent forecasting provides the technical tools to pick a specific data set as the dependent variable “that we’re going to compare all these millions of external signals to, to find one of the right leading indicators for this specific challenge, whether it’s a category, a platform, or a subcategory if it’s for a region”. This ability to easily customize, add, or change the model provides the flexibility and specificity necessary to ensure accuracy across all aspects of the business planning process for CPG and retailers.

While business leaders know the logical relationship between external signals and their business performance, they often do not have the validation or quantifiable information to support their intuition. Intelligent forecasting empowers leaders to quantify and integrate their experience and knowledge into the planning process. Insights from the intelligent forecasting model need to be combined with human intelligence to maximize results. Prevedere’s intelligent forecasting is centered around this idea of transparency and ease of use to optimize integration opportunities with business leader’s insights.

Ultimately, investing in predictive analytics with AI not only means more accurate business forecasts but can also create a better relationship between CPG companies and retailers. In the webinar, Rich explains, “we’re seeing people become category captains because they’ve got more insight, and that insight is desired by their partners and their distributors”. Over time, creating these types of stable and improved relationships with the help of quantifiable data is essential for CPG companies and retailers.

To access a recording of the session:

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