How P. AI Chatbot Improved Sales Forecasting for a Food & Beverage Company

Problem Statement

A leading beverage manufacturer, with over 120 SKUs and distribution networks covering 7,500+ outlets across North America, faced significant challenges with its sales forecasting. The team was responsible for generating forecasts for each product, but the process was bogged down by the need to retrieve and manually analyze vast amounts of data from multiple, often inconsistent sources.

The forecasting team, consisting of 10 analysts, spent nearly 60% of their time on data extraction and cleansing, pulling information from over 15 different systems. This not only led to delays but also created room for errors and inconsistencies in the data, which in turn affected the accuracy of the forecasts.

Due to these challenges, the company's sales forecasts were frequently off by 10-15%, leading to either stockouts or excess inventory, which affected the company's bottom line.

Even though the data was accessible, the leadership team struggled to reconcile the varying output formats from data analysts, data scientists, and other teams, which hampered decision-making.

Solution Implemented

• Multi-algorithm approach tailored forecasts by product category.
• Data science team ensured accuracy despite inconsistencies.
• PAI chatbot integrated into data systems and Microsoft Teams.
• Enabled interactive, visual sales forecasting within Teams.
• Rolling forecasts helped sales prioritize high-margin products.