Consumers enjoy PepsiCo products one billion times a day in more than 200 countries and territories around the world.
PepsiCo’s Collaborative Planning, Forecasting, and Replenishment (CPFR) team provides data and analyses that enable effective retail sales management. The team also collaborates with large retailers to supply the right quantities of product for their warehouses and stores.
Supplying too much product results in wasted resources. Supplying too little means that they risk losing profit—and they must reconcile with unhappy, empty-handed retailers. An empty shelf also risks consumers choosing a competitor's product, which has harmful, long-term effects on the brand. To strike the right balance between appropriate product stocking levels and razor-thin margins, PepsiCo continually refines sales forecasts.
PepsiCo adopted Tableau partner, Trifacta to wrangle disparate data, pulling the data into Tableau for forecasting and analysis. With Trifacta, the CPFR team reduced end-to-end run time of PepsiCo’s analysis by as much as 70%. And with Tableau, PepsiCo reduced report production time by as much as 90%. Today, PepsiCo has more accurate data—faster, giving them a competitive advantage in the retail space.
Searching for a single source of truth
PepsiCo’s customers provide them with reports that include warehouse inventory, store inventory, and point-of-sale inventory. PepsiCo reconciles this data with their own shipment history, production numbers, and forecast data. Each customer had their own data standards, which didn't correspond with each other (let alone PepsiCo's system). For example, PepsiCo relied on UPC codes to identify each product, while customers created their own internal numbers.
Wrangling this data was a challenge and reports could take months to generate. Analysts knew that their ability to quickly standardize data across all retailers—and speak the same language as their customers—was critical to preparing data faster for their forecasting and planning efforts.
Churning out sales forecasts fast enough for management to steer the course on sales was another challenge. Each new report required the CPFR team’s analysts to build a tool in Microsoft Access that combined retailers’ sales data and PepsiCo supply data; a process that could take up to six months.
The team primarily relied on Excel for analysis, creating large quantities of messy data. And the team had no efficient way to spot errors, leading to potentially costly outcomes. For example, a missing product from a report could result in inaccurate forecasts and lost revenue.
The CPFR team needed a way to wrangle large quantities of disparate data. At the same time, the team needed a visual analysis tool that could help them make the most of PepsiCo data.