Alteryx Case Studies Pepsico's Transformation to Smarter Sales Forecasting with Designer Cloud

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	Pepsico's Transformation to Smarter Sales Forecasting with Designer Cloud Alteryx

Pepsico's Transformation to Smarter Sales Forecasting with Designer Cloud

Alteryx

Applicable Industries	Consumer Goods Retail
Applicable Functions	Procurement Sales & Marketing
Use Cases	Demand Planning & Forecasting Time Sensitive Networking
Services	Cloud Planning, Design & Implementation Services
Challenge	PepsiCo, a global consumer packaged goods company, faced a significant challenge in calibrating sales forecasting to supply the right product quantities to its retailers. The sales forecast incorporated a variety of data, including warehouse data, store stock data, and promotional forecast data, all of which were provided by retailers in different file formats and delivered using various methods. The primary challenge was the speed of preparing a sales forecast. With the existing Microsoft Access and Excel-based processes, the time required to prepare this data was so extensive that analysts could only leverage it once a month or not at all. This inefficiency risked under or oversupplying retailers, potentially impacting PepsiCo's business operations and customer relationships. Read More
About Customer	PepsiCo is a global consumer packaged goods company whose products are enjoyed by consumers more than one billion times a day in over 200 countries and territories worldwide. The company's product portfolio includes a wide range of enjoyable foods and beverages, with 23 brands that generate more than $1 billion each in estimated annual retail sales. PepsiCo's operations involve a complex supply chain, with a need for accurate and timely sales forecasting to ensure the right product quantities are supplied to its retailers. Read More
Solution	To address this challenge, PepsiCo built a Microsoft Azure data lake for centralized data storage and access. The company also implemented Designer Cloud, which analysts trained in Excel and SQL could easily adapt to. This solution enabled the analysts to prepare and standardize diverse retailer data significantly faster for visualization in Tableau. Unlike Excel, which had size limitations requiring analysts to stitch together multiple spreadsheets, Designer Cloud allowed PepsiCo to see the full picture of its data and quickly spot any errors or inconsistencies. As a result, analysts spent less time on data preparation and could dedicate the majority of their time to analyzing data and predicting trends, driving more value for the company. Read More Log in to view content
Contents

Applicable Industries

Consumer Goods

Retail

Applicable Functions

Procurement

Sales & Marketing

Use Cases

Demand Planning & Forecasting

Time Sensitive Networking

Services

Cloud Planning, Design & Implementation Services

Challenge

PepsiCo, a global consumer packaged goods company, faced a significant challenge in calibrating sales forecasting to supply the right product quantities to its retailers. The sales forecast incorporated a variety of data, including warehouse data, store stock data, and promotional forecast data, all of which were provided by retailers in different file formats and delivered using various methods. The primary challenge was the speed of preparing a sales forecast. With the existing Microsoft Access and Excel-based processes, the time required to prepare this data was so extensive that analysts could only leverage it once a month or not at all. This inefficiency risked under or oversupplying retailers, potentially impacting PepsiCo's business operations and customer relationships.

About Customer

PepsiCo is a global consumer packaged goods company whose products are enjoyed by consumers more than one billion times a day in over 200 countries and territories worldwide. The company's product portfolio includes a wide range of enjoyable foods and beverages, with 23 brands that generate more than $1 billion each in estimated annual retail sales. PepsiCo's operations involve a complex supply chain, with a need for accurate and timely sales forecasting to ensure the right product quantities are supplied to its retailers.

Solution

To address this challenge, PepsiCo built a Microsoft Azure data lake for centralized data storage and access. The company also implemented Designer Cloud, which analysts trained in Excel and SQL could easily adapt to. This solution enabled the analysts to prepare and standardize diverse retailer data significantly faster for visualization in Tableau. Unlike Excel, which had size limitations requiring analysts to stitch together multiple spreadsheets, Designer Cloud allowed PepsiCo to see the full picture of its data and quickly spot any errors or inconsistencies. As a result, analysts spent less time on data preparation and could dedicate the majority of their time to analyzing data and predicting trends, driving more value for the company.

Impact #1	The implementation of Designer Cloud brought about significant operational improvements for PepsiCo. The analysts were able to reduce the total reporting time by 70% and build dashboards for new customers 90% faster than with Excel and Access. This efficiency meant that analysts could spend less time on collecting, cleaning, and preparing data, and more time on creating dashboards for more customers, including online retailers. Additionally, Designer Cloud’s visual profiling capabilities allowed the team to easily identify gaps and outliers in the data to get ahead of larger issues, thereby reducing errors and improving the overall quality of their work.

Impact #1

The implementation of Designer Cloud brought about significant operational improvements for PepsiCo. The analysts were able to reduce the total reporting time by 70% and build dashboards for new customers 90% faster than with Excel and Access. This efficiency meant that analysts could spend less time on collecting, cleaning, and preparing data, and more time on creating dashboards for more customers, including online retailers. Additionally, Designer Cloud’s visual profiling capabilities allowed the team to easily identify gaps and outliers in the data to get ahead of larger issues, thereby reducing errors and improving the overall quality of their work.

Benefit #1	70% reduction in total reporting time
Benefit #2	90% reduction in data pipeline build time
Benefit #3	$7M in order processing errors proactively resolved

Benefit #1

70% reduction in total reporting time

Benefit #2

90% reduction in data pipeline build time

Benefit #3

$7M in order processing errors proactively resolved

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Overview

Pepsico's Transformation to Smarter Sales Forecasting with Designer Cloud

Operational Impact

Quantitative Benefit