Businesses Use Analytics to Find Hidden Opportunities at meteolytix

Published on 06-Nov-2012

Customer:
meteolytix GmbH

Industry:
Consumer Products

Deployment country:
Germany

Solution:
BA - Business Analytics, BA - Predictive Analytics, Big Data & Analytics, Big Data & Analytics: Customers, Smarter Marketing, Smarter Planet

Overview

meteolytix GmbH builds statistical models that provide daily sales forecasts for the retail and service sectors. With six employees, this innovative enterprise unites the know-how of statistical data analysis, high-quality weather forecasts and enterprise consultation service in a unique manner. Its aim is to save costs for its clients by making intelligent use of available knowledge to increase service levels and improve customer retention.

Business need:
To reduce returned goods and save costs, a bakery chain was looking for piece-precise sales predictions for each branch based on the day’s weather.

Solution:
With the help of IBM® SPSS® Statistics, meteolytix GmbH developed precise, accurate sales forecast models based on weather data, historical sales and information about other contributing factors. The result is a self-learning automatic closed loop statistical model which increases revenue and lowers costs by minimising over- and under-production.

Results:
Reduces returned goods by approximately 33 percent. Saves two to three working hours per week for each branch.

Benefits:
Uses exact sales forecasts to optimise production, capacity and distribution costs, and improve the availability of products and services. Increases customer satisfaction. Contributes to the avoidance of waste and reduces environmental impact.

Video

meteolytix GmbH builds statistical models that provide daily sales forecasts for the retail and service sectors. With six employees, this innovative enterprise unites the know-how of statistical data analysis, high-quality weather forecasts and enterprise consultation service in a unique manner


Products and services used

IBM products and services that were used in this case study.

Software:
SPSS Statistics

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