Challenge
The Fiege Logistics Branch in Vienna employs just under 110 people in a storage area of 16,000 m². Fiege handles all logistics for its customers. Customers also include a large electronics retail chain. A customer who is unable to make forecasts and also has a highly action-driven business model. Accurate forecasts of incoming and outgoing quantities of goods in B2B and B2C business are necessary here in order to be able to carry out long-term, data-based personnel deployment planning.
For an electronics retail chain, Fiege Logistics previously had internal forecasts that were used on an Excel-based basis for personnel deployment planning. This only made it possible to react manually to events and spikes. Long-term vacation planning and targeted staff growth are therefore hardly possible. There are increased costs and forecasts are based purely on internal data without taking into account important external factors such as major sporting events, the effects of the COVID-19 pandemic and other influences on incoming and outgoing goods.
Approach
The AI-based pacemaker forecast forecasting tool for Fiege logistics was made available at the Vienna location. With the fully automated SaaS solution, the site was able to predict incoming and outgoing goods for the next few weeks. As a result, personnel deployment could be planned much more long-term. For the first time, external influencing factors were also included in the forecasts of incoming and outgoing goods. For example, the tool showed that special effects such as major sports events and the closure of branches due to corona have a particular impact on the utilization of the location.
Outcomes
Together with Michael Jahn (Managing Director of Fiege Austria) and the team from the Fiege Omnichannel Retail Location, a fully automated machine learning forecast was implemented in personnel deployment planning within just a few weeks. The first forecast achieved an accuracy of over 90% and was improved through further data comparisons.