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Data-Driven Digital Transformation of a Car Rental Business

Key results
3% increase in fleet utilisation rate
95% accuracy of demand prediction
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Summary

Russmann, a Germany-based car rental business, sought to boost efficiency through IT ecosystem modernisation. ELEKS developed the Central Disposition System, featuring centralised fleet management, data-driven car disposition and fleet planning. Our data science experts created analytics modules for fleet optimisation, advanced planning, customer segmentation, and behaviour prediction. This enabled Russmann to forecast demand with 95% accuracy for three to nine weeks, resulting in a 3% increase in fleet utilisation and reductions in transfer costs and idle time, thereby enhancing overall profitability.
Location
Europe
Cooperation period
2016 - 2020
Services used
Data science Technical support Application re‑engineering
Industry
Logistics
We were impressed by ELEKS’ attention to detail and willingness to analyse how our business works. They consider issues from both business and technology perspective and work out a well-envisioned and carefully designed solution. We had a pretty tight timeframe of just two months for creating the first working version of the system, but ELEKS managed to rapidly build up a team and scale it efficiently, which helped us meet the deadline and successfully develop the solution further.
Peter Russmann
Managing Director at Russmann GmbH + Co, KG
The situation

Russmann wants to increase business efficiency by revisiting its IT ecosystem

In 2016, Russmann understood the need for redesigning their operational processes to improve cost-effectiveness and increase its fleet utilisation rate. They wanted to transform the fleet management process and enable informed and more accurate fleet transfer decisions by making them centralised, automated and data-driven.

Russmann aimed to integrate and orchestrate all its IT systems to improve operational efficiency, reduce errors and minimise IT risks. They also wanted to adopt an automation solution that would eliminate the need for station managers to distribute vehicles manually, and would work towards higher fleet utilisation rates and lower transfer costs.

Russmann contracted ELEKS as a technology partner to help them address their needs with an efficient IT solution.

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The solution

A centralised fleet management solution reinforced by data science

As a first step, ELEKS performed an on-site product design phase for Russmann, to understand their key needs and translate them into a technological solution. As soon as the scope had been agreed with Russmann, ELEKS proceeded with MVP development. One of the critical challenges for the team was the timeframe of two months for the MVP, delivered from scratch.

The Central Disposition System that ELEKS designed and delivered for Russmann works as a complex solution for the customers’ needs. The solution provides centralised fleet management, data-driven car disposition and fleet planning. The system also includes a customer service module and a dashboard to facilitate managerial decisions.

The solution uses data science to provide a weekly forecast on car rental demand, based on the historical data and taking into account seasonality and other factors. ELEKS’ data science

specialists also created a number of analytics modules for fleet relocation optimisation, advanced fleet planning, customer segmentation and behaviour prediction.

The solution was installed on each Russmann’s station, helping managers make long-term and short-term decisions about fleet disposition. The ELEKS team provides ongoing improvement and maintenance.

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The result

Reduced costs and higher profits with a single point of orchestration

The Central Disposition System established a single point of orchestration for all of Russmann’s previously disconnected systems. A streamlined communication among our client’s systems eliminates the need for manual car management. Currently, five disposition managers coordinate the whole fleet as the tool has automated 90% of car distribution decisions.

Russmann can now predict demand with a 95% accuracy for a period of three to nine weeks. Our client’s profitability improved with a 3% increase in their fleet utilisation rate while their car transfer cost and idle time significantly decreased.

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What our customers say

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