Dijon, June 2022 – For its ODATiO WMS/TMS solution, Savoye is bolstering Labor Management with the development of a new dedicated and innovative module thanks to the use of machine learning.
A key feature of the WMS dedicated to the management of human and material resources, Labor Management makes it possible to plan operators’ work by comparing it with the workload generated by customer orders to be shipped, pending orders and units to be received from suppliers for all logistics platform activities.
Although this feature is systematically present in the specifications of key players in the retail and e-commerce sectors, it is seldom deployed. This is a real paradox, which Savoye has been working on, to offer its customers the means to take advantage of all that Labor Management has to offer.
Overcoming the flaws of Labor Management
Savoye has created a benchmark of Labor Management solutions on the market. We have found that most solutions have five major flaws: short-sighted, vague, selfish, annoying and without ROI.
Indeed, their single-channel nature makes it difficult to plan operational resources. Without an efficient forecasting tool, the WMS only saves a few hours for its user when planning the workload: it becomes rather short-sighted. This is coupled with a considerable lack of precision in activity monitoring and an inability to integrate and measure process productivity not controlled by the WMS. In addition, Labor Management solutions generally involve the management of a name-based staff schedule, which is particularly complex to manage.
All these flaws no doubt lead to a lack of return on investment.
Field-oriented features and user expectations
Savoye’s new Labor Management module makes it possible to define the KPIs required to manage your warehouse: productivity per “sector”, “cell” and also per “delivery destination” or “sales channel”. Via the ODATiO solution, Savoye has provided fully tailor-made solutions for each installation.
In order to simplify the roll out and, above all, daily use when quick decisions have to be made, Savoye has chosen to use resources that are not name-based, i.e. An FTE (full-time equivalent) solution.
An essential feature of this module, real-time productivity reporting is able to measure the productivity of operators, including tasks that are not covered by the WMS.
Offering improved HR management thanks to machine learning
In order to optimize its Labor Management module and to provide all the information about the workload to be expected in the warehouse, Savoye has relied on artificial intelligence and machine learning. “ERPs mainly use statistical techniques for their forecasting. The advent of machine learning is gradually making this approach obsolete. Therefore, our models are based on stored data in the warehouse for them to produce their own forecasts, using real-life business cases.” explained Marwane Bouznif, Machine Learning and Optimization Engineer at Savoye.
In order to demonstrate the efficiency of its solution, Savoye has already initiated three POCs (Proof of Concept) in the retail sector: “Over almost five years, we have been able to achieve a discrepancy of 5 to 10% between our calculations and actual applications. This excellent result enables our customers to better anticipate their operational workloads, in particular during sales periods or one-off events and to increase profitability”, concludes Grégory Lecaignard, Software Product Manager at Savoye.
The new Labor Management module is integrated into the latest version of ODATiO.