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Warehouse
August 8, 2023

What Solution to Improve Warehouse Resource Management Performance?

Companies with their own warehouse face numerous challenges related to productivity and the attractiveness of logistics jobs. To address these challenges, some invest heavily in mechanization and automation. However, an AI-driven resource organization offers a more accessible and immediate lever for performance improvement. This is where a solution like a Resource Management System (RMS) comes into play. Let’s explore the explanations and implications.

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The Need for Anticipation

To effectively manage schedules and daily task assignments, warehouse managers require a detailed overview of all available resources: operators, robots, mechanized chains, sorters, equipment (carts, forklifts, …), and facilities (docks, racks, ventilation systems, …). Isabelle Badoc, Product Marketing Director at Generix, states, “Managers constantly make decisions to allocate resources to tasks in order to achieve the productivity necessary to meet volume objectives.” This demand is amplified by e-commerce, which brings about increased volumes and a wider variety of tasks. Simultaneously, predicting the irregular flows becomes a critical aspect. Thus, anticipation becomes a key strategy.

Enhancing Resource Management for Better Employee Retention

E-commerce-related flows require more labor for package preparation and packaging than delivering pallets to stores. However, the sector is facing a shortage of candidates. Warehouses are thus challenged to retain already trained resources by making their work more engaging. Compensation conditions are no longer the sole criterion for attracting or retaining employees. Motivation and satisfaction are better factors for attractiveness and retention, contributing to improved work quality. Employers must take action on two fronts: ensuring a secure environment through accident prevention and ergonomic measures, and providing a certain level of autonomy that generates job satisfaction. Various initiatives, such as integrating challenges for younger employees in the “gaming” generation and adapting tasks for senior employees, aim to strengthen employee engagement.

Balancing Flexibility and Productivity

Logistics professionals operate in a context of uncertainty due to irregular flows and absenteeism rates that can reach up to 50%. This necessitates constant agility in organizing on-site resources and prioritizing activities. Calculating actual production capacity while optimizing available labor is a complex challenge. Effective deployment of versatility could ease this challenge. Isabelle Badoc explains that versatility ensures more flexibility for warehouses by utilizing multi-skilled resources, thereby enhancing the capacity to carry out important tasks on any given day. Employees trained for multiple roles can switch every two hours, reducing the strain of repetition, maintaining their focus and performance throughout the day, and reducing the need for temporary workers, thus cutting costs.

Are There Solutions to Achieve These Goals?

Previously, many warehouse managers primarily considered investments in mechanization and automation to enhance performance. However, resource management based on better planning could prove more efficient while maintaining the same human-machine ratio. This is the purpose of the Generix Resource Management System (RMS), named Generix Resource Management. It analyzes performance, predicts the time needed for each task, and aligns these elements to plan and distribute resources effectively. This solution is also customizable and contributes to reducing workplace accidents and strain.

In conclusion, integrating AI into an RMS solution offers powerful resource planning capabilities, thanks to prediction and optimization. The combination of human-robot collaboration will likely remain a key logistics model in the coming years. Maximizing the use of existing resources could be a simpler and more cost-effective performance lever to explore before committing to massive investments in machinery.

 

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