Features and innovations
As we know, artificial intelligence (AI) can be used to automate and optimize warehouse processes. This is the case with our "Warehouse Healing" strategy, which shortens travel times, improves warehouse structures and reduces throughput times during order picking.
But to fully exploit the potential for increasing efficiency in the warehouse, our data science expert Timofej is working on AI-based personnel planning for intralogistics.
Melanie from Marketing spoke to Timofej about the topic and learned some exciting things.
1. why did you get involved with AI-based personnel planning?
Timofej: As a data scientist at a software manufacturer for warehouse management systems (WMS), I am always looking for ways to improve and automate processes. The idea of using artificial intelligence (AI) for workforce planning came about while I was assisting with a bachelor's thesis. We analyzed the data from our WMS, including past incoming orders, stock levels and historical data, and discovered the potential for optimizing workflows.
In logistics, the unpredictability of the volume of work often presents a challenge. Scheduling the right number of employees at the right time is not easy. AI-based personnel planning recognizes patterns and predicts peak phases. This enables more efficient planning. The aim is to plan and act not only reactively, but also proactively.
2 I often read on the Internet: "We use AI for personnel planning." Is that really the case?
Timofej: The claim "We use AI for HR planning" is quite broad and is interpreted in different ways. Many companies say they use AI, but in reality they only use simple automation techniques or statistical methods. These are often found in tools such as Excel or specialized software. While these methods are useful, they do not offer the advanced capabilities of true AI models.
The development of AI-based workforce planning goes beyond simple automation and traditional data analysis. We develop and implement advanced AI models that learn from large amounts of data. These models recognize complex patterns and make precise predictions for workforce planning.
The AI-based forecasts in our WMS help users to make dynamic and data-driven decisions. Integration takes place directly in the operating environment.
3. how can AI support personnel planning?
Timofej: Artificial intelligence and machine learning in personnel planning offer various opportunities to optimize processes and increase efficiency.
4. which problems can be solved with the help of AI in personnel planning?
Timofej: Manual personnel planning is a time-consuming task and very error-prone in a complex and large warehouse with many employees and requirements. These problems can now be eliminated:
5. what data is required?
Timofej: For effective and precise AI-based personnel planning, I need a broad database. The following data is important:
6. what challenges are there during implementation and use?
Timofej:
7 I'm getting ahead of myself, as the tool is still in the development phase. How will the tool be made available in the WMS and will there be a separate dashboard?
Timofej: Yes, that's the plan. The forecasts for staffing requirements and other analyses are then integrated directly into the WMS. This guarantees a seamless user experience. Customers can access all information as usual. The dashboard is designed to be clear and user-friendly. It offers diagrams, tables and visual representations. These help users to analyze and interpret data effectively.
The dashboard provides continuous updates so that specialist staff can act quickly. The forecasts in the WMS ensure that all relevant information is centralized and easily accessible. This reduces administrative work and speeds up decision-making. The integration minimizes the need for training, as employees can continue to use their familiar systems.
Thank you for your time and the interesting insight into your work.
In the second part, we explain the advantages and possibilities in more detail: AI-based workforce planning: Optimum scheduling with just a few clicks (Part 2/3).
We use data from our customer Hermann Müller Elektrogrosshandel GmbH to develop the tool. You can find out more in this article.