AI-based workforce planning: Optimum scheduling with just a few clicks (Part 2/3).

In this article, we go into more detail about the benefits from the interview on "AI-based workforce planning: The invisible helper for the warehouse. (Part 1/3)" with our data science expert Timofej.

What was the interview about?
The short version: That it is difficult to schedule the right number of employees at the right time in the individual warehouse areas. There is often an imbalance between available and required staff. This is usually due to unforeseeable order peaks and unplanned staff absences. Manual shift planning is also time-consuming and error-prone, especially in complex warehouses with many workers and variable requirements.

The advantages at a glance
AI models analyze and process large volumes of historical data. This includes Order volumes and events such as sales promotions as well as process data. AI-based workforce planning recognizes patterns, seasonal fluctuations and trends. It predicts peak periods and future workloads. This enables more efficient planning. As a result, the right number of employees are always deployed according to the workload. Significant savings in personnel costs can be achieved by reducing overtime and idle time.

Making optimum use of availability and skills
AI-based personnel planning takes into account the availability of team members as well as the workload. One employee may be on vacation, another may be ill or absent for a longer period of time for personal reasons. This also makes it easier to balance the different skills of the employees (if available) for the tasks. For example, new employees first need to be trained or employees with special additional training are more experienced in certain areas than others.  

"With the help of AI, shift scheduling is perfected, operational efficiency is increased and operating costs are reduced at the same time. The tool ensures that the right staff with the right skills are scheduled in the right area at the right time to maximize productivity. It also reduces the administrative burden and frees up staff to focus on other important aspects of warehouse operations, says Timofej."

Lightning-fast response to changes
AI-based tools can respond in real time to changes such as unexpected sick notes or sudden order peaks. The use of algorithms that reschedule quickly ensures that the warehouse is always ideally staffed. This flexibility helps to minimize downtime and improve service quality.

Traditional planning methods quickly reach their limits when there are sudden fluctuations in demand. The tool enables specialist staff to proactively prepare for unexpected changes in shift planning. In dynamic working environments, the rapid adaptation of personnel resources to changing conditions can be crucial.

Data instead of gut feeling
AI helps professionals to make decisions based on data instead of intuition or outdated methods. This leads to more objective and well-founded planning in HR management.

In addition, AI can not only assist with planning, but can also analyze performance data (if the people data is available) to identify areas for improvement. The analysis can show that certain teams work more inefficiently at certain times, which is often due to a loss of concentration. This enables targeted adjustments to be made to planning.  

The analysis of performance and skills also helps to identify training needs. This allows individual training measures to be planned and implemented.

Transparent shift planning promotes motivation
The tool creates balanced and transparent shift plans. It takes into account individual preferences and qualifications (if documented). This boosts motivation, ensures job satisfaction and helps to increase productivity.

Outlook
After the test phase and further optimizations, the next step is to integrate the legal provisions. The solution can be programmed in such a way that it is helpful in complying with working time laws and break regulations and takes individual preferences into account.

This can reduce conflicts, ensure compliance and improve working conditions. This is because the manual implementation and consideration of labor law regulations can be very complicated. With an automated solution, these requirements can be met better and more comprehensibly.

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In Part 3, we explain how our data science expert goes about developing the AI model for workforce planning: AI-based workforce planning: Creating added value from data (Part 3/3).

We use data from our customer Hermann Müller Elektrogrosshandel GmbH to develop the tool. You can find out more in this article.