AI for Resource Planning: Improved Recommendations for Overloaded Personnel


A new AI is being used in resource planning and promises significantly improved recommendations for handling person overload. Unlike the previous AI, this new model is fully capable of learning and is based on the Inverse Reinforcement Learning (IRL) technique. This allows the AI to learn from users and suggest more targeted alternative resources.

Rule-Based vs. Machine Learning: Enhancing Resource Planning with AI

The previous AI operates on a rule-based system with limited learning capabilities. In contrast, the new AI falls under the category of machine learning and is highly adaptable. This allows it to continuously improve and provide more refined recommendations.

In resource planning, project managers often face the challenge of finding an alternative person to replace an overloaded resource. This task involves considering various criteria such as availability and skills. The new AI takes on this task and specifically identifies alternative resources, taking into account individuals in the same department who may have similar skills. This significantly improves the efficiency of finding alternatives.

The AI identifies an alternative person and simulates their availability. By determining if the alternative person is suitable and sufficiently available, the risk situation improves compared to the current scenario. Therefore, the AI suggests an alternative person who can take over the work.

The new AI tool provides project planners with valuable recommendations for evaluating overload risks and receiving alternative suggestions. By taking into account the work already completed, project planners can make informed decisions and reject unsuitable suggestions, prompting the AI to propose additional resources. This streamlined process helps save time and effort for project management, enabling more efficient resource allocation and better mitigation of overload situations.

The new AI system brings numerous benefits to users, including time savings in resource research, enhanced knowledge of resource capabilities within the organization, and improved solutions for resource overloads, resulting in more balanced workloads. Additionally, it facilitates the onboarding process for new project managers and enables advanced analyses such as identifying key resources. Further application areas for the AI system are expected to be explored in the coming months.

The new AI has already proven its worth in practice. After just a few weeks, the suggestions from the neural network were adopted by project managers in 80% of cases. The time savings for users were deemed significant. The AI is continuously being developed to make even better suggestions.

The next generation of AI will introduce additional feature enhancements and provide the capability for users to submit their own suggestions. Furthermore, efforts are being made to develop a model that supports even more precise planning. This will allow for more customization and user input, empowering individuals to contribute to the resource planning process. The focus is on improving accuracy and flexibility, ensuring that the AI system adapts to the specific needs and preferences of each user.

Overall, the new AI provides a more efficient and adaptive solution for resource planning. It saves time, enhances planning quality, and alleviates overloaded resources. With further advancements and application areas, the AI will bring even more benefits in the future.

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