Ressourcenplanung mit Machine Learning

Resource Planning for Clinical Trials

Increasing the predictive accuracy of clinical trials with an optimized ML model.

Use Case: Resource Planning for Clinical Trials
Managers often face challenges when planning and managing resources, especially in time-intensive and complex projects. A platform that collects historical data from the data warehouse as well as from various SAP systems and enables users to clearly visualize current resource requirements and allocations through robust predictions helps here. 

Cross-project and optimal visualization of the required resources

Three success factors of the Resource Planning for Clinical Trials:

  1. Anticipation of resource requirements with the help of predictions supported by machine learning and simulations​
  2. Reduction of overheads in project planning while improving overall results​
  3. ​Modern solution with user-friendly UI


Ressource Manager, ​

SAP BTP, 3rd Party Tools

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Akin Artimac: Customer Engagement
Akin Aritmac
Chief Sales Officer

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With passion and cross-industry knowledge, Akin Aritmac supports his customers on their way to successful digitization.
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