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

Proof-Point
Healthcare

User
Ressource Manager, ​
Manager,​
Planner

Technology
SAP BTP, 3rd Party Tools

Noch Fragen offen zur Resource Planning for Clinical Trials?

We would be happy to talk to you about use use cases, that are not only exciting, but can also be successfully implemented.

Akin Artimac: Customer Engagement
Akin Aritmac
Chief Sales Officer

Your Contact

With passion and cross-industry knowledge, Akin Aritmac supports his customers on their way to successful digitization.
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Tags
AI & Data SAP BTP Simplify IT SAP Business Technology Platform