Algorithm design for finding the best matches of employees with the planned project

The objective of this diploma thesis is development of a tool for improving the allocation of human resources. The tool is developed as a response to the specific needs of the Enehano company in the area of increasing the efficiency of employee allocation. The work also creates new data structures to hold information related to this area and creates semi-automated processes to create new records of these data structures. The entire solution runs on top of the CRM platform Salesforce, which Enehano uses. A necessary condition for implementing a work solution in another company is the ownership of an Enterprise license, and an optional condition is the ownership of a Tableau license with a Tableau server, which will allow implementing the proposed improvement of reporting. The thesis discusses the advantages and disadvantages of different types of employee workload data storing and allocation requirements storing. Its conclusion on this topic is that keeping data at a lower granularity (weekly) result in approximately 80% data savings. On the other hand, data with a higher granularity (daily) brings new possibilities in evaluation and reduces the discrepancy with the data on the actual utilization of the employee, which in most cases is in the daily granularity. This disparity then results in the necessity of creating many validation conditions and transformation components to connect these two objects. The work also provides methods by which variables can be obtained on the matching of the employee's qualities and free time with the new position.