The population is getting older and, at the same time, there w ill be a less percentage w ho can pay for the resources in healthcare by means of taxation. Surgical operations are the most expensive field in secondary care. This is a staff-intensive business that is complex to plan and operate. In some regions, w aiting time for surgery is long and suspended operations are a fact due to resource shortages. Today, all planning and scheduling of personnel and operations is done manually. The purpose of Sownder is to provide decision support for efficiency in operations. This decision support consists of three parts: (i) scheduling; (ii) automatic data analysis and prediction; and (iii) analysis and continuous monitoring of operations using key ratios. The scheduling part is modeled based on the concept of w orking w ith parallel operations for scheduling operations and personnel. This concept reduces operation turnover time. Technologies used are mainly based on mathematical optimization, simulation and machine learning.