Visma Optimization Technologies
We love challenging problems. And we love to solve them.
We have customers who struggle with some of the most challenging and complex mission-critical problems every single day. Our job is to find those customers, identify their problems and solve them. By dedicating ourselves to the latest research within artificial intelligence, particularly machine learning and optimization, we seek to significantly improve the operations of our customers within healthcare, education and the private sector.
By empowering clients with user-friendly, analytical tools in the cloud, we radically transform their manual processes into competitive advantages, enabling them to make powerful and informed decisions.
How we work
Nurse route optimization
In Norway, more and more elderly are receiving health treatment in their homes, creating a burgeoning in-home care industry. Until 2019, routing nurses to the right house at the right time was done manually—an extremely difficult and complex task. With just 3 nurses and 30 patients, the number of possible routes exceeds the number of atoms in the universe.
In Fall 2019, Visma Optimization Technologies launched Visma Flyt Route Planner—an application that uses techniques from AI and Operations Research to help home nursing care optimize its travel routes. The app allocates patients to nurses and determines the best route for each nurse to take. The results have been remarkable. Nurses can now spend 10% more of their time—the equivalent of 2 extra cups of coffee per day—with patients. We are now looking to take the Route Planner to other markets such as mail, trash, and food delivery services.
Making a school timetable for the year ahead is a time-consuming and frustrating process for people to do by hand. There are many moving parts such as available rooms, competent teachers, time slots, required subjects, and necessary hours.
Through Visma InSchool, we have provided an automated timetabling solution that reduces substantial time, effort, and inaccuracy. The solution assigns lessons to rooms, teachers, and time slots based on the type of class, room capacity, schedule, and teacher competencies. This decision-making can also be customized based on user priorities and will present a proposed timetable for administrators to accept or modify as they see fit. The solution was first available to Viken county in Norway for the 2019 timetabling season. We are currently rolling out the solution to a larger selection of schools.
Each municipality in Norway is responsible for carrying out annual kindergarten admissions, with the goal of allocating children to preferred kindergartens. However, there are national, municipal and kindergarten-specific legislations that complicate the admissions process. Moreover, the suggested allocations are far from optimal and many children are not allocated to their desired kindergarten. As a result, the problem is demanding to solve manually, and it can take months to produce an allocation that satisfies all needs.
To improve the admissions process, we are developing the Kindergarten Admissions Optimizer which applies techniques from Operations Research to create an optimal allocation of children to kindergartens within seconds. This gives teachers more time to develop learning resources in the kindergarten and maintain close contact with guardians. Also, the admissions optimizer can be configured to ensure balanced age and gender distributions, as well as minimise the average traveling distance for parents. The admissions optimizer will be launched in 2020.
For a business, hospital, factory or any other organisation, scheduling employees to shifts in an efficient manner is critical when facing fluctuations in demand. The already tedious task of forecasting and meeting daily requirements in staff competence is complicated further by laws and employee preferences. The result is a repetitive and time-consuming process that can lead to inadequate and unfair schedules.
In the workforce management project, we have developed an optimization solver that, within minutes, optimizes shift allocation, thereby automating many workforce scheduling processes. The solver assists schedulers in creating fair and efficient schedules that also adhere to laws. It will be launched as a module in the Medvind WFM solution in the Swedish market in Q1 2020. Later, we will adapt the solution for the Norwegian and Finnish markets as well.
Join the team
If you care about the societal impact of your work and possess the diverse set of skills needed to adequately solve complex, real-world problems, we are very interested in getting to know you. We look for highly skilled people with a passion to challenge the status quo. If you have a background from optimization, artificial intelligence, machine learning, infrastructure, or cloud technology, get in touch with us.
Oslo, Norway / Dublin, Ireland / Stockholm, Sweden / Riga, Latvia