The goal was to improve the real estate utilization by using new technology. The users of the space and stakeholders were taken into account, and various information systems were connected into each other. With a new mobile application, the use of the spaces was made easier and utilization improved by more than 26 percentage points (more than double).

Industry maintenance required accuracy and real-time information to improve everyday work. IoT sensors were installed into the right places, and various information systems and information models were used to create a real-time AR view for maintenance workers. The workers can now see the correct maintenance part or target in their view, with real-time information to help them.

A normal apartment housing system required the design of everyday services. The residents, owners and service providers were gathered into one service, which allows them to choose and acquire their own service for living and support. The resident satisfaction indicator improved, and old ways of working changed. The concept was taken into use in multiple locations.

Performance results had been measured for a long amount of time, but none of the factors affecting them had been identified in concrete terms. By clustering the results and using reinforced learning (Bayes theorem) technology we were able to create a platform that can create result forecasts.

The current product-based business model became outdated due to increasing competition. The customers were ready to change from one-time purchases to service payments and service indicators. By creating process indicators both supplier and buyer got a real-time view of the current state of the business and development areas.