Testing Building Smart Readiness: Experiences and Lessons Learned from SRI Assessments in the ERKKI Project

The Smart Readiness Indicator (SRI) for buildings is an EU-wide methodology used to measure a building’s capacity to optimize energy efficiency, adapt to user needs, and flexibly respond to signals from the energy grid. The national implementation of SRI assessments will begin in the summer of 2027.

As part of the ERKKI project, we carried out three pilots to test the applicability of SRI assessments in challenging public properties. The project examined how major renovations affect smart readiness, whether assessments can be conducted purely based on digital data, and how artificial intelligence can streamline the generation of assessments.

Three New Perspectives on Assessing Smart Readiness

At the Yrjönkatu Swimming Hall, we examined how a major renovation affects the smart readiness of a protected, historic property. The assessment was carried out by comparing the situation before and after the renovation. As a result of the overhaul, modern building services technology was introduced, enabling demand-responsive control and improved monitoring. Consequently, the SRI score rose from the original 20% to nearly 47%. The results showed that even though smart readiness is not explicitly targeted during renovation planning, major overhaul significantly increases the rating. Achieving a higher score, however, would still require separate investments in properties, such as solar panels or EV charging points.

For Maunula House, we piloted the generation of an assessment in collaboration with Granlund Oy, utilizing digital data sources. The idea was to investigate the state of current building information models (BIM) for producing an SRI assessment and how digital data management could be developed so that future evaluations can be produced with minimal resources, field visits, and interviews. The assessment was conducted using remote connections to building automation, IFC building information models, equipment lists, and an energy audit report. Based purely on digital documentation, the resulting SRI score was 30.7%. When refined through an expert interview, the score rose by only about one percentage point to 32.1%. The study demonstrates that while required information is relatively comprehensively available, the biggest challenge lies in data fragmentation. High-quality digital material can get very close to reality without an on-site visit.

In the Malmitalo pilot, we tested how assessments could be produced with AI assistance. The aim was to explore how fragmented documentation, such as energy performance certificates and operational descriptions, can be rapidly processed by AI into scoring compliant with SRI criteria. AI was found to be effective in searching for technical keywords and consolidating information, but the work still requires expert validation and precisely structured prompts to function reliably. Based on the study, AI could support property owners in portfolio-level assessments, allowing lightweight evaluations of large numbers of properties to identify sites where additional measures are required to verify assessment accuracy.

Lessons and Recommendations for the Future

The project’s most significant finding relates to the state of data management across Finnish building stock. Although necessary information exists, it is often “siloed” and scattered across different systems, maintenance logs, and expert memory. When data must be searched, filtered, and verified from multiple sources, SRI assessment becomes a laborious process. To scale SRI assessments across large property portfolios, attention must be paid to the structured nature and availability of building metadata as early as the design phase.

Good data management is essential for easing assessments, but conversely, assessments can also be used to evaluate and improve the state of data management. The SRI should not merely be a “tacked-on” certificate; conducting assessments should generate added value for the property owner. Therefore, it is most natural to integrate assessments into existing processes, such as major renovation planning. Setting smart readiness goals during the initial project planning phase helps avoid technology silos and ensures investments genuinely improve building flexibility and user experience. For example, the Yrjönkatu Swimming Hall case demonstrated that energy efficiency improvements and smart controls go hand in hand, yet grid-level flexibility remains the largest development area for many properties.

Current building information models serve geometric design well, but the technical metadata they contain is not yet sufficient for fully automated SRI calculations. In the future, building information models should be linkable to other data sources regarding system functional levels and control zones. This would allow the SRI score to update nearly in real time via a building’s digital twin, serving as a continuous management tool rather than a one-time audit.

Conclusions

The SRI pilots in the ERKKI project demonstrated that measuring building smart readiness can be successfully carried out using a variety of methods. The greatest potential lies in leveraging digitalization: by improving data structures and automating data collection, cost-effective and comparable information on property portfolio condition can be generated using tools like AI. For property owners, the SRI can provide a roadmap guiding future development—revealing which systems need the most improvement and how a property can better serve both its occupants and the surrounding energy grid in the future.

While the national implementation of SRI assessments launches in the summer of 2027, we recommend property owners start preparing now by managing and ensuring the quality of baseline data, enabling future assessments to be conducted cost-effectively. Better utilization of digital information models and building automation data will be key to scaling SRI assessments across broader property portfolios.

The ERKKI (Optimization of Energy Efficiency in Challenging Public Cultural and Leisure Properties) project is co-funded by the European Union (ERDF). The project is implemented in cooperation with Green Net Finland. The project generates concrete experiences and lessons learned from utilizing new technologies and services in properties and promotes dialogue between public property owners and companies so that new solutions adapt and scale across different building types.