Energy data collection

The measurability and traceability of sustainability goals is playing an increasingly important role for real estate owners. Members of the Asset Management Association Switzerland (AMAS) are required to publish all environment-related key figures in a standardised format. There are also binding standards at European level in the form of the EU Taxonomy and the CSRD. However, the reporting of ESG data is very time-consuming and laborious, as the necessary data is often stored in different data sources or has to be collected in a structured manner in the first place. The manual collection and preparation of data for the various standards and benchmarks is time-consuming and, above all, error-prone. ESG Data Management can automate these processes and guarantee high data quality at the same time. This frees up resources to focus on the essentials: analysing the data and optimising the building stock.

The collection of energy data is crucial for ESG reporting. Our smart ESG application co₂lect supports you in the collection, management, processing and quality control of your consumption data (energy, water, heat).

More and more owners are collecting their energy data via smart meters. The data can be aggregated and integrated directly into co₂lect. If no smart meter solution is yet available, some of the data can be obtained directly from the energy company in structured form or there is an interface to their source system.

Until all data collection processes are automated, consumption bills often remain the only source of data. To avoid having to laboriously read these out by hand, we have developed an intelligent AI-based algorithm that can automatically read the data from PDF invoices or even scans of invoices and integrate it directly into co₂lect.

A combination of human and artificial intelligence is used to automatically check the quality of the data integrated into the ESG infrastructure. These are rule-based and check, for example, whether a value is within the defined range of last year’s value. On the other hand, outliers in the data are identified, i.e. data points that deviate significantly from the general mean are reported.

The results of the various data quality checks are processed in an interactive quality report. This report enables to quickly find errors and warnings in the data.

The pressure for sustainability from investors is also increasing for smaller property owners. Various associations such as AMAS, KGAST and ASIP have defined environment-related KPIs that must be published. European standards such as DNK or ESRS have also defined reporting guidelines. All standards now require detailed data on the energy consumption of all properties in the portfolio.

Often, smaller companies in particular do not have standardised processes for collecting this data, and the data is collected manually in a time-consuming process. This is not only time consuming but also prone to error.

Our data infrastructure and the associated co₂lect application are flexible and can be tailored to individual requirements. For example, if only the AMAS KPIs are relevant, the data infrastructure is correspondingly smaller and primarily processes all energy consumption data. Automating the data collection and KPI calculation processes saves a lot of time and ensures high data quality.

Our ESG data infrastructure can also be continuously adapted to new and growing needs by integrating new data sources and generating additional metrics.