Data solutions for the real estate sector
We make data from asset, property and facility management usable in such a way that portfolios become more transparent, objects more economical and operations become more efficient. From strategy to implementation.
Real estate management based on a common database
The real estate industry is being slowed down by fragmented data and isolated systems. Information is distributed in ERP, CAFM, ticket and IoT systems or in Excel files. There is no consistent view of portfolio, properties and operations.
We help real estate companies break down these silos and create a common database. In this way, portfolios can be managed transparently, properties can be operated more economically and processes can be measured and compared across all service providers. With a modern data and AI stack, we connect existing systems and make information usable where decisions are made. We support you from strategy to architecture and implementation to operationally usable dashboards and AI applications.
Typical questions
Typical questions
- How do we identify, evaluate and prioritize use cases with the highest strategic impact (e.g. churn prevention vs. network data analysis)?
- How do we anchor regulatory requirements (unbundling, EnWG, GDPR) in a uniform data governance concept?
- Which platform architecture allows us long-term flexibility while maintaining security and investment protection?
- How do we establish a central understanding of data across various IT systems, market roles and specialist areas?
Our services
- Development of a holistic data strategy with a top-down and bottom-up approach
- Use case portfolio analysis including profitability assessment
- Development of a role model for data ownership & governance
- Change enablement & organizational development for data-driven work
success stories
For RheinEnergie, we developed a central data strategy that is closely linked to corporate strategy and divisional strategies and supports their implementation in a targeted manner. The strategy addresses decentralized data landscapes and promotes a company-wide self-service culture for data-driven value creation. It provides clarity about roles and responsibilities and defines a common understanding of governance as the basis for scalable, future-oriented use of data.
Typical questions
Typical questions
- How do we identify, evaluate and prioritize use cases with the highest strategic impact (e.g. churn prevention vs. network data analysis)?
- How do we anchor regulatory requirements (unbundling, EnWG, GDPR) in a uniform data governance concept?
- Which platform architecture allows us long-term flexibility while maintaining security and investment protection?
- How do we establish a central understanding of data across various IT systems, market roles and specialist areas?
Our services
- Development of a holistic data strategy with a top-down and bottom-up approach
- Use case portfolio analysis including profitability assessment
- Development of a role model for data ownership & governance
- Change enablement & organizational development for data-driven work
success stories
For RheinEnergie, we developed a central data strategy that is closely linked to corporate strategy and divisional strategies and supports their implementation in a targeted manner. The strategy addresses decentralized data landscapes and promotes a company-wide self-service culture for data-driven value creation. It provides clarity about roles and responsibilities and defines a common understanding of governance as the basis for scalable, future-oriented use of data.
Typical questions
Typical questions
- How do we identify, evaluate and prioritize use cases with the highest strategic impact (e.g. churn prevention vs. network data analysis)?
- How do we anchor regulatory requirements (unbundling, EnWG, GDPR) in a uniform data governance concept?
- Which platform architecture allows us long-term flexibility while maintaining security and investment protection?
- How do we establish a central understanding of data across various IT systems, market roles and specialist areas?
Our services
- Development of a holistic data strategy with a top-down and bottom-up approach
- Use case portfolio analysis including profitability assessment
- Development of a role model for data ownership & governance
- Change enablement & organizational development for data-driven work
success stories
For RheinEnergie, we developed a central data strategy that is closely linked to corporate strategy and divisional strategies and supports their implementation in a targeted manner. The strategy addresses decentralized data landscapes and promotes a company-wide self-service culture for data-driven value creation. It provides clarity about roles and responsibilities and defines a common understanding of governance as the basis for scalable, future-oriented use of data.
- Portfolio performance across all properties is only comparable to a limited extent
- Reporting for owners is created manually from Excel and various systems
- Property and facility management data arrives late or in different structures
- Investment decisions are often based on incomplete data
- Performance, cost and operating data can be compared across objects
- Property and facility management data is available in real time
- Scenarios for investments, Capex or ESG measures can be simulated based on data
- Reporting for owners and management is generated automatically
- Information about objects, tenants, spaces and tickets is stored in various systems
- Processes from tenant inquiries to billing are only partially digitally represented
- Reporting for owners requires manual data compilation
- Service quality and response times of service providers are difficult to measure
- Processes can be measured from tenant concerns to settlement
- Owner reports can be created automatically
- Service quality and response times of service providers become transparent
- Property managers have less time for reporting and more time for operational management
- Maintenance, testing and faults are managed in various tools and Excel lists
- The overall overview of system conditions and maintenance requirements is missing
- IoT and sensor data (e.g. room climate, occupancy, meter readings) are available, but are barely incorporated into operational management.
- Clearly presents maintenance, faults and system conditions
- Makes response times and SLA compliance measurable
- Improved maintenance strategies from reactive to condition-based
- makes costs and operational quality comparable across all properties
- Portfolio performance across all properties is only comparable to a limited extent
- Reporting for owners is created manually from Excel and various systems
- Property and facility management data arrives late or in different structures
- Investment decisions are often based on incomplete data
- Performance, cost and operating data can be compared across objects
- Reporting for owners and management is generated automatically
- Data from property and facility systems is available in real time
- Scenarios for investments, Capex or ESG measures can be simulated based on data
- Information about objects, tenants, spaces and tickets is stored in various systems
- Processes from tenant inquiries to billing are only partially digitally represented
- Reporting for owners requires manual data compilation
- Service quality and response times of service providers are difficult to measure
- Processes can be measured from tenant concerns to settlement
- Owner reports can be created automatically
- Service quality and response times of service providers become transparent
- Property managers have less time for reporting and more time for operational management
- Maintenance, testing and faults are managed in various tools and Excel lists
- The overall overview of system conditions and maintenance requirements is missing
- IoT and sensor data (e.g. room climate, occupancy, meter readings) are available, but are barely incorporated into operational management.
- Clearly presents maintenance, faults and system conditions
- Makes response times and SLA compliance measurable
- Improved maintenance strategies from reactive to condition-based
- makes costs and operational quality comparable across all properties
How we have already successfully supported other real estate companies
Modern data architecture
Together with Aachener Grundvermögen, we have set up a modern, data-based infrastructure that supports the efficient handling of large amounts of real estate data. The use of the data vault approach ensures high data quality. At the same time, a flexible architecture is being created that enables both the connection of various source systems and future expansions without any problems.
Our solutions for network providers
Transparency about network investments & maintenance measures
We provide an overview of investment planning and maintenance — from medium voltage to local network level. With comprehensible data and visualizations for technology, controlling and regulatory reporting.
Securing grid stability through intelligent processes
We support you in implementing legal requirements such as Redispatch 2.0 — with sophisticated data processes that reliably combine generation, network operation and planning.
Integration of geodata & spatial reference into BI landscapes
We integrate geodata into existing BI systems — e.g. for network expansion planning, capacity assessment or location decisions. This makes spatial reference an integral part of data-based decisions.
Reliable automation of market communication
We make market processes such as supplier changes, MaKo2024 or format changes robust and maintainable — through clean data structures, automated test tracks and clearly defined workflows.
Data-based control of network connections
We help structure and accelerate grid connection processes for PV systems, charging infrastructure or heat pumps based on data — with automated preliminary checks, bottleneck checks and transparent monitoring.
Cross-project reporting governance
We help build a consistent reporting landscape across projects and specialist areas — with coordinated key figures, clear processes and sustainable data management.
From data strategy to productive use in everyday real estate. This is how we accompany you on your data journey.
Data Strategy & Roadmap
Together with you, we develop a data strategy that takes all three roles into account and defines prioritized use cases for your organization.
Data platform & integration
We build a modern data platform, integrate your source systems (ERP, CAFM, ticket systems, IoT, DMS, etc.), and ensure stable, automated data pipelines.
Data Modeling & Governance
We model your real estate data in such a way that it is comprehensible, expandable, and evaluable—including clear roles, responsibilities, and quality rules.
Analytics, dashboards & AI use cases
We develop dashboards and advanced analytics solutions that make everyday work for asset, property and facility teams noticeably easier.
Enablement & Change
We empower your teams to work with new data products, develop reports themselves and anchor data-driven decisions in everyday life.
FAQ
When data from different systems is brought together, it can also be used for further analyses and data-driven applications. Analytics and AI make it possible, for example, to identify maintenance requirements at an early stage, to better analyze operating costs or to support investment decisions based on data.
The basis for such applications is always a consistent and high-quality database in which information from asset, property and facility management is linked together.
Many classic software solutions in the real estate sector are optimized for a specific process, such as rental, accounting or facility management. They manage operational data, but are rarely designed to bring together information from multiple systems.
A data platform, for example, supplements these systems by integrating and providing data from various sources in a structured manner. This allows comprehensive analyses, dashboards and data-driven applications to be created without the need to replace existing operational systems.
Companies that use their data systematically can identify developments in their portfolio earlier and react more quickly. This includes operating costs, maintenance requirements or changes in the use of buildings.
When relevant information is transparently available, investments can be planned in a more targeted manner and operational processes can be managed more efficiently. Data is thus becoming a strategic factor for the long-term development of a real estate portfolio.
Short heading goes here
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspend Varius Enim in Eros Elementum Tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat.
From vision to anchored data culture
We help you understand data as a strategic resource — and embed it into your existing corporate strategy. In joint workshops (e.g. data thinking, maturity assessments), we identify key use cases and structure a clear roadmap.
Typical questions
- Which data-driven use cases contribute to our goals?
- How do we incorporate data governance into unbundling requirements?
- What roles and responsibilities do we need?
Our services
- Development of a holistic data strategy (top-down & bottom-up)
- Development of a governance model (including data stewardship)
- Prioritize high-impact use cases
- Change management and data literacy initiatives
Practical example
We have developed a cross-sector data strategy for RheinEnergie — as a blueprint for the entire company.
Medium length section heading goes here
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspend Varius Enim in Eros Elementum Tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat.
Medium length section heading goes here
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspend Varius Enim in Eros Elementum Tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat.
