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At Willow, building a “data estate for real estate” speaks to constructing the architecture, systems, and processes that allow built environments to integrate, analyze, and act on operational data in a way that enables insights, automation, decisioning, and intelligence.
A data estate refers to the full scope of data assets, both raw as ingested from sensors and derived or calculated, and the systems, pipelines, and operational layers that make that data usable for insights and actions. As data streams are ingested from existing systems, and external feeds, normalization ensures that data from diverse sources is unified to aligned units and ranges and made accessible in a coherent manner. Building on this foundation, a semantic Knowledge Graph and ontology add context, enabling intelligent querying and interpretation. The structure facilitates analytics, computations, AI/ML-driven insights and predictive capabilities.
Outcomes are delivered through multi-modal user experiences, with alerts, control loops, and automation systems to support decision-making and operational efficiency. Underpinning all of this, governance, access control, data quality and security ensure that data is trustworthy, secure, and compliant. Anomaly detection and predictive maintenance close the loop by embedding intelligence into day-to-day operations and enabling continuous improvement.
In a real estate portfolio, the data estate must span many heterogeneous systems like HVAC, lighting, energy meters, occupancy, across thousands of assets, often with varied standards, formats, temporal resolution, and quality.
A key motivation is to achieve unified operational visibility by replacing siloed systems across mechanical equipment, energy, and security, with a single, integrated view for each building and across the entire portfolio. Organizations seek benchmarking and performance comparisons, allowing them to evaluate avoidable cost across energy use, maintenance efficiency, and space utilization. Predictive and prescriptive insights help identify potential failures, anomalies, and opportunities for operational optimization. Feedback loops generate real-time alerts and automated control adjustments based on data-driven triggers.
There is a growing need to support compliance and ESG reporting based on audit-quality real-time data. Finally, scalability and reuse are essential, ensuring that as real estate portfolios expand, the underlying data architecture can grow seamlessly without requiring reinvention for each new building.
Willow’s “data estate” is comprised of these core elements:
1. Ontology: Based on DTDL, this rich classification describes how to represent the real world in Willow. It normalizes data and defines what can be described digitally so it can exist in the Knowledge Graph.
2. Data Models: Also knows as Shapes, leverage the ontology and provide structure on how to set it up for consistency. This is crucial for analytics and AI, i.e. modeling Occupancy Zones with Sensors and Rooms, or HVAC Zones with Terminal Units and Rooms.
3. Data: Willow’s Knowledge Graph, time series or live data streams, documents, events, insights, and work orders all light up the platform.
Here’s how Willow’s platform enables organizations to create a data estate:
Building a data estate in real estate is a complex challenge, with several key obstacles to overcome. Heterogeneous and legacy systems are common. Many buildings rely on outdated equipment, proprietary protocols, and inconsistent documentation, making integration a major initial hurdle. Data quality becomes a challenge when sensors fail, drift, or produce gaps, requiring robust cleaning, imputation, and fault detection processes.
Temporal alignment is critical, as systems often report data at different intervals or with time offsets. Without synchronization, insights can be misleading. Spatial consistency is also essential. The digital twin must accurately map sensor data to rooms, zones, and equipment to reflect the building’s physical layout.
As data scales, performance and storage become key concerns. Time-series data and wide sensor arrays demand efficient pipelines and infrastructure. Governance, security, and privacy must be addressed with clear access controls and audit trails.
On the process side, change management is crucial. Teams must trust and integrate new tools into their workflows for the system to deliver value. Finally, automation of systems via Active Control requires safety mechanisms, fallback options, and well-defined boundaries.
A mature data estate powered by Willow unlocks transformative capabilities across building portfolios. Benchmarking and anomaly detection identifies buildings that consume significantly more energy per square foot even after adjusting for variables like occupancy and weather. Predictive maintenance allows teams to detect early signs of equipment degradation in HVAC systems or pumps before failure occurs, reducing downtime and repair costs. Operational efficiency improves as insights are used to optimize schedules, adjust setpoints, reduce energy waste, and shift loads intelligently. Through automation and control loops, systems can trigger safe responses or provide actionable suggestions to operators.
Willow’s data estate enhances asset lifecycle and investment decisions, helping stakeholders determine whether to repair or replace assets based on data-driven insights. ESG and sustainability reporting offer auditable metrics on energy use, emissions, water consumption, and maintenance. Tenant and occupant experience is improved with occupancy and environmental data-driven enhancements to comfort.
Building a data estate with Willow typically begins with discovery and audit, where teams inventory existing buildings, systems, sensors, and data sources, identifying gaps and assessing connectivity and protocols. A semantic model is defined to standardize naming conventions and map relationships across floors, zones, and equipment. With this foundation, connectors and integrations are deployed to bring in real-time data streams. Spatial modeling with floorplans to map sensors to physical locations enables visualization. Data QA/QC addresses anomalies and establishes baselines for normal operations. Skills are deployed to generate insights, deriving metrics like energy per square foot or load curves, and building models for forecasting and anomaly detection. These insights are surfaced through multi-modal user interfaces, tailored for facility teams, technicians and executives.
Automated workflows can be set up to trigger alerts take action based on thresholds, while governance and access control ensure secure, compliant data usage. The system is deployed at enterprise scale with continuous improvement driven by performance monitoring and feedback loops that refine models over time.
Building a data estate comes with several risks, but Willow provides tools and services to help mitigate them. A phased approach with Willow’s Activate Packs helps organizations succeed with very large deployments as they navigate the journey of becoming grid-aware and eventually grid-interactive. Poor data quality from faulty sensors or calibration issues can compromise analytics. Willow addresses this with built-in data quality checks and Skills.
Buy-in from IT and OT teams is imperative and Willow offers professional development services to support change management. Data silos can develop due to proprietary systems, while scalability must be considered early, as time-series data can grow rapidly. Willow’s architecture is designed to handle this efficiently.
As buildings evolve, the data estate must adapt. With automation via Active Control, Willow ensures a human-in-the-loop approach, maintaining safe boundaries for automation.
In conclusion, building “data estate for real estate” with Willow means creating a robust, scalable, integrated data infrastructure for buildings and real-estate portfolios. This includes ingestion, integration, semantic modeling, analytics with AI, user surfaces, governance, and operational workflows. The goals is to drive performance, insights, optimization, and ultimately transform how real estate is managed.