The Challenge
An institutional investor faced operational inefficiencies that limited scalability in its real estate portfolio. With 10 service providers managing 100+ properties across North & Latin America, UK & Europe, and APAC - inconsistent Excel submissions forced teams to spend extensive time on manual formatting and validation. Teams also struggled with reconciling data discrepancies and preparing reports spanning office, retail, multi-family residential, industrial, and mixed-use properties, while the fragmented technology stack created audit trail gaps and compliance challenges. The investor wanted to proactively address the manual processes that could potentially hinder the investment portfolio’s growth trajectory and ability to deliver timely and trusted insights to inform investment strategy and capital deployment decisions.
The Solution
The proposed solution focused on creating a consistent way to bring in information, automating how that information is gathered, and connecting it seamlessly to the investor's existing Snowflake data warehouse. Cherre configured the platform to handle the investor's specific reporting needs while being flexible enough to grow with their portfolio and easily incorporate industry data standards initiatives.
The Results
By implementing Cherre, the institutional investor achieved immediate wins in improving data aggregation capabilities, supporting data quality imperatives, enabling timely reporting, and unlocking data confidence across its real estate investments. The outcomes included:
- Cost-effective Data Ingestion – Effectively addressed data collection gaps facilitating transparency, analytics and setting the foundation for AI.
- Systematized General Partner (GP) Collaboration – Cut down on administrative burden of back-and-forth emails and questions by giving GPs clear, standardized processes.
- Streamlined Internal Data Operations – Eliminated repetitive Excel work through automated ingestion processes, enabling faster transformation of raw GP submissions into reporting-ready datasets.
- Enhanced Data Governance – Improved data quality and reduced operational risk through consistent validation rules, standardized chart of accounts, and full data traceability.
- Scalable Data Management Foundation – Established workflows that can accommodate diverse file types as well as make it easy to onboard new partners and properties.
Why Cherre?
Cherre's institutional knowledge and proprietary data models proved essential in addressing large-scale data normalization, validation, and aggregation challenges. Cherre proved to be not just a technology solution, but a long-term partner in solving for the client's unique architecture and evolving roadmap requirements for long-term scalability.
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