Real estate fund managers are not short of data; they are short of usable insight.
Our Global Head of Sales, Karl Salamangi, recently moderated a webinar exploring the importance of data visibility in real estate. The panel featured Lynn Peters, our Director of Global Operations; Will Robson, Executive Director of MSCI Research and Development at MSCI; Karen Martinus, Senior Vice President of Research and Investments at Affinius Capital; and Shreya Sheth, Head of SmartLab and Director of Investment Management at Patrizia.
Over the course of the discussion, a consensus emerged between the panellists that data exists across systems, teams, and service providers, but rarely connects in a way that supports timely decisions. As Lynn put it, the industry is “information rich, but insight poor.”
For Shreya, it’s clear that fund managers often operate with “hidden inefficiencies,” not because processes are inherently flawed, but because they lack transparency on where value is lost. In tighter capital markets and under increased investor scrutiny, this lack of clarity is becoming harder to absorb.
Data fragmentation is causing hidden inefficiencies
Most real estate platforms rely on multiple systems spanning property management, accounting, reporting, and asset management. According to Shreya, data flows between them are often manual and inconsistent, resulting in duplication and delay, with “the same data recreated three to four times across different functions,” adding cost and increasing the risk of error. By the time information reaches fund-level reporting, it is often already outdated.
The problem is exacerbated by the fact that these inefficiencies are not always visible. They surface as slow reactions to issues such as leasing performance, capex overruns, or operational risks. According to Will, the challenge is that data is often “siloed to specific use cases and doesn’t flow well across the ecosystem,” leading to repeated effort and inconsistent outputs.
AI is delivering value where data is usable
While AI dominates industry discussions, its most immediate value is operational. Lynn highlighted that current use cases focus on “automating data-intensive processes, not replacing investment judgment.”
AI applications are most useful when they reduce manual workloads and allow teams to focus on analysis and decision-making. Karen reinforced this point, noting that AI should “free up time for higher-value workflows,” rather than act as an end.
From reporting outputs to decision inputs
Historically, operational focus has sat with investor reporting. Much of the effort has gone into producing accurate outputs, often with limited connection to internal decision-making.
That is changing. Shreya observed that data flows are increasingly being linked to “actual asset-level decisions, not just reporting outputs.” The goal is to connect operational activity, financial performance, and portfolio outcomes in near real time.
Investor demands are raising the bar
Limited partners (“LPs”) are asking for more consistent, timely, and comparable data. They assess performance across multiple managers and require a common basis for comparison.
Will highlighted that LPs often operate with “thin teams looking across many funds,” making consistency critical. Without a common data format, even detailed reporting becomes difficult to use.
Responsiveness is equally important. Karen noted that the ability to answer investor queries quickly has become a trust factor, particularly in a competitive fundraising environment. Firms that cannot meet this expectation risk losing both capital and credibility.
Combining internal and external capabilities
Most firms are adopting a hybrid model. Internal systems provide control and flexibility, while external providers offer market data, benchmarks, and scale.
Karen explained that her team continues to rely on external datasets but is increasingly “complementing them with internal data,” including portfolio-level insights and extracted information from investment materials.
The focus is shifting toward combining proprietary insight with broader market context. Ultimately, closing the gap in real estate operations is not about adopting a single tool. It is about creating a clear flow of data from asset to investor.
Watch the webinar to hear the full conversation.
