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Real Estate Environmental Data

Environmental, Social and Governance (ESG) initiatives have become a top priority for the real estate industry, and provide a unique opportunity for collaboration between investors, owners and occupiers. While what they do with the data may vary, they share a common need for real estate environmental data that’s collected at the asset level that’s accessible, consistent, transparent and can be exchanged across multiple systems. A data standards-based approach becomes a catalyst to attract more investment in real estate and address regulatory requirements that require reporting of real estate environmental data, including greenhouse gas emissions.
The time is now to dramatically improve the flow of environmental data between these stakeholders and across the industry, linking asset-level data with portfolios and attracting new investment in funds based on improved enviromental capabilities and performance. OSCRE's focus is on the environmental data standards needed to go beyond real estate reporting for ESG, and to help integrate data source from diverse systems and platforms many of which are managed by others.
 
“At Brookfield, sound ESG practices are integral to building resilient businesses and creating long-term value for our investors and other stakeholders,” said Pourhashemi. “Our industry, however, continues to face significant challenges with collecting, validating and reporting on ESG data as well as on other meaningful metrics. Through my new role at OSCRE, I’m excited to tackle these challenges to help drive the industry forward.”
- Soheil Pourhashemi, 2022/2023 OSCRE Chairperson of the Board, and Senior Vice President, Head of Technology at Brookfield Properties

If you’d like to know more about OSCRE’s Data Standards Initiative, please email us at info@oscre.org for more information.

Assessment of the Current State of ESG Data

  • No current standards for ESG data exchange
  • Limited ability to integrate ESG data along the supply chain
  • Integration problematic from asset to portfolio level
  • Regulatory reporting requirements expanding
  • Focus must be more expansive than reporting

OSCRE Focus - Solving ESG Data Challenges

  • Data integration is a priority
  • New standards extend the existing OSCRE IDM
  • Corporate governance relies on effective data governance
  • ESG data management practices are key to improvement

ESG Data Standards

Why Standards-based Master Data Management is Essential for Portfolio Management

 

The ability to extract value from data is becoming a competitive differentiator for organizations involved in real estate portfolio management. Companies that optimize the use and management of this important resource can make better decisions faster, enabling them to maximize opportunities and minimize risks more effectively than their peers. But before they can attain that capability, organizations first have to identify the data that’s critical to the operation of their business and then implement procedures to establish and maintain the quality of that data. That’s where standards-based master data management (MDM) comes in.

The importance of MDM in the real estate sector was recently a key topic at the March OSCRE Innovation Forum. Leading industry experts, including Bill Harter from Visual Lease, Tracy Jefferson of EBUSINESS STRATEGIES, Shannon Prince from CBRE Investment Management, and OSCRE Technical Director Chris Lees, shared their insights during a session moderated by OSCRE CIO Ian Cameron. Among the topics discussed:  

 
The High Stakes of Getting a Handle on Master Data for Portfolio Management

Almost two-thirds of organizations manage at least 1 million gigabytes of data, according to an AvePoint report. Within that vast ocean of data is master data, information that the organization uses to describe and operate its business. For companies involved with real estate portfolio management, this master data can include details on tenants, employees, properties and assets.

When we talk about identifying master data, it’s not that organizations have lost this essential information. The problem is that it’s being stored in different formats and repositories that make it difficult to access and work with centrally. For example, you may learn that a heat pump at one of your properties has been recalled by the manufacturer due to faulty wiring. This defect can pose a fire hazard, so it’s important to know if that equipment is also in use at other properties in your portfolio. If information on assets is only kept on-site, for example on a facility manager’s laptop or a piece of paper in a file folder, getting those units serviced and eliminating this risk promptly becomes much more difficult and time-consuming.

In the early stages of building an MDM framework, organizations will flag that equipment information as critical. Once that framework is implemented, not only will the business have an established process for making sure that data is collected and organized in a central “single source of truth,” it will also lay out how the accuracy of that information is maintained. Working with data that’s inaccurate is no better than having no data at all. For instance, it may be that an old heat pump at one of your properties was recently replaced with the model that’s being recalled. If the database is not updated to reflect this change, you end up back at square one in terms of your ability to address a potentially serious issue quickly.

Given this stark example of the value of master data and the importance of MDM, implementing an MDM framework would seem like a no-brainer. Yet, according to a recent OSCRE poll, more than two-thirds of real estate organizations either have no strategy for master data or are just beginning to develop one. 

 
Overcoming Challenges to Implementing MDM

One of the reasons MDM is easier said than done is that it requires close, ongoing coordination between multiple departments, like Finance, Legal and IT. That kind of cross-functional alignment can be tough to sustain. One major challenge is that MDM’s benefits often show up behind the scenes: it’s hard to quantify risks that never became issues. 

Implementing effective MDM also requires an understanding of the concept and its benefits among key stakeholders within the organization. In a previous OSCRE poll, 68% of respondents cited a lack of MDM expertise in their business as a primary obstacle to their organization’s adoption of it. As OSCRE’s Chris Lees pointed out in the Forum, skipping key steps in the MDM process leads to short-lived programs: 
“Organizations that just do one or two shiny things on the path to implementing an MDM framework may get some short-term wins, but they won’t see long-term success,” said Lees. “Give it a few years and those data management programs, in my experience, tend not to last.”

One way to overcome these obstacles is to align your data management strategy with your business strategy. Explaining the concept of MDM in the context of real-life initiatives and projects will make its value and potential benefits easier to grasp for stakeholders. Following that up with regular updates about how MDM will accelerate progress toward major goals and objectives can help keep the process on track over the long haul.


The Role of Data Standards in MDM for Portfolio Management

Making data standards the foundation of your MDM framework ensures that every user or producer of a data stream – whether it’s property addresses, lease renewal dates or floorspace – is referring to it in the same way. No more pounds here, kilograms there, or month/day/year in one place and day/month/year in another. This consistency is key to enabling scalability and interoperability, as well as aiding in regulatory compliance and reporting.


Incorporating data standards into your MDM program not only enables you to get the most out of your master data, it’s also key to maximizing the ROI of workplace management solutions, facility maintenance tools and advanced technologies like automation and generative and agentic AI.

 

Getting Started on Standards-based MDM Implementation

For organizations involved in real estate portfolio management, avoiding the quagmire that untamed data can create and harnessing the power of master data comes down to developing and maintaining a robust, standards-based MDM program. OSCRE’s Industry Data ModelTM (IDM), which was developed over nearly 20 years by real estate owners, occupiers, investors, service providers, leading software companies and others, can support your data standardization efforts. It provides a framework for core real estate functions with more than 130 use-cases including leasing, space management, facilities management work orders and investment management.

If your organization is ready to take the next step toward smarter portfolio management, consider how standards-based MDM—and communities like OSCRE—can support your journey. Click here to learn more about OSCRE membership. 
 

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