Building better: Key takeaways from BOMA Canada’s 2024 Digital Transformation Report

Building a data program is a complex journey that requires deep thought and teamwork to achieve success. Companies across most sectors recognize the value of data and have been collecting and analyzing it to improve business outcomes for years.

While the real estate industry hasn’t evolved nearly as quickly as others, a growing number of real estate businesses are realizing the value of data and are creating strategies to get the most from their buildings and operations. BOMA Canada’s second digital transformation report discusses what it means to become a data-enabled organization in the real estate space and analyzes current trends in the industry.

What are the key takeaways from the report?

BOMA Canada’s second digital transformation report interviewed real estate professionals and data experts to gauge the current state of the industry and identify trends in digital transformation. These are the key takeaways from the report:

The importance of data analytics

While pandemic lockdowns are over, COVID-19 made people reconsider what they want out of office and retail spaces — and the impact is still being felt years later. However, real estate companies have realized the potential that Internet of Things (IoT) technology offers to help them move forward and meet these evolving expectations.

Data-collecting sensors and cloud technology make it easier to gather and analyze large amounts of information. This helps real estate businesses understand how buildings are being used and make the necessary adjustments to improve performance. Those that fail to adapt to a changing landscape risk being left behind — as it will be challenging to innovate and leverage new technologies such as artificial intelligence (AI) without a solid data foundation.

Driving factors for digital transformation

The report uncovered two key areas driving digital transformation in the real estate space. These areas are:

• Improving operations and decision-making
• Enhancing the tenant experience

Real estate companies are recognizing the important role that a comprehensive data strategy plays in helping businesses realize their strategic goals. Companies that have developed a data strategy are able to make decisions more accurately and efficiently, identify and assign metrics to manage performance, and ultimately improve operations.

Additionally, expectations for the tenant experience are evolving and companies are realizing the crucial role data plays in helping them continue to meet these shifting expectations. Sensors can help identify how a property’s amenities are being used, and leveraging analytics on that data can help define which tenants are most likely to use which types of spaces. This helps enhance the tenant experience while also laying a solid data foundation to help businesses leverage the potential of AI.

Ensuring data collection aligns with business goals

Before getting started on the data journey, real estate businesses must ensure they are collecting the right data. It is also vital for companies to ensure the data is of good quality (e.g., accurate and complete), and to determine how they are going to leverage that data, such as through generating insights, developing products, etc. This involves understanding what data you are collecting, and how it aligns with your both your tactical and strategic business objectives.

Additionally, ensuring data quality is crucial to capture the information businesses need to succeed. To continue the previous example, data-collecting sensors must be installed in the right location and correctly calibrated to gain important insights into occupancy and space utilization. This helps businesses understand how each building is performing and make informed decisions to improve energy consumption or space utilization.

The rise of data strategies

Real estate businesses understand the important role data strategies play in helping them achieve their goals. Data strategies typically include defining business objectives, assessing the current state of data maturity, identifying the data needs of the business, and establishing a data governance program.

Additionally, defining data architecture, selecting the right tools, and ensuring data security and compliance are key areas of focus. Rolling out the strategy in prioritized phases, fostering a data culture within the business, and scaling and adapting the strategy as needed are also identified as vital elements to achieve success.

Stages of the data journey

Data becomes more mature and insightful as businesses progress further along the data journey. During the beginning stage, businesses generally focus on developing usable data — or that the data is captured, usable, and clean. Companies typically spend 20 percent of the time analyzing data and 80 percent of the time wrangling data into usable form in this opportunistic stage.

Companies increase analytics during the second, or systemic, stage. The split between wrangling new data and analyzing data is divided equally in this stage and the company begins to make real progress as they use this data to make informed decisions. At the final, or differentiating, stage of the data journey, organizations report spending around 80 percent of their time making data-informed decisions and just 20 percent of their time wrangling new data.

Teamwork as a key factor to success

Businesses identified teamwork as a critical element of achieving their data-focused goals. Those building an in-house data strategy must ensure that key roles, such as chief data officer, are filled to achieve their objectives. Additionally, encouraging ownership and accountability across departments further helps ensure the strategy spans all aspects of the organization.

Real estate companies that don’t have the resources to build an in-house data strategy often consider working with strategic data consultants. These consultants help assess the unique needs of the business and find cost-effective solutions to help companies reach their data goals. Some companies opt for a hybrid model that allows them to maintain control over sensitive data while outsourcing specific projects.

Moving from plan to practice

In BOMA’s second digital transformation report, real estate companies that have successfully moved their data strategy into action shared several key elements that supported their success. Assessing their current data estate and standardizing the data they already had on hand enabled them to define their data into one consistent definition that could be used across the company without discrepancies. Additionally, forming a data governance committee and creating data stewards to ensure the quality of data and champion it within the organization played a crucial role in successfully moving their plans into practice.

Companies state that selecting which metrics to focus on based on business objectives can help ensure the strategy is successful. For example, a business may want to focus on operational metrics and environmental, social, and governance (ESG) data such as energy usage. Additionally, creating a classification system that reflects the processing stages of data — from raw data to data that has been fully verified — can help support the success of the data strategy by showing when data is ready to be used in reporting.

Change management: Keep it going

Real estate businesses identify change management as a crucial element of implementing a successful data strategy. This involves getting directors and other important people in the organization to embrace the new standards and act as data champions. Companies stress the importance of making people feel involved in the process to increase the probability of success.

Getting employees on board involves creating a change management program and sharing data with key stakeholders and the wider business to ensure everyone is on the same page. Creating a steering committee that meets regularly with executives and measuring progress with key performance indicators (KPIs) are cited as key pillars to help businesses achieve their data strategy objectives.