The Digital Building Lifecycle: Taking the Long View

In recent decades, the global architecture, engineering, construction, and facilities operations (AECO) industry has been falling behind technologically. Building projects have become like highly calibrated machines, with complex mechanical and information technology systems and increasing numbers of stakeholders, but the processes and tools for managing them have remained nearly unchanged. Project records take the form of static documents and files instead of machine readable, transoperable data and information. Data is siloed, fragmented, and not optimized for long-term proactive maintenance or predictive facilities management.

The digital age is bringing a better way—and at the Microsoft real estate group we believe it is poised to disrupt the AECO industry’s business-as-usual. We call it the digital building lifecycle approach: a method of using data to deliver built environments with higher total performance at lower total cost. Our real estate group and partners are working toward a digital future, using new business models, processes, and tools that empower the digital building lifecycle approach—changes that could influence the entire AECO industry.

Virtually “building,” simulating, and analyzing projects during the design and pre-construction phase avoids costly mistakes. Digital construction and digital supply chain support implementation of the physical artifact, while digital platforms support the proactive maintenance and predictive operations phase. Accumulating cradle-to-grave building data supports discovery of the most cost-effective ways to disassemble the physical structure to recyclable and reusable resources at the end of its lifecycle.

How is this digital approach achieved? Our digital replica of the physical environment, Digital Twin, consolidates building information models (BIM) with information gathered from the physical environment through IoT sensors, end-user experiences, and reality capture. Data is further refined and processed into information that can be shared and consumed on transoperable digital platforms. Post-occupancy evaluations are performed and overlaid with data for Artificial Intelligence analysis. Now, with data powered by AI, we can bring to light patterns in asset maintenance, visualize building occupancy lows and highs, and predict future need for space. All stakeholders can access the latest and greatest information available for them, and proactive maintenance and predictive operations are enabled. 

The digital building lifecycle method supports data-driven decision making. The total performance of different design options can be compared, analyzed, cost-engineered, and optimized. In the pre-construction phase, for instance, different building materials can be assessed for how they affect the working environment in terms of acoustics, indoor comfort, space usability, security, and more.

Say we are making a decision about roofing materials. Copper has the longest technical lifespan, circa 200-250 years, but the initial cost of installing a copper roof is extremely high due to material and skilled labor cost. Tile roof is less expensive, but its total lifecycle is probably 30-50 years, and it brings higher maintenance costs. Layering in another variable—the owner’s investment plans for the building—complicates the decision further. When all this data is integrated onto a single digital platform, options can be compared, costly mistakes avoided, and the total building performance optimized.

Cloud computing with structured and unstructured data on Microsoft Azure can help to identify maintenance issues, like leaks, before they become problems. A machine learning algorithm can process the visual data, revealing problems like a patch of wall gradually darkening with moisture. Being able to monitor such data allows more proactive stewardship of built environments, saving money and resources and sustainably extending the usable lifecycle of the building.These tools then enable users to take the long view of physical, social, and digital environments, by accumulating critical data sets from each lifecycle phase and refining them into information that is applicable for the next users. Pre-planning the end of a building’s technical lifecycle turns waste into reusable recycled resources.

Perhaps the best thing about the digital building lifecycle approach is the wide range of emerging areas it can impact. The tools can enable the integrated solutions that deliver according to different design strategies, such as accessibility and usability, by ensuring adherence to universal design. They can enable the flexibility that is the hallmark of workplace-of-the-future design, allowing our workspaces to morph in size, layout, and assets as teams change. Machine-readable data supports the increasing practice of off-site construction. Workplace analytics can deliver data on how different workspaces are performing, and thus which should be changed. 

All of this enables us to optimize building performance, cost-effectiveness, and employee satisfaction and productivity—benefits that can bring immeasurable value across our portfolio and bring greater alignment among stakeholders. This alignment results in greater profitability, enhanced project success, higher-quality built environments, and more empowered people. Our real estate group will continue to use the business models, processes, and tools that enable this approach, toward a digitally empowered future.

Article #1: The Digital Building Lifecycle: Taking the Long View

Article #2: Digital Building Lifecycle: The Data-Driven Feasibility Study

Article #3: Digital Building Lifecycle: How Technology can Transform Schematic Design