Burgos, November 18, 2022.- I have read the Whitepaper: “Leveraging Artificial Intelligence and Automation for Return on Investment in Innovation. Architecture, Engineering, and Construction Sector”. A document that analyzes the current situation faced by construction professionals. First of all, for the diagnosis of the following circumstances and their immediate impact on the present (in the short term). I extract the following annotations:
The architecture, engineering, and construction (AEC) industry has a complex relationship with innovation, often embracing new ideas in theory while hesitating to actually innovate due to practical and cultural limitations that disincentivize experimentation. Regulatory and contractual barriers often stand in the way of innovation, and the industry is highly fragmented, operating with low margins, high risk, and complex demands stemming from urbanization, population growth, labor shortages, and limited resources.
AEC’s project orientation, where an array of separate contractors comes together for one-off builds, often means every activity must be billable, contracts must focus on avoiding risk and litigation, and razor- thin margins give leadership further reason to stick with what’s proven. Cultural and business practices built around these conditions reinforce conventional ways of working.
The pressure to embrace innovation must be strong to overcome the obstacles. There’s a lot happening in the current marketplace to ramp up that pressure, and AEC firms are responding. It takes organizational, cultural, and technological changes to drive greater adoption of innovative ideas and mindsets. Experts interviewed for this report recommend the following steps for AEC organizations to overcome obstacles and increase innovation.
Learn from example. One strong force is proof among an organization’s direct peers. “This industry is exceptionally peer influenced,” says Stephen Jones, senior director of industry insights research at Dodge Data & Analytics, a New York construction research firm. There’s also a fair bit of wariness around vendor claims, so it takes enough data about results and what it actually takes to achieve them to drive the belief that failing to adopt new technologies and approaches will harm the business. “That’s what’s going to begin to pull things in,” he says.
Lessons from the past suggest that more aggressive adoption of new technologies and approaches can pay off. Most AEC firms were reticent to adopt what’s now known as building information modeling (BIM) in the 1990s, recalls Martin Fischer, professor of civil and environmental engineering at Stanford University. One Finnish mechanical engineering firm, Granlund, that did embrace BIM early on went on to become one of the few to thrive through a subsequent economic downturn and, in turn, expanded its role to become a primary consultant to building owners, Fischer says. “They dramatically expanded their footprint in the project and building life cycle. You can put it directly back to that strategic decision to invest in this innovation.”
Restructure contracts. Structural changes can also address the disincentives to innovate. Integrated project delivery, a collaborative approach to building that includes multiparty contracts, has been highly effective at encouraging greater collaboration across subcontractors, says Dodge’s Jones. Other experts point to insurance and other legal vehicles to share the risk that otherwise makes AEC organizations hesitant to try something new.
Improve data collection. Improved data collection and analysis are key to AEC innovation, particularly to fuel artificial intelligence and machine learning, but when projects are one-offs, data ownership becomes unclear. Data repositories, such as the one University College London (UCL) is helping create for Homes England, a major social housing provider, can amass the critical, unbiased data needed to fuel innovation. UCL is also testing production control rooms, leveraging data to monitor all aspects of an ongoing construction project. The first live site applications have taken place on commercial projects in London, says Jacqui Glass, vice dean of research and a professor in construction management at UCL. With a production control room in place, “You’ve suddenly got a very different environment to bring in other technologies—it’s like opening a door to new ways of working and thinking about AEC,” she says.
Restructure around innovation. Jo Vertigan, head of digital for the Anglian Water @ One Alliance, a partnership of seven companies collaborating on more than 50% of the British water company’s capital investment program, uses an innovation- focused iteration of McKinsey & Co.’s “Three Horizons Framework,” a structure that enables organizations to explore potential opportunities for growth without neglecting current performance, to guide the transition of innovative ideas from concept to adoption. “Innovation and exploring new ideas take time and effort; [they] can’t just be slotted in in your spare downtime,” Vertigan says. “You’ve got to support [them] with robust commercial underpinnings but also be mindful of having the time and space to learn. You should be careful of customer-led innovation, as it is not always best placed to articulate a future world, especially in traditional business sectors.”
Concrete facts to reflect on
- Artificial intelligence (AI) and automation are often seen as key enablers of innovation, allowing organizations to work better, faster, and more sustainably and efficiently while reducing costs. A 2021 survey of 1,843 global cross- industry organizations by McKinsey & Co.2 showed that 87% reported a cost decrease as a result of using AI in manufacturing and 69% experienced a cost decrease in product and/or service development in 2020. Fully 63% and 70%, respectively, saw revenue increases in manufacturing and product and/or service development as a result of AI adoption in 2020.
- “The 2021 Future Manufacturing Workforce Study,” a survey of 882 Gen Z manufacturing employees by workforce management company UKG, found that 94% called working on fulfilling projects important, very important, or extremely important to their job satisfaction. Three-quarters agreed, somewhat agreed, or strongly agreed that manufacturing has unfavorable working conditions. Attempts to attract new talent to industrial organizations lead to a culture clash of sorts when established workers steeped in manufacturing expertise encounter young, digitally savvy talent without that background. “And that causes quite a lot of disconnect and cultural dysfunction in some cases where the newcomers are not easily welcomed,” says Jo Geraghty, cofounder of Culture Consultancy, a London-based culture change consulting organization. Organizations need ways for new hires to learn from the experience and knowledge of long-term workers while using their data skills to update and transform processes. Sustainability goals are also upping pressure to bring innovation to sourcing, materials, and processes, with stakeholders, including investors, customers, and employees, increasingly focused on goals beyond simply driving revenue.
- Technology is proving a key enabler of innovation, applying increasingly sophisticated algorithms and models to data and automating the iteration of design choices. Sources of essential data are proliferating across manufacturing and construction, thanks to increasingly affordable sensors and cameras and the ability to collect and amass data via wireless and cellular networks and the cloud. Beyond simply digitizing existing analog processes using this data, organizations are increasingly digitalizing them—rearranging business processes by sharing and collaborating on digital information in new ways, with information at the center of this new operating model. AEC and D&M organizations are leveraging automation, AI, digital twins, generative design, and DFMA to foster innovation and create business value by streamlining processes, discovering new patterns and insights, and automating data-based decision making. AI promises to have a profound effect on the entire global economy. McKinsey created a model simulating the potential cumulative impact of the use of AI on the world economy by 2030, including an analysis of how it could affect companies.
- Digital twins are also increasing their role as a tool of innovation in AEC and D&M. Organizations are tapping digital twins’ ability to create a virtualized version of a product or structure to enable designers and engineers to experiment with designs, materials, and other variables as part of the initial design process. The dynamic nature of digital twins and their ability to represent real-world data and performance on top of a virtual model create a feedback loop between physical and virtual environments. This loop helps users and organizations make better decisions, improve their business practices, and access benefits such as reduced downtime and increased ROI during construction and manufacturing. Digital twins also benefit the ongoing usage of products and buildings. The global digital twin market is projected to grow at a 58% compound annual growth rate (CAGR) from 2020 to 2026, from $3.1 billion to $48.2 billion, respectively, according to a report from Markets and Markets.