Build, build, build. That’s the order of the day to meet the world’s urgent demand for everything from battery factories and renewable-energy projects to energy-efficient work, housing, and transportation infrastructure. The energy transition alone requires an estimated $9.2 trillion in annual investment between now and 2050, with around $6.5 trillion projected for low-emission assets.1
Is the engineering sector up to the task? If past performance is any indicator, not likely. Research confirms the widespread perception that capital projects consistently overrun on cost and schedule.2 Yet to achieve near-term climate commitments, for example, renewable-energy generation capacity would need to come to market at nearly triple the current rate—meaning that more than 520 gigawatts of solar and wind power would need to be installed annually during the current decade.3
This is not a gap the world can afford in terms of time, money, or emissions.
Delivery challenges are compounded by a shortage of engineering talent. Just in the United States, there were about 400,000 vacancies in the architecture, engineering, and construction sector as of late 2023, while in the United Kingdom, vacancies in the sector have risen by about 50 percent since 2019.4
Despite the urgency, the engineering sector is up against a traditional business model that does not incentivize the level of transformation required. The usual compensation structure is based on hours and rates—therefore, inputs: the more inputs, the more revenue and margin. To achieve a step change in performance, incentives for both engineering and asset owners would need to realign around shared incentives and shared risk and reward.
This article explores seven disruptive features—and potential incentives to unlock a reimagined business model—that together could transform the sector, and its ability to create the built environment of the future.
A sector ripe for disruption
Despite the availability of some of the most cutting-edge digital tools since the 1980s, engineering remains largely unchanged in the way it works. Most projects are still organized by discipline (for example, civil, mechanical, and electrical), and inefficient work processes create an enormous amount of paperwork—even when digitized.
However, seven disruptive features are emerging in the engineering sector, largely driven by fast-moving changes in software engineering (see sidebar: “Agile software engineering at a glance”):
- Redefining the “product”
- Switching from push to pull workflows
- Switching from a discipline focus to a cross-functional focus
- Creating a single (real-time) source of truth
These first four changes have produced time and cost savings of anywhere between 30 and 50 percent, significantly improving quality and “first time right” metrics, as well as leading to construction productivity further downstream. To speed up the performance transformation needed, engineering could also leverage three disruptive features:
- Using AI-enabled design automation
- Applying continuous integration and automated testing
- Adopting open sourcing
While engineering firms (and teams within larger organizations) are beginning to experiment with these changes —with encouraging results—an organization is yet to emerge who has brought together all seven facets. Combining them could truly disrupt engineering as we know it.
One: Redefining the “product”
The first, crucial disruptive feature is reframing the “product” that engineering provides. Currently, engineering produces drawings, which inform cost and schedule estimates for investments and instruct construction on what must be built. Traditionally, the different engineering disciplines have little awareness, incentive, or practice of looking at the ultimate product that is being engineered.
Placing the (real) customer of engineering outputs at the center of the profession could help to reframe the product delivered. This “customer” is actually the construction (ability to deliver the asset in right sequence on schedule), and ultimately the asset owner (NPV).
In this reimagined approach, the engineering product becomes the construction-ready drawings for all elements involved, in the exact sequence and at the required volume and quality, to enable execution of the instructions.
This approach could be incentivized in different ways. Increasingly innovative contracting practices link engineering fees to outcomes “downstream”—for example, to the start of construction or to the net present value (NPV) the asset produces. The engineering team of a global transport sector manufacturer, meanwhile, was incentivized based on revenue generation from its newly completed production lines.
In the case of early engineering or front-end engineering design (FEED), the product is a robust business case that is attractive to investors. Engineering’s contribution in this vital early stage of the project delivery process would be a product that is viable enough to inform decisions on whether to take an investment decision, to continue to a detailed design (or not).
Two: Switching from push to pull workflows
Once the downstream customer and product are established—for example “construction” to start—a shift from push to pull workflows becomes possible.
In essence, this means prioritizing the engineering deliverables in line with what the downstream construction customer needs next to maximize throughput and asset completion for operation. Although this might seem obvious, we repeatedly observe a mismatch between engineering outputs and requirements of teams and work processes that follow. Aligning the two is not a new principle—famously, the Empire State Building was built in this way. More recently, Toyota made it the basis for optimizing its manufacturing process by reducing waste and inventory, while maximizing valuable throughput at its factories.
In this reimagined model for engineering—designed to create a major acceleration in project work—aligning engineering deliverables with construction needs and sequencing would unlock schedule and cost savings across all industries.
Three: Switching from a discipline focus to a cross-functional focus
Agile principles can accelerate the cycle times and product quality for software and physical products across industries and could be a game changer for engineering, too. The principles are intuitive if we focus on a product. They combine all the capabilities required to deliver a product (or an integrated unit of it), empower teams to make decisions on the delivery of the product or unit, and create a cadence that allows for speedy resolution and escalation when bottlenecks occur.
Composing teams in this way requires bringing together skills from all relevant engineering disciplines, as well as from commercial, construction, and procurement, and including key suppliers. The design process becomes robust for the customer (e.g., construction, asset operator) and the contributors because designs are geared toward the ultimate operations, availability of components and materials, and constructability.
One oil and gas supermajor piloted agile ways of working with its well-delivery team, including key suppliers. On the first try, it shortened the timeline for concept selection by 60 percent, reduced design development for a horizontal well to 13 weeks from 26, and saved 240 full-time equivalent (FTE) days (40 percent) in well planning. All of this was achieved while improving employee engagement scores and increasing empowerment scores by 30 percent.
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Four: Creating a single (real-time) source of truth
Currently, engineering workflows are mainly executed in siloed use of PDF-equivalent documents and myriad spreadsheets. This makes it challenging for owners and engineering contractors to bring together large amounts of work into an integrated design—requiring lots of manual work and rework, without the ability to drill down into root causes of discrepancies or provide forward-looking perspectives on expected outcomes.
Establishing a single source of truth (SSOT) for all stakeholders could be one disruptor the industry needs. Structuring information models in such a way that every data element (design or schedule detail) is mastered in only one place would make it much easier to prevent mistakes, duplication, or inconsistencies, thus improving control.
A basic-level SSOT would provide transparency on priorities, progress, and current and potential bottlenecks in delivery. This kind of improvement was demonstrated in a multibillion-euro capital program relying on one supply chain to deliver multiple megaprojects simultaneously. The owner and contractor worked together to create transparency in supply chain performance —from the outlook of an individual purchase order to an aggregated view by category, project scope, and asset. Appropriate access was secured for project teams, central functional teams, and top leadership to enable joint problem solving on current and emerging bottlenecks.
A higher-level SSOT could see engineering carried out in a single data set or so-called “digital twin” from the start, rather than using multiple documents. Such digital-native engineering would pivot engineers from a document-driven way of working to cross-collaboration between engineers, subcontractors, and operators to develop the design in real time.
Five: Using AI-enabled design automation
Much of what an engineer does today could be grouped into one of two categories: first, understanding the size of the component needed, then picking a relevant design from a catalog; second, doing the “creative” work on how to put together the various building blocks.
The first category is ready for disruption through algorithmic approaches. An oil and gas player in Asia recently digitized its subsea tieback design process, cutting the timeline for getting a very good first design to less than a day from around 12 weeks. This design could then be fine-tuned by engineers.
The second, or creative part of engineering, is likely to see disruption on the horizon, too, judging by recent advances in generative AI. Current technology could already enable blueprints and specifications to be produced in seconds instead of days for final refinement by an expert.
Tasks such as structural design detailing and construction schedules could also be optimized by AI. Generative scheduling, which involves optimizing the sequence of activities for execution, is already being successfully deployed in the construction industry. AI construction simulation and optimization platforms have resulted in generated major productivity improvements for a number of project owners and contractors. For example, when constructing a $300 million petrochemical factory, one such platform tool identified the opportunity to decrease labor idle time by 33 percent, reduce labor requirements by 8.5 percent, and save three weeks on the critical path schedule.
Six: Applying continuous integration and automated testing
Implementing a continuous integration (CI) workflow could significantly reduce the overheads of synchronization and tighten feedback cycles through automated testing. For example, continuously (or regularly) updating the SSOT would allow advanced automated testing of all iterative changes. This could provide immediate feedback on whether a change is both within parameters and an improvement on the existing design.
Many teams and organizations already harness simulations and physical requirements in their digital design process. This could be further optimized through digital twin and AI-powered use-based tests. These could validate improvements by simulating the final stakeholder’s asset operation, thus ensuring rapid actionable feedback on every design iteration.
This kind of product-use simulation is a step up from the classical physics-based simulations typically used in engineering. In effect, it provides end-to-end visibility for all stakeholders at every design update. Downstream consequences, such as financial implications or maintenance requirements, could also be calculated and made visible instantly, supplemented by AI-enabled user testing of the full asset.
Such a use-based approach allowed the Emirates Team New Zealand to iterate ten times faster on their sailboat design—ultimately winning them the prestigious America’s Cup. For the sailing vessel, the QuantumBlack, AI by McKinsey team took physical simulation and design one step further by training a digital AI pilot as a stand-in for the team’s pilot. This allowed the team’s sailors to spend less time in their simulator, and designers to iterate an order of magnitude faster by simulating the use of the vessel in the competition.5
Seven: Adopting open sourcing
Open sourcing is commonly used in software engineering, allowing universal access to designs or scripts to encourage collaboration on new ideas, optimize existing products, and provide broad access to solutions.
A significant proportion of engineering design work is repeating what has already been done—for example, designing a distillation column. Open-sourcing designs, with no (or limited) real business IP value, could spur innovation. This could especially help nascent technologies that play an important role in the energy transition, where risk is high and debugging essential.
A gold-mining company used an open-source approach to solve some of its biggest technology issues. Every year, the company organized a global conference in a compelling location and paid for invitees’ flights and accommodations. To participate, delegates needed to have done meaningful research and written a paper on the company’s most pressing technology challenges. This moved problem solving from a small group of engineers to a global pool of talent.
Open sourcing has also emerged as a tool to find solutions for reducing carbon emissions. For example, the Northern Lights project is developing the world’s first open-source CO2 transport and storage infrastructure, located on the Norwegian Continental Shelf. This initiative is partially funded by the Norwegian government and has attracted partnerships with energy players, engineering firms, and oilfield service companies.
Rethinking the traditional business model
Combining all seven disruptors could be a game changer for the engineering sector—and critical to the net-zero transition. However, realizing these changes will not be easy. The engineering sector finds itself trapped in a traditional business model that does not incentivize acceleration and optimization.
However, if the product delivered by engineering is reframed, the industry could shift its business model from being paid for inputs, to being paid for output (the product).
For example, in early-stage engineering, the product is a business case for investment with a robust NPV. Could a reimagined engineering remuneration approach be linked to the NPV of the target asset instead of to expectations of a potential on-time delivery of design, cost, and schedule estimates?
In detailed engineering, the product is construction productivity in relation to sequence, volumes, schedule, and quality. Revenue generation comes from first or ramped-up production. Could a reimagined engineering incentive be instead linked to construction productivity or to first at-scale production?
Naturally, a reimagined business model would need to share the gains and the pains across project stakeholders. Here, new, more collaborative contracting approaches are already delivering materially better outcomes than traditional “adversarial” models. For example, in hospital buildouts in the United States, collaborative contracting has resulted in 15 to 20 percent improvement in cost and schedule performance compared with traditional contracts.
The urgency of the energy transition is creating the positive momentum for change that the engineering sector needs. By daring to combine all seven disruptive features—each of which has been proven to work on its own—and by engaging with asset owners to redefine the business model to align incentives, engineering players could create a credible, sustainable competitive edge.
