In our previous posts in this series, we established a case for construction technology due to severe labor shortages, and discussed two primary challenges as market fragmentation and complex market structure. We then looked into a number of automation-related opportunities involving site preparation and foundation phases of the construction process, focusing on construction surveying and concrete foundation fabrication. We also discussed nuances around modular construction and possible approaches by which this might succeed.
In many cases, companies that attempt to directly automate construction jobs do not present a lucrative investment opportunity. Sometimes, proposed projects are not technologically feasible; in other cases, the incentives among and between the asset owner, general contractor, subcontractor (and others) do not align and inhibit market adoption.
In this final article in our construction automation series, we will examine and evaluate companies that are indirectly solving the construction labor challenges, and make the case for the most interesting venture investment opportunities.
Ninety-eight percent of construction megaprojects face time and cost overrun
Time and cost overrun are the norm in the construction industry. According to KPMG, only 25% of construction projects were completed within 10% of their original deadlines, while only 31% of all projects came within 10% of the budget. Furthermore, large projects typically take 20% longer to finish than scheduled and are up to 80% over budget, while 98% of megaprojects incur delays or exceed their budget. The problem is exacerbated in large-scale infrastructure, in which overrun of capital expenditure can be as much as 80%, with delay beyond the original schedule as much as 20 months compared to a typical 3-6 years project timeline.
With a reduced pool of skilled labor and positive net outflow of the labor pool, we would naturally expect these time and cost overruns to aggravate. We cannot necessarily fill in a gap of some specific construction jobs due to technological and market structure hurdles; therefore, the only viable solution is to enhance overall construction management productivity where it would most likely improve delays and cost overruns.
The causes of construction project delay
We looked at each task and examined the construction management process from end-to-end to assess the underlying factors one by one. Results are presented in Table 2.
|Construction Management Process||Cost and Time Overrun Factors||Attractive|
|Design||Design Issue: Faulty design will lead to incorrect application of construction techniques, resulting in erroneous builds that cause project delay.||Yes|
|Time and cost estimation||Inaccurate time and cost estimation: Construction complexity leads to poor engineering estimates and budget shortages.||Yes|
|Resource Planning and Management||Ineffective project planning and scheduling: Planning and scheduling rely on experience, with weeks to complete each iteration, leaving little room to optimize the plan and schedule or reschedule accordingly.||Yes|
|Raw material delivery: The lack of real-time data integration between project scheduling, progress monitoring, and raw material/equipment planning results in raw material delivery delay.||Yes|
|Raw material price volatility: Construction raw materials are commodities; their prices can fluctuate greatly throughout the construction period beyond estimates made years in advance.||No|
|Monitoring and Inspection||Equipment abuse and breakdown: Lack of visibility in the supply chain makes it difficult to know with clarity which equipment is needed where and when.||No|
|Inspection, supervision and quality control: Despite the high level of competition, opportunity exists at the “integration stack.”||Yes|
|Site Management||Poor site management, communication and coordination: The market landscape is very competitive, with many SaaS companies vying to improve site coordination. There will likely be winners but accurate prediction is difficult.||No|
|Document Management||Inefficient document management: The number of mature competitors includes Marker Blue and DocuSign.||No|
|Payment||Payment delays and unpaid work: The payment process is extremely cumbersome for a financial institution, resulting in a high degree of friction and efficiencies.||Yes|
|Safety||Injury and safety concerns: Both safety-related budgets and customer sentiment lack market demand for safety-related solutions.||No|
Decisions made early in the conceptual planning and design phases have a dominant influence on project cost and completion time. Consequently, solutions that enhance the construction management process during the pre-construction phase have a greater impact on the project, thereby creating value for the asset owners and general contractors who are likely to be the customers of these solutions.
Resolving the design issues
The design process may take years, yet still fail to produce adequate detail. These limitations are first realized once the project is underway, stalling site progress while the architect and general contractor finalize the details. Design-Build, in which the general contractor designs and builds the project, resolves some of these problems but also introduces other risks to the asset owners. Design issues create ripple effects that ultimately result in further inaccurate schedule and cost estimates and, ultimately, overrun.
Over the past couple of years, a field called generative design, which attempts to standardize design inputs and creates consistent outputs, has emerged. Using a linear optimization approach, generative design creates a number of outputs, often limited but in great specificity, that meet certain criteria such as the number of toilets or the amount of required sunlight.
Generative design may reduce design errors but it is a highly inflexible tool that requires pre-specifying the inputs and deterministic variables in advance. This often does not match the existing design and construction processes that are more fluid and creative. Customer requirements may also change and evolve throughout the construction process.
We have yet to see a tool that offers the best of both worlds, comprising a high degree of design specificity that eliminates ambiguity, without needing a complete library of deterministic inputs. Such a tool is likely to look less like Microsoft Word’s auto-correction and more like Google’s Smart Compose, which predicts text in Google Doc (although Microsoft is about to release a similar feature). An AI tool that demonstrates the ability to predictively resolve design errors, whether by automating key features or searching for potential glitches, will greatly reduce cost and time overrun along the entire chain. We are still searching for such a company.
AI-generated construction schedule and cost estimate
Construction planning is a complex task and often follows an intuitive, experience-driven approach. A non-residential construction project, such as a 60-storey office building, typically takes 3-4 weeks for construction schedule planning. Rescheduling is also complex and may take up to one week, making scenario planning extremely difficult. Lack of detailed design often leads to inaccurate plans and project schedules. Raw material planning does not synchronize with real-time project status, which leads to material shortages.
However, this scenario is changing drastically with the advent of building information modeling (BIM), which offers planners more detailed 3D design. Many construction companies are now adopting BIM. ALICE is an AI-powered construction simulation and optimization platform that deconstructs and breaks down BIM design for a given project into a task-by-task schedule. The software allows companies to optimize different cost parameters such as labor, vehicles, and tooling against project schedule to determine the most cost effective and least labor intensive solution to meet both budget and schedule.
ALICE enhances human planners by resolving delays and enables general contractors to rapidly change plans to meet unexpected external events such as severe weather or material delays. However, changes to plans may not translate into actual cost savings. For a general contractor that owns and operates its own crane, a short-term reduction in crane usage may not necessarily translate into cost reduction because the contractor cannot move the crane to a new site. An asset owner may use the software to find a more optimal schedule, but the general contractor may not want to commit to such a schedule.
The power of optimization is wide-ranging. Logically, ALICE will eventually offer or integrate with a material planning feature to reduce material delivery delay. One day, a cost planning tool will appear that utilizes augmented reality/virtual reality (AR/VR) and lets users manipulate the design, while recalculating the cost in real-time and integrating with scheduling tools to triangulate between design, cost, and schedule. However, these planning and optimization tools must also account for the ability of companies to realize cost and time savings from an optimal plan or risk seeing churns from their hopeful, but disappointing customers.
An opportunity one layer above
Asset owners and general contractors often subcontract the required day-to-day inspections. An array of “sensor-on-the-ground” companies attempt to automate these tasks to no avail because asset owners and general contractors do not care how the inspections are done as long as they are done. Subcontractors are not good customers of these technologies due to market fragmentation and tight balance sheet issues. The value in inspection lies not in automating the inspection task but rather in aggregating the data and forming insights that actually matter to the asset owners or general contractors, a more consolidated segment with much greater purchasing power.
One company that does this well is VEERUM, a Calgary-based firm that creates an analytic layer to help energy companies understand construction reality versus planning for multi-billion dollars projects. VEERUM lets other companies do the heavy lifting of site inspection, aggregates different types of data, and turns them into broader and more meaningful insights by helping their customers understand both the construction status and the sources of delay, offering a complete picture of a job site rather than piecewise data.
Skewing toward pre-construction
Our view skewed toward companies solving problems in the pre-construction and early process of the construction phases. We do not have a particular affinity toward them but the economics point to solving problems in these areas.
Good management early in the project is far more likely to help companies save valuable resources in the long run. The challenge of ambiguity can be dealt with using the power of Big Data and predictive analytics. Solving the construction design and scheduling upfront and supplementing them with analytics concerning construction monitoring are likely to help the company curb rising costs and time constraints as industry norms.
Many companies and VCs seek to optimize the far end of the bullwhip, where each improvement is incremental at best, but we are searching for companies that solve a much harder and more ambiguous problem at the earlier phase of the construction process. We will continue our search until our targets are located.