In Part I, we explained that the construction industry is experiencing heightened demand primarily from the residential and infrastructure segment, an aging workforce that is retiring, and the challenge to attract younger generations. These factors lead cumulatively to a severe labor shortage and rising labor wages that are constricting an industry historically operating at a low-to-mid single digit profit margin. Thus, creating automation within the construction industry to substitute the workforce using advanced technology will boost productivity.
But what should be automated? First, we need to look at the major challenges in construction technology investment to build a comprehensive understanding of a possible great opportunity.
Billions in fragmentation: the challenges of investing in construction technology
Construction is one of the world’s largest industries but has two major challenges as market fragmentation and complex stakeholders.
The construction industry as a whole is nationally fragmented but occasionally locally concentrated. This differs depending on segment and type of construction company, with each generally comprising less than 10 workers. The top 100 general contractors account for less than 20% of the total construction market. Subcontractors are even more fragmented, with top players accounting for less than 1.0% of the total market share. This makes sales processes and scaling very slow and highly inefficient.
The number of different players that must work together also increases market dynamic complexity. Aligning interests between developers, general contractors and subcontractors becomes extremely challenging. Developers want contractors to reduce cost, but they cannot force developers to adopt any particular automation technologies or analytical tools beyond a typical bidding process. General contractors that want to deploy site management tracking tools to improve collaboration and productivity often incurs resistance from the many subcontractors engaged for the job. Once completed, the new project might use a new subcontractor, renewing the friction of technological advancement acceptance.
Successful investments, therefore, select construction technology segments that can best adapt to scalability and ensure alignment of interest among different stakeholders in the industry. These areas are limited but offer lucrative investment opportunities.
Job by Job, Process by Process and Opportunity by Opportunity
Given the above challenges, it follows that the most lucrative market opportunities for construction automation are defined by jobs under severe shortage with high market value that are also sufficiently concentrated among the top players (serviceable available market among the top 100 customers of at least $1 billion), and contain sizable homogenous tasks. We also believe that the best automation opportunities will not impact modular construction, a specific investment opportunity discussed later in this article.
|Labor Market||TAM||SAM among Top 100 customers||Severe Shortage||Sizable Homogenous Task||Feasible to automate||Does not compete with Modular Construction||Attractive|
|Steel Framing Worker||$4.9B||Sufficient||Yes||Yes||High||No||Yes|
|Wood Framing Worker||$5.0B||Insufficient||Yes||No||High||No||No|
|Glass and Glazing Contractor||$3.8B||Insufficient||No||No||High||Yes||No|
|General inspection crew||$5-10B||Insufficient||No||Yes||High||Yes||No|
Table 1. Summary of Construction Labor Market Analysis by Creative Ventures
Our analysis of the labor market presented in Table 1 identifies an interesting insight. Some of the most attractive opportunities are jobs required in the early part of the construction process during site preparation and foundation installation, while many of today’s construction technology companies are operating on the latter part of the construction process.
Automating the automated: Making use of drone data
One of the most labor intensive processes in site preparation is topography adjustment, which requires excavation and leveling. Autonomous construction vehicles are the obvious solution but adoption has been slow due to a number of operational challenges. We believe that a hidden opportunity lies in disrupting the surveying market, which has recently benefited from increased adoption of drone technologies.
Drones can be used to automate labor intensive tasks such as construction staking, whereby a surveyor marks the location of proposed new structures. An Israeli company called Civdrone is attempting to solve this problem using a drone to drive a stake into the ground. However, solving the surveyor labor shortage directly is not highly lucrative because this market is significantly smaller than the excavator market that has similar operational challenges. Rather than automating surveying fieldwork, it may be more beneficial to automate what they do “on the desk.”
The surveying field has recently seen increased data collection, with the challenge shifting from simple operations to analytical manipulation of the resulting geospatial data. One technical issue is translating 3D drone data from LiDAR or photogrammetry into more commonly used 2D data such as CAD drawing, which is traditionally performed either by the surveyors or CAD engineers. One such company tackling this is AirWorks that automates data translation collected by drones, giving surveyors more time to spend in the field and also resolving the shortage of CAD engineers since an increasing number are now attempting to “graduate” into higher-paying engineering roles.
The surveyor job market may not be the largest but the “adjacent” geospatial market is huge. Globally, the geospatial market is currently valued at $52 billion and is expected to grow at 12.9% CAGR according to MarketsandMarkets. The construction surveying market offers a great beachhead to build an automation tool on top of the broader geospatial market across multiple industries, following the previous success of companies such as Trimble.
Automating the difficult but repeatable: A case for concrete
The challenge presented by direct automation of construction is that most are extremely intricate and not repeatable. Electricians installing electrical wiring or carpenters implementing woodwork perform tedious tasks that vary across the field, and require large amounts of contextual information that state-of-the-art AI and robotics technologies are unable to replicate.
However, for almost all construction sites, the foundation process is primarily concrete-based. Contractors install a base structure from wood, panel, or foam and then add reinforcement steel, also known as rebar, to increase foundation tensile strength. Cement is then poured, leveled, and allowed to cure before the basal structure is removed.
The foundation footing comprises 15-30% of the entire construction cost. Processes such as rebar and concrete pouring are challenging but relatively repeatable, with companies such as Toggle and Rebartek attempting to tackle this problem. Sufficiently versatile technologies that improve repeatability with minimum setup time are still limited but the huge market size makes this a very lucrative opportunity that we will continue to monitor closely.
An unworthy long tail: From framing to plumbing
After the foundation phase, construction processes are dominated by an extremely fragmented long tail of subcontractors with tight balance sheets that do not promote the advantage of being early customers of automation technologies. These subcontractors tackle complex mobile jobs such as plumbing and roofing that the most advanced robotic gripping technologies are not yet sufficiently able to emulate. These tasks require multiplex hand and finger movements and involve location transfer from point to point on the construction site.
Most of these jobs are managed by subcontractors. The segment is highly fragmented and the subcontractors typically maintain very tight balance sheets. Their small scale does not lend well to being early customers of automation technology. Moreover, the work of the likes of carpenters and electricians is often highly complex and mobile. Robotics gripping technologies are not yet sufficiently advanced to emulate the multiplex hand and finger movements required to perform these tasks, let alone movement from point to point on the construction site.
A closing note: Modular construction
So why not use modular construction?
The attempt to “productize” construction into a homogenous manufacturing method has been mooted since the 1960’s. Early prefabricated houses were inflexible and of low quality, resulting in consumer perception problems, while many other challenges included logistics, high upfront investment, financing infrastructure, and cost.
Katerra is a very outspoken modular construction company that brings the entire end-to-end process in-house. Katerra offers everything from an architect and interior design to material, manufacturing, and assembly of prebuilt units. However, this is an extremely asset-heavy approach that is likely to bear significant short-term costs during a downturn, with the inherent solvency risk.
A likelier path is for modular construction to occur in a “bottom-up” fashion, in which more labor-intensive “modules” are fabricated using a manufacturing-like method. We have already seen this happening in wet areas such as bathrooms and toilets. Other areas that involve the most skill-intensive types of work, such as MEP (mechanical, electrical, and plumbing), are also expected to be eventually modularized by lower-cost manufacturing workers.
A venture capital opportunity occurs when a critical mass of these modules suggests that a given company would be able to build a virtual factory that aggregates module supplies and applies AI technologies to generate a highly customized product, most likely for the affordable housing segment given its highly acute shortage, in an asset-light and distributed manner. This approach would maximize suitability, scalability, and return.
In the next post of this series, we will look at construction analytics, and the opportunities offered by automation. You can read part I in the series here.
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