In the previous article, we summarized that additional costs incurred in the construction market exceed 865 billion USD annually. One potential approach to improvement is leveraging digital tools for operational enhancement, namely Digital Transformation (DX).However, even in today’s world where DX is advancing across various fields, the construction industry, particularly the field of construction design, is said to lag behind other industries, as processes involving handwriting and paper still persist*1*2. The delay in implementing new solutions to improve productivity in the construction industry, known as “Construction DX,” is ultimately lowering the overall productivity of the construction sector and creating the challenge of losing competitiveness.
A key reason for the lack of progress in DX within the construction industry, as highlighted by Brian Potter, a specialist in building physics, is the risk associated with operational changes*3 . In construction projects, numerous stakeholders are involved, and it has been pointed out that changes in workflows can ripple through the entire process, potentially leading to unexpected costs and schedule delays.
On the other hand, areas within the construction industry, such as the adoption of IT software like BIM (Building Information Modeling) and CAD, are not entirely stagnant. However, the reality is that these specialized software tools lack data compatibility with each other, and not all stakeholders can easily use them, making it difficult to leverage data effectively or optimize operations across the entire project.
In this way, the lack of progress in DX across entire construction projects is intertwined with multiple factors.
In this article, we will examine the challenges in construction and architectural design that need to be addressed to promote Construction DX, drawing on the unique perspective of Tektome, a provider of AI solutions for architectural design.
Unutilized ‘Unstructured Data’ Accumulated Within the Company
One of the key factors hindering construction DX is the presence of ‘unstructured data.
To understand the challenges of unstructured data, it is first necessary to address the concept of “dark data.” Dark data refers to “data within a company that has the potential to generate value but remains unused.” According to a survey conducted by Splunk involving over 1,300 business and IT decision-makers worldwide, 60% of respondents indicated that half or more of their company’s data is dark data, and one-third of respondents reported that over 75% of their data is dark data. In the construction industry, the proportion of dark data is expected to be even higher. While this data exists, leaving dark data unutilized not only hinders digitalization and operational efficiency but also means that its latent value remains untapped.
One of the factors contributing to dark data is the presence of unstructured data. Unstructured data refers to data that does not have a format suitable for searching, aggregating, or analyzing, and lacks a clear definition. This includes data that cannot be easily stored in table formats or databases. In the construction industry, unstructured data is particularly prevalent. Examples include BIM and CAD drawings, on-site photos, and contract documents. These types of data vary in format and content, leading to challenges in ensuring compatibility and consistency among the data.
The biggest challenge with unstructured data lies in its difficulty of handling. For example, even a simple operation like “measuring distances” on a 2D drawing requires identifying the starting and ending points. However, in its unstructured form, pinpointing these elements is quite difficult. Additionally, with unstructured data, statistical processing and searching become extremely inefficient, significantly limiting the scope of data utilization. Furthermore, advanced processes such as quality checks and design automation are nearly impossible to achieve when dealing with unstructured data.
To overcome the challenges posed by unstructured data in the construction industry, it is essential to convert the data into a structured format. However, such efforts require significant time and cost, making it a major challenge at the moment. To transform previously accumulated data into structured data, the advancement of AI-driven data analysis technologies will be indispensable.
The Complexity of Specialized Tasks in Construction Design Done by Highly Skilled Experts
Construction design projects rely on the integration of highly specialized expertise. For example, even in a single architectural design process, professionals such as architects, structural engineers, mechanical engineers, and landscape designers collaborate closely to move the project forward. As the project transitions to the construction phase, even more specialists become involved, including construction managers, mechanical contractors, and on site workers—often numbering in the dozens or even hundreds. Each professional plays a critical role, and it is only through their combined efforts that a single building is finally completed. This concentration of high-level expertise is what creates the unique complexity characteristic of the construction industry.
In industries outside the construction sector, many DX solutions have emerged to support the work of specific professionals. For example, in the medical field, AI-powered diagnostic imaging solutions assist by automatically analyzing medical images and detecting abnormalities, thereby reducing the workload of doctors. However, most of these solutions target tasks that, while sophisticated, are “standalone and self-contained”—areas where AI-driven replacement or support is relatively easier to implement.
In this context, supporting specialized tasks in the construction industry is significantly more challenging compared to other fields. First and foremost, construction tasks themselves are extremely complex, often making it difficult for AI or other technologies to fully understand or provide effective support. For instance, aesthetic judgments in architectural design or improvised solutions when unexpected issues arise on construction sites are areas where simple AI algorithms fall short. These tasks require a level of creativity, experience, and on-the-spot decision-making that current technology struggles to replicate.
Furthermore, when multiple specialists collaborate as a team, the difficulty increases even further. It is not sufficient to digitize the tasks of a single professional; instead, there is a need for an integrated solution that addresses the needs of all specialists involved. In architectural design projects, for example, the proposed designs from architects must be validated with structural engineers, while mechanical engineers also work together to refine and shape the design into a feasible solution. Developing a system to support this process requires a comprehensive understanding of all specialized fields and the creation of a mechanism that effectively integrates and connects them.
Thus, in the construction industry, it is not only the individual tasks of specialists that require support, but also the entire project as a whole. However, developing such solutions faces numerous technical and organizational barriers, making progress in solution development difficult at present. This complexity lies at the very heart of the challenges surrounding digital transformation in the construction industry, underscoring why achieving digitalization in this field is particularly difficult.
Low Return on Investment Due to Fragmented Tasks
To introduce DX solutions into construction design, economic viability is essential, with the key factor being return on investment (ROI). ROI is measured by two elements: the cost of investment and the impact of its outcomes. However, in the construction design domain, significant challenges exist on both fronts. This is one of the primary reasons why digitalization and the adoption of innovative solutions have been slow to advance in the construction design sector.
First, regarding the magnitude of investment costs, the previously mentioned challenges of unstructured data and the complexity of specialized tasks make solution development for construction design extremely difficult. Transforming and standardizing unstructured data into structured formats for accumulation and analysis, understanding the intricacies of each specialized task, and building processes supported by AI, IoT, and other digital technologies all require significant resources. Given the high degree of development difficulty, project scale and costs inevitably expand, making large investment amounts unavoidable.
Next, attention must be given to the limited impact of such solutions. Construction design consists of an extremely fragmented set of tasks. A single workflow is composed of hundreds to thousands of micro-tasks, each requiring specific expertise and skills. As a result, even if a single solution is introduced, it is often unable to significantly improve overall efficiency. For example, in a scenario with 1,000 tasks, one solution might address only a single task, representing a mere 0.1% of the entire process. Such cases are not uncommon.In this situation, even a technologically advanced solution delivers only a limited impact on the entire construction design process. Coupled with the substantial investment required, the return on investment (ROI) becomes low because the benefits are restricted to a small portion of the workflow. Thus, the combination of technical challenges and workflow fragmentation undermines the economic rationality of digitalization in construction design. This serves as a barrier to innovation adoption, further delaying the digital transformation of the industry.
In conclusion, the construction design sector faces a dual barrier: the magnitude of investment costs and the limited impact of solutions. These structural challenges have made it difficult for DX investments to gain momentum. To enable the industry as a whole to fully reap the benefits of digital transformation, there is a pressing need for a more integrated and economically viable approach that spans the entirety of construction design workflows.
The Construction DX Solutions That Are Needed
As discussed, the three intertwined factors—unstructured data, the diverse and complex nature of specialized tasks, and low return on investment—make the development of DX solutions in construction design exceptionally challenging. However, to enhance productivity in the construction industry, innovation through DX cannot be halted.
Under these circumstances, the solutions required by the construction industry must possess the following characteristics:
1.Technologies for Handling Unstructured Data
In the construction industry, it is essential to organize and analyze vast amounts of unstructured data accumulated in the past and convert it into a usable form. Technologies such as natural language processing, image analysis, and integrated processing of BIM data are key.
2.Advanced Reasoning and Logical Thinking to Support Complex and Specialized Tasks in Construction and Design
Construction and design involve not only technical accuracy but also creativity and reasoning abilities, making the tasks inherently complex. To support this, it is necessary to have advanced logical thinking models and reasoning engines that complement expert judgment, rather than simple automation. Examples include supporting the evaluation of design proposals, streamlining structural calculations, and optimizing construction processes. Additionally, it is essential to support not just single tasks but multiple integrated operations.
3.An Integrated Platform to Simultaneously Solve Multiple Issues
Since construction design consists of a collection of segmented tasks, it is unrealistic to solve all challenges with a single DX solution. However, having an integrated platform capable of addressing multiple tasks and phases can connect partial solutions, thereby improving overall efficiency. Ultimately, this approach is more economically rational than introducing standalone solutions.
DX solutions with these features will be key to accelerating digital transformation in the construction industry.
In future articles, we will focus on each of these elements and delve deeper into the technologies and approaches that can overcome these challenges. From innovations in unstructured data to supporting specialized tasks, we plan to present concrete solutions and possibilities.
- McKinsey & Company(2018), How OEMs can seize the high-tech future in agriculture and construction
- Transform Partner, Construction Industry Being Reshaped By Technology
- Brian Potter(2021), Why It’s Hard to Innovate in Construction
