Should you learn to code?
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Starting a conversation about programming in construction might not sound like a recipe for excitement. But give it a minute.
When you zoom in on what professional services truly mean in this industry, the endless Excel sheets, the risk of human error, and the sheer amount of admin, you start to see the problem. And with it, the solution.
On our podcast Inventing Construction we recently had a conversation with Christian Kongsgaard about the essential role of coding in the digital progression of the industry. The core question was: Should professionals, from architects and engineers to cost managers and quantity surveyors, learn to code?
The answer is yes. It’s not about becoming a software developer, but about adapting to the inevitable change that is reshaping how construction services are bought and delivered.
In the following article, we’ll discuss:
- The construction industry’s core conflict
- Where to start: Practical coding for professionals
- The necessity: Why automation is critical now
The construction industry’s core conflict
The single biggest barrier to the widespread adoption of automation isn’t the technology—it’s the existing business model.
Many organisations’ turnover is currently based on inefficiency. If the business model relies on having “bums on seats” and billing hours for manual paperwork and administration, then automation directly threatens that model. If it’s good for business to just add more hours and get a bigger margin, there’s no need to automate anything.
- The Problem: Management KPIs often revolve around maximising hours and turnover, creating resistance to efficiency.
- The Inevitability: This model is quickly becoming outdated and unsustainable. The only way to deal with the overwhelming volume of work and the critical shortage of professionals is through automation.
- The Opportunity: If you can complete a task in 10 hours that traditionally took 150 hours and deliver it quicker, clients will pay a premium for that speed, quality, and efficiency.
The transition period is here: we are moving from an old, traditional service model to a new, efficient one. Companies that fail to upskill and adapt will inevitably be left behind.
Where to start: Practical coding for professionals
The good news is you don’t need a computer science degree to begin. The entry point for most architecture, engineering, and construction (AEC) professionals is through visual programming tools that are already integrated into their daily work.
- Visual programming: Dynamo and Grasshopper
For designers and engineers, the journey often begins with visual tools:
Dynamo: This is a visual programming tool often used with Autodesk Revit.
It’s an excellent starting point because it is directly connected to the building model data you use every day. QSs and cost managers can use Dynamo not for design, but for data processing—checking quantities, quality assurance on bills of quantities (BOQs), or ensuring the right properties are applied
Grasshopper: A similar visual programming tool primarily used with Rhino, often leveraged by architects for complex parametric design and advanced technical analysis like building physics or wind simulations.
In these environments, you chain together “building blocks” (components) to define a sequence of actions, which is the underlying principle of an algorithm. This teaches you how to process data and think logically about processes—the foundation of programming.
- Upgrading Your Excel Workflow with Python
For QSs and cost managers, and others who spend a significant portion of their time in spreadsheets, value can be found in a language like Python.
Python is a versatile and widely used language that can be integrated directly with tools like Dynamo and Grasshopper. The key strategy is to use Python to replace the logic of your old, dusty Excel sheets.
Instead of a multi-tab, complex Excel file that is prone to human error, you create a streamlined process: Excel In → Python Code → Excel Out.
The Value: In Python, the formulas (the logic) is easy to read and quality-check. This process increases accuracy and replaces manual calculations.
The Future: As skills develop, the Excel output can be replaced entirely by feeding the data into a centralised database and visualized on dashboards – like Power BI. - Overcoming Misconceptions
One of the biggest misconceptions about coding is that you need to be good at advanced math. Programming is actually much more about logic, sequencing, and data processing—most code involves text, pictures, or data, not complex numerical calculations. Therefore, a lack of mathematical comfort is not a barrier to entry.
The necessity: Why automation is critical now
The demand for automation is being pushed by two major forces:
- Increased complexity and regulation: The industry is facing increased regulations and demands (e.g., sustainability and carbon requirements), forcing professionals to do more for the same price and in the same time. Automation is the only viable path to achieve this efficiency.
- Talent shortage: With the industry short thousands of professionals, firms cannot afford to have their high-value QSs and engineers spending up to a third of their time on mindless admin. Technology must free up this time so that professionals can focus on higher-value work, such as risk management, building relationships, and strategising around data.
It is important to remember the 80/20 rule. While automation can achieve massive productivity gains, returns begin to diminish around 80%. Construction remains a unique, project-based industry , and human interaction will always be required for final quality assurance, interpretation, and flexibility.
The human role shifts from spreadsheet wrangling to using soft skills—communication, teamwork, and interpretation of the automated output. You need the human touch to polish the code and steer the process in the right direction.
The path forward
The need to upskill is an inevitability, not an option. For professionals across the AEC industry, the path forward involves:
- Starting small: Begin by exploring visual tools like Dynamo and Grasshopper, or by automating your current Excel logic with Python. There are ample online resources for self-learning.
- Seeking community: Look for collaborative networks like Open Source Construction. These communities connect scattered digital doers and provide free resources for collaboration, helping overcome the perception that technology adoption is too expensive.
- Digitizing with purpose: Don’t digitise just for the sake of it. Identify your problem first, involve your team, and then choose the tool that fits.
The disruption is coming, whether from fast-moving startups or large tech companies who see the low technology adoption as an opportunity. By embracing coding now, you ensure you are on the winning side of that change
It might just save your margins—and your Monday mornings.