Navigating the boom in generative design software

Posted on December 3, 2024 at November 28, 2024 by Allister Lewis

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Generative Design (GD) tools have become increasingly accessible, empowering architects, engineers, and clients to explore innovative designs and streamline project feasibility. But with so many options, how can AEC professionals choose the right tool to meet their needs?, asks Allister Lewis, Automated Data Driven Design (ADDD)

Generative Design (GD) is a technology-driven approach to optioneering designs by using algorithms to explore a vast number of possible solutions based on defined constraints and goals.

By inputting parameters such as unit mix, desired building heights, spatial layout requirements, and performance criteria, GD software generates numerous design options. This allows designers to evaluate and select the most optimal solution. Instead of manually crafting each option, designers can review a wide range of solutions, filter and adapt them further, enabling new creativity, or simply getting optimal answers faster for clients.

The expanding landscape

As the popularity of GD has increased, so has the number of available tools. This is both exciting and overwhelming.

It is clear that GD software developers have identified early stage feasibility as an area that GD can be applied to effectively. The software should help designers make decisions faster, using data to confirm project viability, and communicate options more effectively than traditional CAD/BIM authoring tools. However, this presents a challenge for professionals to learn which one is best for them, manage licence costs, and then understand how to integrate them into their own tech stack effectively.

Breaking down barriers to adoption

Despite the promise of GD, there are still notable barriers to adoption for many AEC professionals.

1. Time to Learn: GD tools have opened the door for many users to explore data driven design but within a proprietary format, without a steep technical learning curve of visual scripting. GD tools still require time and effort to master, which can pose challenges for busy professionals.

2. Cost: Licensing fees vary from free trials and low introduction fees, to expensive Software as a Service (SaaS) models. When added to the growing list of software required for AEC workflows, this is an additional cost that puts pressure on companies already struggling to manage cash flow. While GD tools may offer long-term savings by accelerating workflows, the recurring monthly costs can deter adoption.

3. Workflow Integration: Not all GD tools integrate smoothly with existing software ecosystems, which can create friction. Users often rely on a core suite of tools, and if a GD solution disrupts these workflows, it may slow productivity. Ensuring compatibility and ease of integration with a company’s preferred BIM authoring software is crucial for broader adoption.

4. Functionality: These tools are new and are continually expanding the range of functionality they offer. However, no single tool has managed to provide the comprehensive design functionality that meets all user needs. A careful study of requirements is required to make sure the software does what is needed.

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A tool for clients and developers

An emerging trend among ConTech software companies is a shift of focus from selling to architects to targeting developers and clients, who may wish to understand site potential before hiring a design team. Tools that automate site analysis and feasibility studies allow them to receive insights into purchases at a much earlier stage. This has an impact on the architect’s traditional role particularly in the early-stage design process.

This shift presents both opportunities and challenges. While it may reduce architects’ involvement in early feasibility studies for some clients, it also creates an opportunity for architects to use these tools for clients who seek deeper data insights but prefer not to use the tools directly.

By accessing data and insights generated by GD solutions quickly and easily, architects could provide value faster, creating more refined designs that align with clients’ initial requirements. This approach suggests architects should adapt, adopt a solution, and potentially provide new services for clients. GD users could enhance their role in delivering data-driven projects with this approach.

Risks and challenges

While the potential benefits of GD are clear, there are some risks that users should consider carefully:

1. Quality vs. quantity: The ability to generate a multitude of designs quickly can be both a blessing and a curse. With too many options, architects may face decision fatigue, or find themselves sacrificing quality for speed.

2. Cost and learning barriers: For many architects, especially smaller firms, the cost and time to learn required to adopt these tools remains a hurdle.

3. Dependence on technology: Over-reliance on GD tools can sometimes overlook essential design considerations that come from experience, intuition, and human creativity. Designers who depend heavily on GD software should augment this with a hands-on design approach that allows for unique, site-specific insights.

How to assess GD tools

With the growing variety of GD tools, users need a consistent way to evaluate software that goes beyond features and marketing hype. This is why at ADDD, we have developed an assessment criteria, based on the Future AEC Software Specification (FASS).

The aim is to enable a consistent approach to reviewing software so different tools can be compared to each other. This assessment methodology was presented at AEC Magazine’s NXT DEV conference and has now been used to assess four Clash Detection and Issue Management software.

The outcome is a quantitative framework of questions designed to bring clarity and consistency to software evaluation. When combined with a qualitative approach, where users can communicate their findings and thoughts, a report can be produced that supports the AEC industry to have a consistent way to assess software.

GD tools will undoubtedly disrupt early-stage ‘‘ design within the AEC industry, offering powerful capabilities that allow users to explore, create, and iterate with unprecedented speed

The assessment provides a structured, objective way to assess GD tools on critical factors such as ‘Designing in Context & Scale’, ‘User Experience’, ‘Modelling Capabilities’, and the other criteria from the FASS. By applying the FASS criteria, users can identify tools that align with their needs, budget, and project demands, allowing them to make decisions that suit their requirements. This approach not only simplifies the selection process but also ensures that chosen tools meet the demands of modern AEC workflows.

I am also advocating for Best For …’ results, rather than one software being better than another, as this is too simplistic. In a landscape flooded with options, having a consistent assessment method like the FASS can be invaluable, helping users to navigate to the appropriate GD tool that is ‘Best For Their Needs’.

N.B. Information about the assessment criteria can be found here . ADDD also welcomes feedback on how software is assessed.

Charting a way forward

GD tools will undoubtedly disrupt earlystage design within the AEC industry, offering powerful capabilities that allow users to explore, create, and iterate with unprecedented speed. This will require adaptability, a consistent structure to assessing software, and a way to help strategic decision-making within organisations.

As GD options continue to search for their specific niche, AEC professionals have the opportunity to explore and embrace these tools as allies in their work, with the opportunity to lead to better client outcomes. With resources like the FASS Assessment, users can assess, compare, and select the solution that aligns with their organisational goals, empowering them to succeed in a digital future that balances creativity with technology.