Early stage feasibility assessments are key to realizing development potential, yet for most they are still a manual, time-consuming process with very little verifiable data as output. A new methodology exists, however, that allows those in architecture, engineering and construction to automate and drastically improve results. Utilizing cloud-based generative design software, thousands of design options can now be explored to find the ideal solution.

With an automated feasibility design process using generative design, designers and engineers are able to outline design goals along with any specific constraints. These designs can be imported directly into BIM authoring platforms for further design development, as well as detailed provisioning and commercial viability calculations. Using the development's overall commercial criteria, generated design options can then be ranked and filtered down to a few high-performing options, allowing for significant capital expenditure decisions to be truly data-driven and based on provable datasets, compliant designs and verifiable commercial calculations.

Shortcomings of the traditional methodology

With any new site, challenges arise around the feasibility of development and, in turn, realizing the potential return on investment. Given the complexity and often limited resource or fee available, the process behind early stage feasibility can regularly be detrimental to the outcome.

Engaging with an architect primarily, a client will seek to develop the project objectives and brief through outlining any parameters and constraints that may affect matters such as cost, programming and sustainability. Often with a small team, an architectural office will develop a few different options to present to the client and look to develop one or two of these in more detail. With this in mind, it’s difficult to conceive every possible solution and explore all tangible outputs.

The process to understand the feasibility of any potential option is a linear process and often requires other external consultants to contribute at some stage. As a result, something that meets the architect’s requirements initially can often fail when an MEP engineer runs their calculations. If this happens, the process can frequently need to be repeated to find a solution that works.

Embracing a tech-enabled approach

As with all new technology, and particularly within the AEC industry, there is an initial reluctance to adopt any new methods of working. This can be seen all the way back to when companies began to move from the drawing board to CAD. While frustrating on one hand, it also means that the AEC industry is ripe for innovation, but only innovation that works and brings tangible benefits.

There is currently a growing influx of companies aiming to fill this “innovation void,” including giants like Google and Amazon, all looking to provide value in an industry otherwise foreign to them. As more and more companies try to tackle outstanding problems, the speed of adoption over the industry as a whole will increase.

By enabling a more data-centric approach to early stage feasibility, calculations and provisions can be automated with mathematical algorithms designed to output the desired metrics. With the computer now doing much of the heavy calculations, designers are free to concentrate on more complex issues. Rather than creating spacing diagrams and adjacencies to find an optimum solution manually, this part of the process can be completely automated.

The limit and speed at which an algorithm can work far exceeds the capability of an individual or even a team, therefore allowing for a far greater number of options to be evaluated.

Looking ahead

As it now stands, the potential for cloud-based generative design is huge, and real estate owners, developers and general contractors stand to benefit the most. The ability to quickly understand the viability of a site prior to any engagement (and get feedback from multiple sites instantaneously) is tremendously valuable. Embracing this new approach will transform a traditional design process into a computational one that can be leveraged for true business innovation.