As changes continue to modify efficiency, productivity and the business climate of the AEC industry, some companies are looking at ways to reduce the use of consultants and complete work inhouse. Automation can help with this shift in processes, and the decision to use computer automation depends on company leadership.

Instead of being wary of the time it will take to implement technology improvements, company leaders may be better served by looking past that to the productivity that can result. The struggle comes from having a “time mentality” as opposed to a “task

mentality.” Sometimes in construction, the project estimate can guide expectations for how quickly a task should be accomplished. Without proper contingency planning, external forces can wreak havoc with those expectations.

Using more automation can help a company be resilient, while decreasing costs. If company management can maximize the amount of time design staff spends actually designing, that can lead to more innovative outcomes on projects. Relegating some mundane tasks to automation can maximize an important human aspect of a project: the decision making. Using computer automation enables decision makers to view the entire project, gather relevant data and make informed choices. This gives a company the opportunity to achieve a project’s targets.

Ideally, all teams are working toward a cohesive goal: producing a good product for the owner.

Implementing technology should benefit all teams on a project. Data needs to be transferrable and translatable. Tech should facilitate communication among owners, architects, contractors, and consultants. If they can all use the same project model for design and analysis, it reduces discrepancies in assumptions and modeling.

Design revisions are a real problem for a majority of jobs. As a result, teams can end up pushing data around instead of designing. According Patrick Chopson of Cove.Tool, reducing one design revision per project per year can result in a 3% profit increase for a company. This can happen when engineers and architects collaborate more productively.

Cove.Tool is a cloud-based platform that streamlines the energy modeling process, as well as team communications. By reducing data translation issues, a building information model (BIM) can transition smoothly to a building energy model (BEM).

The data processing platform analyzes a project’s performance and identifies potential cost and energy savings in the early stages of design. It performs energy modeling from beginning to end.

Machine learning can be employed as part of this process, starting with baselines, then using an algorithm to compute a set number of good options for the designer to choose

from. Thousands of alternatives can be narrowed down through the use of parametric design. In this case, the automation helps people figure out which option(s) get closest to the optimum they’ve identified.

When it comes to designing for sustainability and limiting carbon emissions caused by building and operating buildings, the responsibilities are diffuse. This can be addressed by reducing the data loss among teams in order to come up with designs that manage the carbon issue. Automation can help balance the cost tradeoffs among energy efficiency objectives.

Tune in to Season 3, Episode 2 of AEC Disruptors podcast to hear from Patrick Chopson  of Cove.Tool about automation, collaboration, machine learning, sustainability, and more.

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