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COVID-19 call for partners

Mark Thorley

COVID-19 call for partners

Introduction

Many companies right now are trying to find safe and practical ways of repurposing the workplace. There are many ideas going around in articles and reports - some encouraging changes in behaviour or staggered working patterns or reducing office capacity, while others push for greater flexibility to work from home and ensuring that work spaces are thoroughly cleaned.

But is this enough? Will anyone analyse or monitor the impact of these measures to relevant metrics or provide statistics on the differences that these changes could make?

Safety and wellbeing is now more important than ever and making sure people feel confident returning to the office is key to getting workspaces open again. At matterlab, we think that providing tangible metrics on the impact of these actions is essential for getting people back into the office safely.

We are looking for partners who can help us to build the tools required to tackle these issues. For that, we need data from teams who are trying to go back to work.

Generative design as a solution

Over the last year, we have been working closely with Autodesk to help them define their generative design offering and its application in our industry. One of the first studies around generative design by the Autodesk Research team was for the design of their new office in the MaRS Innovation District of Toronto. The goal was simple: could a computer identify an optimal floor plan for the site? It had to be based on measurable goals like work style preference, adjacency preference, low distraction, interconnectivity, daylight and views to the outside. And the answer was yes - the computer was able to balance trade-offs based on real data to find the best design.

Since this study took place, our team have been actively working with generative design approaches, developing other solutions and workflows for the AEC industry on a wider scale. We even developed an online e-book which covers many of these topics in detail .

We have always been strong advocates of automation within AEC and a lot of our work with our partners has been focused around developing algorithms to generate, evaluate or evolve designs. These new technologies can allow us to analyse and iterate floor plan design options much more quickly to see what the true impact is and find the best solution available.

Optimising office layouts for COVID-19 with generative design

Access routes and wayfinding

We have already seen one-way systems and distance markers or regulations in supermarkets. This strategy is now making its way into office spaces as they look to reopen.

While this is a sensible idea, we still lack information on the impact of this approach. Do markings on a floor really help prevent the spread of infection? What analysis is being run to ensure they’re n the correct positions, in places where people will take the most notice? Do these measures breach fire regulations that define minimum distance to exits?

These are questions that need to be answered, especially for companies with large teams or big offices. We have developed algorithms that can find the best access routes in a building. What we found out is that one-way systems will likely lead to long routes from desks to amenities and, worse still, fire exits. We need to explore options here and balance trade-offs to find a suitable approach for everyone.

Locations of handwash stations and sanitiser units

Even before we entered lockdown, we began to see sanitiser units appearing on walls and doors. We need real assessments on this to make sure that they’re positioned in the best places for people to access, whilst also taking into consideration things like communal areas or meeting rooms, where group work might still be happening. Staff should be able to access these points frequently without having to travel long distances, but also without having to pass a large number of people. By leveraging data, we can be more strategic about how we implement facilities like this

Minimising interactions

When the open-plan offices were introduced in the early 2000s, workplaces became less siloed and more open for collaboration. Interestingly, it’s this open-plan approach that will come under the most scrutiny now.

Interactions will need to be limited and social distancing maintained in the new office environment. Lots of people online are already discussing potential solutions like reducing the capacity of meeting rooms and introducing plexi-glass barriers between desks or seating in breakout spaces.

Great work happens when people collaborate, so how can we find a balance between maintaining productive ways of working and ensuring that team members are safe? One option could be to create scoring systems, based on order of importance of interaction. Doing that can help teams to decide which interactions are the most useful for getting things done. After that, we can find alternative ways of working for non-essential activity.  

And what about people going to get a coffee or going to the toilet? How many people would they pass en-route and how many of those can be avoided? We’re not suggesting set toilet breaks, but instead that we use data to better understand the risks people face. In a single hour, for example, we could say that on average each staff member might interact with five other team members per hour. If we can find ways to reduce that number by changing office design or creating new ways of working, then we can create safer workplaces for our teams. Generation and evaluator algorithms can be used for this.

Optimal desk arrangements and seating layouts

There have already been a couple of posts online looking at the layout of desks and even staggering seating to ensure a 2m or 6ft distance between staff members. While this is a good start, we need to take it further. Just simply halving the number of staff in the office at any one time or moving desks further apart will likely have some impact, but how much? We should be producing real data around why this approach is effective and making decisions based on that evidence. Governments all around the world currently are making decisions based on mathematical models of the spread and behaviour of infectious diseases. We should be using similar principles to analyse our future workplaces.

So how can you help?

With all that said, it now makes sense to apply our expertise and help companies make data-driven decisions by turning their return-to-work strategies into useful technology. To date, we have been working on a prototype that analyses previous floor plans and creates suggested layouts based on lowering interaction levels. The approach is to specify the desired average level of interactions for the office and the algorithm creates a layout with the optimum percentage count.

We are actively looking for partners who are building their return-to-work strategy, and who need to find ways of gathering data to support their approach.

We have experience building these algorithms and we have the expertise in our teams to build ones to tackle these issues. That said, what we don’t have right now is the datasets required to shape them and to make them truly effective. Nor do we have the experience of facilities teams who are trying to solve this huge problem. But with this data, we can make informed decisions for new layouts and can help both governments and employees to feel comfortable returning to work.

If you are a company who can help us to get this sorted, please get in touch.

Further reading

WIRED

WeWork

Perkins Will

Kean Walmsley

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