In my previous blog post of this two-part series, I talked about the importance of face-to-face communication in hospital wards for exchange of information and socialisation and the development of a new single measure – SCI (Spaces for Communication Index). SCI measures space effectiveness in the form of maximising communication opportunities which is crucial for good healthcare outcomes and can be applied to dynamic environments. In this blog post I will talk about co-working spaces where communication and collaboration is equally important and explore what the SCI measure can tell us about these spaces. If you want to know more about the role of design of co-working spaces in shaping collaborative behaviours, you can also check out this blog.
Following the spread of COVID-19, a lot of people have discovered that they can work from home, but that does not necessarily mean that they will want to do so forever. Entrepreneurs, business owners, and freelance workers choose to work in a co-working space because of the social networks and local connections it provides and to avoid loneliness. The community dimension of co-working spaces is important for its businesses and it will be critically important for recovery and rebound in post COVID-19 times. Business owners will seek the support of their community in finding clients and discussing strategies to overcome financial difficulties.
The key metrics that organisations usually use to assess workplaces focus on efficiency. For example, co-working providers measure occupancy and membership turnover. The higher the occupancy and the lower the turnover the more efficiently used the space is. However, the problem that designers of co-working spaces face is how to best design the space so that it encourages chance encounters. Members want to know how to choose which space to rent other than just taking into account cost and size. One factor that has been shown to be important for potential members is how well the co-working space will provide them with connection opportunities. Similar to hospital wards, co-working spaces are environments where people have dynamic work patterns, they use different kinds of spaces during a working day and visibility is key to create casual collisions. I developed SCI based on in-depth observations in six hospital wards and showed that the higher the index, the better the quality of care. I was interested in applying the measure to another building type to see what new insights this different way of seeing can provide and chose co-working spaces since they exhibit similarities to hospital wards.
I applied SCI to six co-working spaces to compare and contrast their spatial layouts according to their likely degree of sociability. The floor plans of these spaces were available online and varied in size from 800 sqm to 1800 sqm. Actual outcome statistics e.g. rental income or observational data to identify the most frequently traversed paths were not available. This analysis mainly aimed at exploring how SCI could be applied to other types of workspaces with dynamic everyday practices.
The six co-working spaces showed marked differences in their degree of sociability as measured by SCI. Without the in-depth observations that I had available in the hospital wards, I used existing knowledge and understanding of movement patterns in workspaces to identify key spaces that would likely be frequently traversed, including assigned desks, tea points, meeting rooms, print rooms, the entry to the floor level and the WCs. I also tested various scenarios of proportions of routes traversed and found that these had no significant impact on the fundamental differences in SCI index conferred by the spatial layouts in each co-working space. In other words, the SCI index was explained by differences in spatial factors.
The SCI scores of the six co-working spaces had a strong positive relationship of 68% with size and of 75% with the average connectivity of the plan which measures the average size of spaces and the viewsheds they provide. This meant that the larger the floor plate and the average connectivity of the plan, the higher the index value.
Using the same floor plan data within a single co-working space, I also looked at the locations of desks which have high SCI values. The results showed that desks whose occupants would have to pass by or near a tea point en route to other ‘attractor’ facilities had higher SCI scores and thus those occupants had a greater potential for chance encounters. Intuitively, those sat in open plan spaces would have higher SCI scores, however this was not always the case showing that being located in a more visible area does not necessarily lead to higher opportunities for interaction.
SCI is an objective method that can be used for comparing design options of different hospital wards and in this blog post we investigated its application to co-working spaces. The results of this study highlighted the potential usefulness of the application of SCI in co-working spaces, helping designers to identify the best design solution that would maximise opportunities for interaction and help members choose their seat location. Six co-working spaces may be too small of a sample to draw definite conclusions and more case studies as well as performance data would be required for fully testing the index on co-working spaces. Still the analysis shows that co-working spaces appearing similar at first sight do in fact differ markedly when assessed in terms of their potential for communication. If you are interested in having your co-working space analysed, get in touch with us!