Design

Data to Design: the new information tools for designers

How can design studios leverage social data in the physical workplace? A new report by Humanyze and WORKTECH Academy outlines the importance of new sensor technologies in measuring collaboration in the office

Facilities managers today have a solid and increasingly mature grasp of the practical role of data analytics in their work. Using utilisation and environmental data, they can calculate a range of workplace factors from air quality and levels of occupancy to predictive maintenance.

In comparison, the rich potential of data to the design process itself is only now being recognised by workplace designers and architects. The design professions are still on the foothills of fully understanding the relationship between data science and design of the physical work environment.

But that could be about to change according to a new report launched by data analytics pioneer Humanyze with WORKTECH Academy, Data to Design: bringing the right intelligence to redesigning the workplace. This predicts a burgeoning relationship between design and data science to create better workplaces for the future.

Information for design

Designers have always used information of different types to shape new workplaces, augmenting the basic ‘org chart’  (which sets out the organisational hierarchy) with user observations, interviews and space utilisation studies to create a richer picture. But much of this data to guide design decisions has, until now, been subjective and restricted in scale, due to the limited ways that human activity in the office environment can be measured.

Today, however, new data tools with cutting edge social sensor technologies can scientifically reveal the deeper patterns of interaction, communication and team dynamics within the workplace. The report asks: could data be set to refashion the entire design process?

The need for more accurate social data analytics stems from companies constant strive for the previously intangible metric of collaboration. In the changing landscape of the physical office environment, collaboration is notoriously difficult to measure. The Humanyze report outlines five key changes that are driving the need for more accurate social data:

Flexible working – people are working in more fluid and dynamic ways which makes it difficult to know who is collaborating and where;

The changing workforce – insight is required to understand how the multi-generational workforce interacts, we can no longer rely on demographic stereotypes;

Focus on experience – improving employee experience means looking at the workplace holistically from employee wellbeing and nutrition to social spaces and concentration space;

Technology changes – AI and machine learning will slowly start to take over routine tasks, and a greater focus will be placed on tracking creative work;

Smart precincts – the surface area of connected environments is growing, which prompts the need to understand how people use space across a wider field.

What data matters?

In the past, human observational data was integral to understanding how people connect and communicate. However not all communication is visible. More than 150 million emails are sent every minute; email traffic in one organisation alone can give a rich insight into interaction. Humanyze augments email, calendar and meeting booking data with the use of socio-metric badges that anonymously measure face-to-face interaction through embedded proximity sensors.

The report outlines two types of communication data which matters: cohesion data (the connection within teams) and exploration data (the connection between different teams). These types of data can help determine how people communicate within the microcosm of their team, and how the organisation interacts as a whole.

Experimenting with data

Data science is exactly that – a science. Hypothesis and theory need to be constantly tested with experiments to produce accurate and reliable results. The same applies with office design. Objective quantitative measurement means that companies can experiment with workplace design and discover interesting relationships between different variables, such as re-siting coffee points or rearranging furniture, lighting and partitions. Once a large data lake has been collected, organisations can use machine learning to predict patterns of interaction and communication.

The implications of data to design?

As many workplace designers will verify, office environments are in a constant state of beta. This permanently temporary approach means that designers can use a portfolio of quantitative data developed over a long period of time to validate existing designs. This will lead to a continuing relationship between companies and their designers, as changes are constantly researched, modelled and adjusted on a real-time basis.

This report not only outlines the new technological tools available to designers, but also new opportunities for long-term relationships with clients. In the future, could design studios be swapping out their materials libraries for data libraries?

Data to Design: Bringing the Right Intelligence to Redesigning the Workplace, Humanyze and WORKTECH Academy (2018). See the full report here.