Could AI mean we only spend three days a week in the office?

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Artificial Intelligence

This article is by Bruce Davison, CEO, GoSpace AI

Salesforce is just one of many to announce that they expect more than 65% of their workforce to come into the office only one to three days a week in the future, up from 40% before the pandemic. This seismic shift in demand for workspace and how the office will be used in the future has many obvious benefits but also poses many questions.

The opportunity

There’s no doubt that allowing employees to choose when they spend time in the office will enhance their experience and wellbeing, which in turn will boost productivity and engagement. It provides access to a greater talent pool, as there is no longer a need to hire within commutable distance of current office locations.

In theory, if people only come into the office 2-3 days a week, organisations should be able to reduce the amount of corporate real estate they occupy, spending the money instead on upgrading the workplace environment, or staff incentives, or R&D – the list is endless.

So, this emerging trend really is a win-win for both people and organisations. However, the biggest winner must be the environment, with net-zero being the ultimate prize. The corporate real estate sector has a significant role to play in the reduction of global carbon emissions, with every 100 ft2 of corporate office space generating approximately 1 tonne of CO2 emissions per year.

Heating, ventilation and air-conditioning systems use more than 60% of a building’s total energy consumption, and up to a third of that energy is often wasted. The UNEP states that the buildings sector has one of the highest carbon footprints – it currently contributes to 30% of global annual greenhouse gas (GHG) emissions and consumes around 40% of the world’s energy. And we’re continuing to build, despite global pre-Covid daily occupancy levels being measured at 50%.

The challenge

While the opportunity is huge, achieving this win-win is more difficult than it appears. How does an organisation match the supply of office space needed to reduce operational costs and environmental footprint with the increasingly erratic demand driven by 100% individual worker choice?

Historically there have only been two ways to allocate office space:

1. Manually: supported by technologies that measure usage and provide insights, along with interfaces that can help human operators allocate people into specific spaces.

2. Automatically: reserving an individual space via a booking system, but with no guarantee that when an individual is in the office, their key colleagues or manager that is essential for knowledge transfer will be in.

Let’s explore these two approaches in more detail. The first requires a human, usually an occupancy or space planner, to interpret historic data gathered from various sources (for example access pass readings showing when people entered and exited a building). They take this data and combine it with HR forecast data (new group structures and headcounts), and business and operational affinity data (which groups need to work together, which groups need to be located in specific locations etc) and overlay that onto building floorplans.

They allocate space to each team, based on all the variables they have been provided. Considering there are 62,815,650,955,529,469,952 ways of allocating 10 teams of 10 people to 100 spaces, it’s a complex and time-consuming job even when needs are static.

Now imagine if group structures and sizes are constantly evolving, and furthermore, group members only come in 2 days a week… clearly, this method is no longer appropriate.

The second requires a booking or reservation system, of which there are many to choose from. This technology, which is now over 20 years old, enables individuals to book office space when they want to, with few restrictions.

These systems support the individual-centric view of work, in other words, people fight for the space they need on a first-come-first-served basis, with little concern over supporting intra- or inter-group structures, much less overall organisational objectives and initiatives. Demand for meeting rooms increases as individuals are not co-located and now need additional space to meet together.

In the absence of an intelligent and adaptive underlying structure, this 100% free-for-all drives increasingly erratic demand. For example, Tuesdays and Thursdays might be incredibly busy, with the rest of the week empty. The indication is this approach could increase the total amount of space an organisation occupies to accommodate these wild fluctuations. So much for net-zero.

The way we want to work has changed, forever, and for the better. Gone are the days of everyone being provided a desk – it’s financially and environmentally damaging and both corporately and personally irresponsible. This is where new ways of thinking and technologies must play a greater role, to help us achieve our global goal of net-zero.

The solution

Tony Josipovic from global real estate leader JLL was recently quoted as saying: “Planning for tomorrow won’t work with yesterday’s tools”. Humans cannot process the amount of data required at the speed it’s needed, and existing technologies struggle to connect people efficiently. The only way to solve the complexity of the workplace to benefit people, organisations and the environment, is to take a different approach.

The workplace of the future can only be achieved by harnessing the power of artificial intelligence to support both individual choice, such as with smart concierge/booking technology that helps predict group schedules and reserve space, as well as via strategic AI which synthesises day-to-day booking data with organisational strategic input. This latter AI will primarily be focused on addressing overall dynamic resource allocation – that is ensuring scarce resources are allocated in a constantly changing environment in the most space-efficient and most organisationally effective way.

This new form of AI addresses what has historically been a slow, consultant-heavy process of strategic occupancy planning. Combining analysis, often from other predictive AI technology, with evolving strategic input, this technology applies spatial and temporal algorithms to adapt allocation of supply to continually match the ebb and flow of space demand. Connecting these different smart technologies together will enable organisations to find the necessary balance between providing individual’s choice to be productive on their terms while ensuring that the organisation can achieve their strategic objectives both financially and environmentally.

I believe the static workplace is and should be a thing of the past. The future workplace is dynamic, responsive and balances the needs of individuals with that of the organisation and environment.

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