As part of Think Work Out of the Box, our book on workplace transformation, Studio Banana sat down with leaders across various industries to hear their thoughts on what tools and environments can best serve the contemporary workforce.

Anton Oguzhan Andrews runs Microsoft’s Office Envisioning team creating next generation prototypes and videos that portray a vision of the future of productivity. Working with Harald Becker, the team’s Director of Industry Engagement & Research who focuses on emerging business and technology trends, both men take a human-centered approach to organisational strategy and exploring the new opportunities technology will offer in the next five to ten years.

Here are a few highlights from our conversation about the work environment as it stands today, what it means to drown in data, and the kind of flexibility needed to design for the future.

Studio Banana— We have heard you speak about well-being in the workplace, and about hydration in the most basic sense, i.e., drinking water. But you also used the term “hydration” to illustrate how information and content production should flow. Can you tell us a bit about how this concept could affect the physical and social environment of the workplace?

Anton Oguzhan Andrews— From our side, we can really observe a clash occurring when workspaces are designed for a world that really no longer exists. On one hand, you have the corner offices, meeting rooms and the accompanying long corridors, which reflect a rigid hierarchy. As a counter-concept, the open plan has been developed, but this doesn’t work well either. We all know the statistics. In short, today’s workplace is limited by these models of “old-school environments”. On the other hand, however, the world is evolving in terms of information volume and density, the speed of information generation, the connectivity between people, etc. Dense and complex network structures are gaining the upper hand. And these emerging networks cannot really evolve and flourish in the drywall boundaries of traditional workspaces. To explain the issue at stake through a specific example, think of how people collaborate in increasingly organic and ad-hoc ways: working processes have become very iterative – you do not necessarily know what you are going to be doing three hours from now – and considering these new circumstances, the idea of booking a meeting room doesn’t really make sense anymore. Whereas it might still work for some types of meetings, it tends to become a much smaller part of the pie and the larger one will really be these more organic, informal ad-hoc encounters. So in order to evolve and respond to these new needs, you should design for a fluid experience on a spatial and on a technological level because an activity-based workplace design functions on both registers. Only this will allow you to walk through a landscape that is fit for your work: a work environment that is fit for what you need to do for a few minutes, for half an hour, or for half a day.

SB— Can you briefly tie the discourse back to the concept of “hydration”?

AA— Well, out of these network structures emerges a “knowledge network” or a “cloud of content”. As you move around, knowledge travels with you and is customised depending on who you are, who you are with, what you are doing and what project you are currently working on. And as this cloud surrounds you, it hydrates the space you walk into with knowledge. Does this make sense?

SB- Conventional work environments are designed for information scarcity, but today we have what appears to be the opposite problem, information abundance. We are drowning in data. And it becomes a major challenge to quickly identify what is relevant from the mass of information available to us.

Harald Becker— Well, the concept of “knowledge network” we have described elsewhere, actually has a layer of artificial intelligence (AI) to it. It is not just about accessing data in a traditional way, as you would access the information stored in your physical files and folders. A knowledge network, ideally, brings the right things to the right people at the right time. The challenge is obviously how to foster this kind of connection across the knowledge network.

SB— And an additional challenge, presumably, is for the connections to be semantic.

HB— Exactly. The goal is to create those very rich links so that you actually work with a default co-awareness, if you like, of all the knowledge across the network.

AA— It is important to understand that this knowledge network consists of several layers. One of them is the data information layer. In a large company there are thousands of millions of documents floating around. Another layer is the people creating and co-creating the knowledge. So, ideally, when we hold a conversation, the knowledge network will understand that there may be another team working on a similar problem. This is very complex and there is a lot of engineering work that remains to be done to fulfil that vision. But it describes some of the work that we are particularly excited about and that our teams are already working towards today.

HB— It is certainly some of our more exciting and challenging work: a special hurdle being the AI, which is still in its very early stages in the industry. One of the issues at stake is how to identify relevant, or useful and effective information. How to avoid littering your workspace with insights that you don’t care about, connections to people that you just don’t want to know about. In other words, how do you avoid creating noise and instead be helpful? An overload of irrelevant information ‘noise’ would be the dystopian version of this.

SB— To bring back our discussion to a spatial dimension, the dissemination of knowledge throughout a company can also be a sensitive aspect of workplace design.

HB— Of course, a part of most companies is usually working on more sensitive or even confidential projects. Consequently, we are also studying appropriate technologies to safeguard and filter information. This issue you refer to, is also related to the question of privacy; of private versus public data. And, to briefly summarize our approach, we divide the devices by their dimension: small-scale devices like your mobile phone or tablet, versus large-scale screens and displays, holograms, etc. We tend to treat the small-scale, mobile devices as private and the large-scale, architectural and infrastructural devices as inherently public. The data fed by both is also treated very differently.

The full conversation, where we discuss technological resilience and use examples of Studio Banana’s work with Ernst and Young to illustrate these concepts, can be found in The Phygital Scenario chapter of Think Work Out of the Box.

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