AECOM’s Andrew Laing – the global practice leader for the firm’s Strategy Plus unit, formerly known as DEGW – asked me to contribute the foreword to this year’s Annual Review, which you can download in its entirety here. But I’ve taken the liberty of re-posting my thoughts on the future of work and the office below, some of which might sound familiar…

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As someone who hasn’t worked in an office in more than a decade, I possess a unique perspective on the future of work, especially as it pertains to Strategy Plus. You see, I’m an accidental savant who read Frank Duffy’s Work and the City as my primer in office design. When 2008 is Year Zero in your understanding of how to work, the following propositions start to make a lot of sense:

Workspaces create value, not costs. It should be obvious to anyone invested in innovation that realizing complex ideas demands collaboration, that collaboration requires communication, and workspaces shape how we communicate. They’re more important than any org chart. But try telling that to companies obsessed with “wasted” space.

If clients will only manage what they can measure, then measure it. Again, this is obvious. But it’s also maddeningly difficult – how does one prove the value of a coffee machine? Perhaps this is where sensors and “sociometric badges” will come in. The first test of a quantified organisation should be learning how its office works.

Your workspace should conform to you. Someone once demonstrated to me the 500 possible office layouts they’d generated for a client, who would pick one and keep it for at least a decade. This is nuts. Workspaces should continuously evolve to support workers – call it the real-time office.

Ecosystems need membranes, not walls. No enterprise is an island, as it belongs to an “ecosystem” of partners, suppliers, and customers. This is conventional wisdom for Harvard Business Review subscribers, but it rarely manifests in the office. Workspaces should be permeable, welcoming outsiders while freeing mobile employees.

Serendipity trumps efficiency. Those outsiders bring the potential for serendipity, i.e. unplanned ideas or encounters that result from the discovery of tacit knowledge – the hunches and expertise that can’t be written down. These moments and meetings are the seeds of something new and unknowable, and thus can’t be factored into metrics measuring efficiency.

The city is not an extension of the office. That’s reversing the relationship: the office is merely one island in a sea of places to work. Duffy knew in 2008 that we would never realise the full potential of mobile workers without understanding that the scale had changed. Seven years later, we still haven’t.

Free HR, FM, and IT! All of these changes are predicated on radically different roles for what are traditionally powerless back-office functions. Who should be working together, where and how are all strategic questions and should be treated as such.

But then again, you knew this already. What Duffy envisioned in 2008, Strategy Plus is creating today.

I was delighted to learn that “Workspaces That Move People,” my feature in the October 2014 issue of Harvard Business Review written with Ben Waber and Jennifer Magnolfi, has been chosen for inclusion in HBR’s 10 Must Reads 2016: The Definitive Management Ideas of the Year from Harvard Business Review. You can read the entire essay here; the jacket copy is below:

We’ve combed through the ideas, insights, and best practices from the past year of “Harvard Business Review” to help you get up to speed fast on the relevant ideas driving business today. Revisit these topics now to make sure you’re incorporating the smartest, most up-to-date ideas in your organization, or keep it as a reference so you can access these memorable pieces when you need them most. The collection includes articles on leadership, strategy, and innovation, as well as articles to help you manage yourself and others. A year’s worth of management wisdom, all in one place.

I had the honor and pleasure of appearing on “Numbers and Narrative” – a weekly podcast devoted to the stories we tell ourselves about the quantifiable – co-hosted by The Fires author Joe Flood. We managed to dissect the promises and perils of the smart city in a brisk 45 minutes. Please give it a listen.

I’m currently in the throes of the fall conference season, which means traveling 44 hours to-and-from Singapore to spend just 36 hours attending the Abraaj Group’s Annual Forum – and finding time to take MIT’s autonomous car for a spin. Or did it take me for a spin? I’m not sure. A quick recap and preview of my travel schedule follows below, grouped by a few themes. (Not included: my 20th high school reunion.)

The future of mobility. I kicked off September at the Los Angeles office of Gensler with a talk on the future of urban mobility, drawing upon a combination of NYU Rudin’s “Reprogramming Mobility” project, my report for the University of Toronto’s Global Solution Networks, and my ongoing research for the New Cities Foundation’s Connected Mobility Initiative. I revisitied the theme later in the month with both the Federation Internationale de l’Automobile (FIA) and the Automotive Fleet Leasing Association (AFLA), both whose members are still coming to grips with the implications of mobility-as-as-service. (I sat down with the FIA for a brief chat following my talk.)

At the end of September, I flew to Toronto to present to the transportation task force of the York Regional Council, a body comprised of elected officials representing nine municipalities and more than a million people immediately north of Greater Toronto. The region expects to add an additional 500,000 residents over the next few decades, which has councilors and staff scrambling to implement bus rapid transit and a long-term strategy to densify development, increase service, and lure people away from their cars. I was honored to encourage them to keep one eye on the horizon for how the advent of new technologies and services that help or harm their plans.

From there, it was onto London for the second annual Cities on the Move conference hosted by the New Cities Foundation and Google, where I was interviewed by the BBC’s Gareth Mitchell. I moderated a panel on how cities might start to construct mobility-as-a-service platforms, beginning with Michael Glitz-Richter’s work in Bremen twenty years ago to current efforts to build a seamless transportation mesh in Finland. Next month, I’ll be the master of ceremonies at the Disrupting Mobility conference at the MIT Media Lab, followed by hosting the opening session of the 50th anniversary conference of the California Transit Association.

The future of work and the office. My other great passion besides transportation, this was the theme of my brief remarks at the Municipal Art Society Summit in New York this month, along with several sessions I moderated for the Abraaj Group in Singapore – although I’m afraid I can’t say much more than that. Nor can I say much about the master class I led for a Fortune 20 company on “serendipity engineering.” But next month, I’ll be in Paris for the OECD’s New World Forum, where I’m set to join a panel discussing the future of human labor (versus, you know, the robots).

The future of travel and tourism. In September, I had the pleasure of addressing both the Texas Travel Industry Association and the International Luxury Travel Meetings about the importance of urban networks, policy, and infrastructure in travel and tourism going forward. One idea that had special resonance with both audiences: that convention and visitors bureaus should fund new attractions and infrastructure in the mold of New York City’s High Line or Dallas’ Klyde Warren Park (which was built atop a highway). I’ll have the chance to expand upon this idea next month when I’m back in Dubai to help dream up ideas for a certain World’s Fair on the drawing boards…

While in London earlier this month for the second annual “Cities on the Move” conference hosted by the New Cities Foundation and Google, the BBC’s Gareth Mitchell kindly invited me back to once again appear on Click, the technology show he hosts for BBC World Service. I can’t seem to embed the audio for some reason. Please click on this link and fast-forward to the 8:00 mark for my high-speed thoughts on mobility-as-a-service.

(Originally published at Fast Company on October 14, 2015.)

Doctors have just discovered a previously unknown relationship between the long-term recovery of spinal cord injury victims and high blood pressure during their initial surgeries. This may seem like a small bit of medical news–though it will have immediate clinical implications–but what’s important is how it was discovered in the first place.

This wasn’t the result of a new, long-term study, but a meta-analysis of $60 million worth of basic research written off as useless 20 years ago by a team of neuroscientists and statisticians led by the University of California San Francisco and partnering with the software firm Ayasdi, using mathematical and machine learning techniques that hadn’t been invented yet when the trials took place. The process was outlined in a paper published today in Nature Communications, and hints at the possibility of medical breakthroughs lurking in the data of failed experiments.

“What was thought to have been a boondoggle turns out to have great value,” says Adam Ferguson, a principal investigator at UCSF’s Brain and Spinal Injury Center and one of the paper’s authors. Just how much is unclear until trials are conducted in humans, but the finding raises several interesting questions–notably whether scientists should publish their raw data for posterity and whether their time and funding would be better spent poring through old experiments than conducting new ones.

Ferguson’s team began by meticulously reconstructing data from multiple studies comprising some 3,000 animals, including more than 300 from the Multicenter Animal Spinal Cord Injury Study conducted at Ohio State University in the mid-1990s. Rather than draw on only published results, he and his colleagues contacted each researcher and asked for unpublished data and lab notes as well. “They were very cool about this,” says Ferguson. “A lot of scientists in other disciplines wouldn’t be–they’d feel like you were auditing them.”

And perhaps for good reason. A paper published in The Lancet last year estimated less than half of all findings make it into print, with the remainder comprising a “long tail of dark data” that may hold the key to science’s reproducibility crisis. Spinal cord injury researchers are facing a crisis of their own. Twenty years after Christopher Reeve’s paralysis shone a spotlight on their field, there haven’t been any breakthroughs. “There are no drugs,” Ferguson says. “It doesn’t have any real, agreed-upon therapeutic approach. That’s embarrassing. We should have something, at least.”

Instead, they have failures. One reason is the sheer number of variables. Spinal cord injuries are enormously complex and thus still poorly understood compared to other systems. Efforts to isolate simple causal mechanisms have proven elusive, “and that’s a real threat to discovering new therapies,” says Ferguson. So he and his team thought to test old, dark data again, this time using techniques designed for uncovering hidden relationships between large numbers of variables.

Their tool of choice was topological data analysis (TDA), a technique developed by Stanford mathematician (and paper coauthor) Gunnar Carlsson, using concepts from geometric topology–the study of highly complex shapes–to find patterns hidden in large datasets. Carlsson is also president of Ayasdi, the firm he cofounded to combine TDA with machine learning techniques to probe datasets for relationships between variables. (Ayasdi is one of Fast Company’s Most Innovative Companies in Big Data.) Before Ferguson had thought to use it for probing spinal cord injuries, Carlsson and others researchers had successfully employed TDA to find a unique mutation in breast cancers hiding in data sets that had been publicly available for more than a decade.

What sets Ayasdi apart from traditional competitors is its black box model: The software searches for patterns without human supervision (or bias) before rendering the results as a network diagram of variables for further analysis. “It’s the reverse of traditional hypothesis-driven science,” says Ferguson. “We could never have found this correlation with hypertension using traditional tools, because with thousands of variables to test, it would have never occurred to us.”

Does this mean that the process of discovery is over? That all new ideas will come from machines probing data and not from human ingenuity? While he rejects this “end of theory” idea as overblown, Ferguson does believe the first step in the scientific method–observation–has been radically complicated by Big Data and ripe for machine mediation. Or as Ayasdi CEO Gurjeet Singh told me earlier this year, “Traditionally, you have to be lucky, and then you have to have a stroke of insight. But the probability of being lucky is lower and lower over time, so you need these systems to do that work for you.”

In the case of the spinal cord injury data, Ayasdi’s TDA-driven approach mostly confirmed what researchers already knew: The drugs didn’t work. But the discovery of high blood pressure’s detrimental effects on long-term recovery has immediate implications for human patients, namely whether the use of hypertension drugs immediately after their injuries and before surgery could improve outcomes, a hypothesis Ferguson and colleagues intend to test shortly at UCSF.

In the long run, Ferguson believes retroactive data mining is “a worthwhile approach,” especially considering how much less expensive it is to sift old data again than run new trials. “For a little more than a million dollars, we’ve opened $60 million worth of value.”

The brand consultancy PSFK, in conjunction with the architecture and design site Architizer, kindly asked me to contribute my thoughts to their new report on the trends driving the future of design. I’m in great company with architects Michael Murphy, Vishaan Chakrabarti, and Winka Dubbeldam, among many others. Please page through it above, or download to read at your leisure.

While at reSITE in Prague this summer, I sat for a brief interview on engineering serendipity, Uber, and much more. Enjoy.

(Originally published at Fast Company on September 22, 2015.)

I almost didn’t notice I was wearing it, at first. The plastic box strung around my neck was roughly the size and weight of a deck of cards, lighter than I expected. It was only when I spotted the occasional flash of blue light that I remembered this “sociometric badge” was listening to everything I said, where I said it, and to whom–especially if they were wearing a similar device around their own necks. In those cases, our conversations were captured for analysis–ignoring what we said in favor of how long we spoke, and who did all the talking.

I started to turn painfully self-conscious around my first visit to the bathroom: Did the badge know I was in there? Would it listen? Would it freak someone out that I was wearing a giant sensor in the stall next to him? By the time I left the building for lunch, I had zipped it beneath my jacket, less concerned that it was counting my every step than having civilians think I was some new species of Glasshole.

Like Google Glass, sociometric badges were prototyped in Alex “Sandy” Pentland’s Human Dynamics Lab within the MIT Media Lab–a place where his cyborg doctoral students once wore keyboards on their heads and no one thought it strange. Unlike Glass, the badges are still a going concern–five years ago, Pentland and several former students spun out a company now called Humanyze to consult for such companies as Deloitte and Bank of America. Just as Fitbits measure vital signs and REM cycles to reveal hidden truths about their wearers’ health, Humanyze intends to do the same for organizations–only instead of listening to heartbeats, its badges are alert for face-to-face conversations.

For two weeks in April, Fast Company was one of those subjects. (Humanyze provided the badges and analysis for free.) Twenty Fast Company editorial employees–and me, as a visiting observer–agreed to wear the badges whenever we were in the building. Our goal was to discover who actually speaks to whom, and what these patterns suggest about the flow of information, and thus power, through the office. Is the editor in chief really at the center of the magazine’s real-world social network, or was someone else the invisible bridge between its print and online operations? (Or worse, what if the two camps didn’t speak at all?) We would try to find out, though we would be hampered somewhat by the fact that not everyone was wearing a badge, and we didn’t give Humanyze the full range of data, like integration into our email and Slack conversations, that would allow the company to truly understand our work relationships.

More importantly were the questions we chose to not ask: How did these patterns impact performance? Should editors and writers talk less or more, and what did it mean when they talked amongst themselves? Did it result in more posts on Fast Company’s website, or more highly trafficked ones? Demonstrating and understanding these relationships are what Humanyze’s clients pay for; perhaps we were too scared to learn.

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(Originally published at Fast Company on September 21, 2015.)

Imagine if, a few years from now, you’re in a meeting. (Even in science fiction, we spend most of our time in meetings.) Everyone’s phones are on the table; your employee badges hang taut around your necks. You start to interrupt your coworker when all the phones chime at once. Without glancing, you know the Meeting Mediator has called a foul on you: it’s someone else’s turn to speak. While checking your email in a fit of pique, you receive an automated request from HR to introduce your colleagues Kavitha and Sasha over Slack. Evidently, they’re working on the same project but you haven’t met–despite sitting down the hall from each other.

Messages like this were creepy at first, but most of the changes to your office have been for the best. Whoever has been rearranging the furniture at night has made it easier for teams to gather and chat. You’ve met more peers in the last six months than in the first three years of working here, thanks to the rotating coffee machines that replaced the single kitchen for the entire company–a dumb idea inspired by an apocryphal story that the placement of Pixar’s bathrooms was designed to create more human interaction. Amazingly, without you really noticing, your once-burning itch to quit has finally cooled.

If this future comes to pass, it’ll be thanks to the box of sensors slung around your neck masquerading as your ID. These “sociometric badges” already exist, created by a Boston-based company called Humanyze. Using a combination of microphones, infrared sensors, accelerometers, and Bluetooth, they measure wearers’ movements, face-to-face (and badge-to-badge) encounters, speech patterns, vocal intonations, and even posture to measure office statistics, like who’s really talking to whom, for how long, and where.

THE QUANTIFIED ORG
Armed with this information, clients such as Bank of America and Deloitte are in turn mapping these office behaviors to the metrics that matter: sales, revenues, retention rates. You may have already met your quantified self; now say hello to the quantified org.

Humanyze is hardly alone in bringing sensors to bear on the office, but its pedigree and approach stand out in a crowded field. The badges are the product of nearly a decade of research at the MIT Media Lab into the nearly subliminal signals buried in our speech. They represent a massively counterintuitive bet that what we say to each other is much less important than the tonality, pitch, and body language of how we say it, a proposition borne out over hundreds of published papers and experiments.

True to the spirit of Moneyball, Humanyze specializes in debunking conventional wisdom around performance, although typically in an office rather than an arena. Its favorite example comes from one of Bank of America’s call centers, which suffered form the usual problems of burnout and higher turnover. A stint wearing badges revealed that the most productive workers frequently shared tips and frustrations with their colleagues. So the company recommended ditching individually staggered breaks in favor of 15 minutes of shared downtime. This supposedly less efficient arrangement–no one is manning the phones–led to shorter calls and lower stress while increasing productivity by more than 10%. “If you can use data to figure out things that are pinpoint small and easy to implement,” says Waber, “they can have order of magnitude effects.”

Two of his favorite tools are cafeteria tables and coffee machines. In one case, simply increasing the size of table from four people to 12 and instituting company-wide lunch hours led to individual productivity increases as high as 25%, thanks to better communication within teams and larger social networks. In another engagement, Humanyze helped Cubist Pharmaceuticals (since acquired by Merck) increase sales by 20 percent, or $200 million. Badge data revealed when Cubist’s sales force increased their interactions with coworkers on other teams by 10%, their sales also grew by 10%. To increase mingling among teams, the company replaced many small coffee stations with several larger ones, imperceptibly seeding the encounters it hoped to see.

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