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P. 54
BUSINESS SOLUTIONS
Collaboration in the Era of Mobile
and Machine-Learning
Therese Sullivan
Principal
BuildingContext Ltd.
Ididn’t know that using traditional email was such a sign of de- “Lots of people are trying to ‘solve’ email…
crepitude, but I work primarily on a PC in an office. When you Maybe the solution will be that everyone
are a mobile worker that primarily accesses email via phone or
tablet, you have no tolerance for long dumps of unfiltered email who uses email will die off.”
and the related risks of missing or losing important notifications.
You’ve been waiting for something new. Here is a summary of —Ben Evans, Analyst
how Ben Evans and other tech observers describe the evolution Andreessen Horowitz
of email:
My current angle of interest in learning/w platforms comes from
• email = ‘dumb’ file manager my work creating training and marketing content for building
• email + machine learning for auto-cleansing = Google Inbox commissioning firms. With the current perpetual commissioning
• chat and messaging are more direct and effective for com- model, their charter extends to transforming the client building
operations staff into a self-learning organization. This work has
municating via mobile: SMS, iMessage, WhatsApp, Instagram, me asking “How can content for notifications, learning and
SnapChat, Facebook Messenger, BBM (formerly known as collaboration about buildings be organized and shared in a
BlackBerry Messenger) way that provides the best experience for all the target users—
• single-tap, zero-character messaging = YO, The YO app can commercial building operations and facilities management staff,
be combined with the online service IFTTT (“If This Then as well as occupants?”
That”) to turn on and off lights, or perform some other sim-
ple activate/deactivate function in home automation. It’s worth noting that Google Inbox is not receiving stellar
• Team chat apps = next frontier in collaboration. Services reviews by all its early users. Intelligent algorithms can be pretty
like slack.com merge all your communications from email, dumb when they first start trying to predict human preferenc-
various messaging services and push-notifications from es and behaviors. But, they get better with adjustment. This
integrated vertical apps into an integrated, searchable feed raises more challenges and questions, such as “How can we
get out ahead of the algorithms and better train them to do
Facilities managers and building operations teams have likely our bidding?”Then, considering the tech tool feedback loop
already migrated away from traditional email. Just as an app phenomenon, “Can the learning we engage in to define better
like Google Inbox is set to eclipse email, so is machine-learning machine-learning rules for our mail, messaging, social media
technology transforming the business of managing buildings— feeds and other collaboration tools help us improve our skill at
and the business of collaborating about the management of operating and occupying intelligent buildings?”
buildings. Again I have to thank Ben Evans for stating what I’m
trying to say in a simpler way. At GE’s Mind + Machines event A paper just released by Professor Julia Day, formerly of
in October, he made the simple point that the tech tools we Washington State University and now with Kansas State
use to conduct business, eventually change the business we’re University, finds that “More than one-third of new commercial
conducting. building space includes energy-saving features, but without
training or an operator’s manual many occupants are in the dark
Ben Evans, Andreessen Horowitz about how to use them.” Based on another university study,
Carnegie Mellon University (CMU) Professor of Architecture
Vivian Loftness recently said, “Automation has led to more com-
plexity, leaving the occupants of all these offices disempowered
and uncomfortable.” Both sources agree that over-dependence
on automation is a problem and that getting more people-en-
gagement in machine-learning is the way forward. As with
email, there is this preliminary sense of “All this automation is
making us work too hard,” along with the promise that if people
work through the machine-learning, we can get this right.
52 Realcomm
