While I am often amazed at the functionality provided by my
smartphone, I’m also surprised at how dumb the device can be. Every night I
turn my work phone to “do not disturb,” yet despite its vaunted usability, my
iPhone isn’t smart enough to perform this fairly simple task automatically.
Even new “intelligent” apps like Google Now lack fairly basic intelligence.
Google Now is supposed to proactively alert you to delays in your usual
commute, but wasn’t smart enough to realize I was on vacation recently and did
not need a commute time from the Cayman Islands to a restaurant that Google somehow
had concluded was my workplace.

Intelligence versus

Our smartphones have all the tools to act in a more
intelligent manner. They know our location, intimate details about our lives
ranging from who we communicate with to how active we are, and what our
schedule looks like months in advance.

Contextual knowledge, intelligence about what activity we’re
performing and where we’re performing it, has long been cited as the next
innovation in smartphones. Our devices already have all the information to do
seemingly intelligent things like pull up the PowerPoint for the meeting that
we’re heading to, or informing our spouse that we’ll be home a few minutes
later from work due to an accident or a long-running meeting.

Despite having this information available, one of the main
obstacles to more intelligent smartphones is that our data is often segregated
among multiple applications and the underlying operating system, each of which
jealously guards its knowledge about us. Furthermore, most of these
applications have been created by companies that are likely more concerned with
leveraging our data to sell to other companies than providing a superior user

The enterprise
“customer” advantage

One of the main challenges to smarter mobile devices is
determining who the customer of many mobile applications actually is. The preponderance
of “free” consumer applications often harvest data about their users, selling
those data to the “true” customers: advertisers and other companies that pay
dearly for these data.

Enterprises generally don’t have these concerns and, in an
interesting twist to the trend toward consumer-driven innovation, can actually
deliver contextual intelligence to end users rather than selling it to marketers.
For example, a warehouse application might act differently when a mobile device
is out on the shop floor versus when it’s in the office and might be used for
reporting rather than data gathering. A smartphone might sense a worker’s
movements in a high-risk environment and, rather than “phoning home” to sell
marketing data, might report movements that indicate the worker has fallen or
passed out and needs help.

Furthermore, rather than being focused on gathering
individual data, enterprises are likely to find aggregate data more helpful. In
which buildings or sections of a plant are employees spending most of their
time? Which routes do workers take to service a piece of equipment that’s out
in the field? How long is it taking to service the average sales call?
Gathering aggregate data can be likened to key performance metrics, and the
effect of initiatives meant to improve those metrics can be quickly and accurately

Avoiding “creep”

As with advertisers, it’s tempting to gather all manner of
information from employee devices and have those devices track, scold, and
monitor employees around the clock in what amounts to a creepy effort at best,
and an unethical or illegal manner at worst. While courts have historically
sided with employers on questions of monitoring use of employer-provided
technology, these lines have grown blurry with increasingly personal data
available from smart, mobile devices. Rather than immediately running to the
lawyers to see what you can get away with, assemble a working group of
employees who might be impacted by “smarter” devices and gauge their reactions
to your plans.

While commercial interests have driven much of the location-
and contextually-aware functionality of today’s mobile devices, enterprises
might just be in a unique position to commercially exploit the functionality
without exploiting the user generating the data.