Smart Industry 2/2018

utility provider may be able to forecast
demand more precisely, while
logistics companies can reduce waste
or loss. However, if this data is used
solely for getting more detail on one
facet of operations, then other opportunities
to be innovative are missed.
Getting the right approach to analytics
in place can help by using the data
to generate in-depth insight for operations.
In practice, this means linking
IoT data up with other sets of information.
These may be external sets like
weather or consumer behavior.
However, this creates its own set of
problems that cross over from the
technology side into areas like business
process and people skills. For
example, how can the company bring
the sets of data together in real time,
so that they can be used effectively?
What sets of data does the company
have, and what can be brought in
from outside? And what questions
can be answered using that data combination?
Answering these questions requires
more thought on how the business
functions and what its goals are. Looking
at device data on its own won’t be
enough to show all possible applications,
so exploring how to use other
internal and external data sets will
probably be necessary.
For example, many businesses are
looking at how to improve customer
service and loyalty, but the link between
better customer experience
and IoT data may not be immediately
obvious for, say, utility companies.
Getting more insight into the status
of smart devices over time can help
highlight possible problems with assets.
In the utility sector, boilers or
heating systems can be tracked and
companies can proactively recommend
service in advance of possible
equipment failure. Providers like First
Utility in the UK use data analysis to
see energy reduction opportunities
for customers, helping them cut their
bills.
Combining these different approaches
to analytics should add up
to a wider improvement in customer
experience. Stopping device failures
and helping customers reduce their
spending should increase long-term
loyalty and keep customers happier
over time, which should then result
The right mix
A combination of
different approaches
to analytics can lead
to improvement in
customer experience.
Outside views
Insights must be
drawn from both
internal and external
data sets in order to
provide true value.
photo ©: DataStax
in higher average revenues per customer
for companies.
In the logistics sector, increased accuracy
can help with customer service
through more in-depth tracking.
Rather than simply providing generic
information, information from sensors
can provide real-time insight into
where each delivery is. For customers,
this level of insight should be a valuable
extra, while the logistics company
should see how its overall network
is performing.
Making it all work
Getting data and using it effectively
does mean thinking about new applications
and how those services
are delivered. Gradually, it may mean
building on existing IoT data alongside
other sets of information. Scaling
up from initial IoT projects, therefore,
requires an integrated approach to
data, processes, and implementation
where further applications or different
use cases for the same operational
data can be added over time.
Whichever approach your company
has around new ideas and innovation,
it’s worth looking at how to
devote more time and resources to
supporting internal research and
development. Using data from IoT
devices, companies can power new
and interesting services for their
customers. However, getting the approach
to innovation balanced across
the business requires a combination
of the right people, the right data,
and the right platforms to pull it all
together.
photo ©: DataStax
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