The 10 Most Trusted Public Sector Solution Providers 2018 [ Business Magazine ]

Expert's Outlook
Astrologers and science-fiction writers have entirely
lost their professional exclusivity with big data
coming into action enabling anyone to predict the
future backed by statistically analyzed complex data, that
too in a matter of seconds. The key to the future lies in the
past and the present has to connect the dots to make the
time travel journey successful. Astonishingly, this entire
process is reduced down to an operational duration of just a
few minutes with advanced predictive analytics tools.
Field Service, in particular, is a goldmine of data from GPS
and location to client details which had always been lying
dormant inside company servers but are now, gradually,
being channeled for greater purposes. Predictive analytics
has become so important in field service because customers
are, blatantly, expecting companies to understand their
needs and customize their offerings before them expressing
it. Companies can no more merely sell products and
services and have to shift their focus to selling experiences
to make a huge impact on the results.
These are the major impact points of predictive analytics in
the field service sector:
1. Demand
Forecasting demand for products and services can support
enterprises in better inventory management and help in
calculating the number of staff required to meet a certain
objective.
2. Pricing
Although enterprises are still slow in adopting modern
methods of pricing and still rely on the traditional ones,
times have changed with predictive analytics making the
pricing process much more accurate and flexible to various
internal and external factors.
3. KPIs
Superior performance strongly relies on actionable
information which is why predicting KPIs has become so
important for enterprises. The ability of predictive analytics
to measure, monitor and react to KPIs becomes imperative
in formulating both short-term and long-term strategies.
4. Operational efficiency
Task scheduling and route optimization becomes much
more efficient especially with a heavy reduction in
unnoticed slack using the multifunctional aspects of
predictive analytics.
5. Maintenance
Preventative maintenance becomes much more sensemaking
with predictive analytics supporting accurate
planning using historical data about when a part is likely to
fail.
Although there are abundant benefits of using Predictive
Analytics not just in field services but in any domain,
however, we cannot shy away from the risks that it brings
along with it. For Predictive Analytics to properly work,
there should be a huge volume of relevant data sets from a
wide range of activities and even with the availability of
such heavy data sets, algorithms can fail in anticipating
human behavior which in itself is full of complexities. If we
bring time into the frame, it makes things even more
completed. The analytics design might be successful at one
point of time but it might falter with changes in variables
with respect to time.
However, modern predictive analytics tools have managed
to rise beyond the risks and have hit a very high accuracy
mark in making analytical predictions. Especially in field
services, the algorithms have been modified to adapt to the
changes in location-based data and customer insights
considering time intervals as well. Such level of accuracy
becomes imperative in shaping how historical data is used
in making business level and functional strategies for the
organization.
Predictive Analytics platforms have started to become
extremely prominent since 2017 with modern technology
giving a push to business intelligence platforms supporting
predictive analytics. Enterprises in the field service industry
can look at platforms like Tookan and Kato to take a dive
into predictive analytics and transform how they carry out
their business.
Tookan is a robust one-stop shop for all the field service
management problems. Its analytical prowess gives you a
glimpse of the future. Tookan diagnoses and understands
the business with the help of its data mining and analytical
functions helping to make business intelligent decisions to
thrive in this volatile industry.
Kato is a fully equipped analytical platform which has a
wide range of analytical offerings from data preparation,
analytics dashboard to predictive insights. It acts as an AI
and predictive analytics tool by offering plug and play ML
algorithms that solve specific use cases for your business
model.
With predictive analytics supporting functional activities at
every step, enterprises can, literally, visualize a better future
and make business intelligent decisions based on historical
data defining patterns of activities and behavior.
MM 2018| December 2018| 23