I read three thought-provoking articles this week. Firstly, an
interview with Cisco’s Padmasree Warrior, published by McKinsey Insights .
In the interview, Padmasree Warrior argues that despite 20 years of digital
revolution we have only reached around 1% of what could be connected in the
world. Over the next 10 years Cisco expect that figure to rise significantly as
more and more people, devices and sensors connect.
Secondly, I read Wim Rampen’s latest post “Don’t
take the customer decision journey for granted”. As ever, Wim cuts through
the hype of terms like “big data” and “customer engagement” and grounds our
thinking in a service dominant logic mindset. He argues than rather than
throwing more technology at Big Data and assuming that predictive analytics
will fix every problem, in fact a greater abundance of data should present us
with a greater ability to understand the jobs that customers are trying to do
and give us better insight to the barriers they face. In turn this should
inform investments that are made to give customers the right information, tools
and transparency at each step of their decision journey.
Thirdly, I read today that IBM plan to redeploy Watson for
Customer Service (see “Putting
Watson to Work” ) by launching the Watson Engagement Advisor that key clients
like ANZ Bank, Royal Bank of Canada and Malaysia Telecom will be piloting. This
announcement follows hot on the heels of the announcement that Watson
would be opened up as a service to developers to build applications around.
Bringing these three streams of thought together could be
powerful for customer service. The exponential rise in the number of connected
devices over the new few years brings an opportunity to infuse real time data from
up and down the value chain into business processes to help customer service make
smarter decisions. For example, sensing that parts in the supply chain are
delayed, traffic conditions are bad, break pads seem to be showing greater wear
than usual after 10,000km... can all help inform decision making, whether that
be at a macro level (e.g. issuing a product recall) or at a micro level (pro-actively
informing a customer of a delay or simply having all the right information to
hand to understand what’s causing the customer’s issue).
The evolution of Watson from Jeopardy winning super-computer
to an open, service-based platform could allow customer service organisations
to put that smarter decision making into the hands of the customers via
whatever device or app they want to use. What I like about the potential for
Watson in customer service is that it will start by understanding the job the
customer is trying to do (“How can Watson help you today?...”). This has always
been the promise of voice self service systems, chat-bots and self service
knowledge bases, but none have ever quite had the computing power of Watson to
make sense of complex queries and compute vast amounts of structured and
unstructured data to find the right answer.
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