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.
