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Juan Manuel Caro is Director of Operations in Telefónica S.A. He holds a Bachelor's Degree in Telecommunications Engineering from the Polytechnic University of Madrid and a Master's Degree in Business Administration from EOI Business School. He joined Telefónica Spain in 2001, holding different positions and leading transformation programs for Network, Operations and IT. In 2009 he was appointed to an Executive position within the CTO organisation of Telefónica Brazil, holding different roles such as network economic controller or transformation leader. In 2011 he was appointed to his current position within Telefónica HQ, and he is currently reporting to the Global CTIO. His role includes corporate leadership in areas such as Customer, Service, Network, IT and Global platforms operations (technical call centres, field force, service operation centres, customer experience assurance, network operation centres, technical support, datacentres, infrastructure, rentals, power, video, M2M and others) and Network and IT deployments.
Telefonica Keynote Presentation: Real-Time Customer-Centric Operations
In today's complex environments, operations teams must change their mindset and ways of working from a traditional, reactive, network-centric way of solving problems to a proactive/predictive, customer-centric approach of continuous improvement. Understanding our customers, how they use our services, what experiences they are having and what we can do from operations to improve their overall experience is key to succeeding in today's market -- and will be even more important in the virtualized architecture of the near future!
PANEL: ZERO TOUCH ANALYTICS – DELIVERING INSIGHTS IN REAL TIME
Network operators can easily fill huge data lakes with streaming telemetry about network paths, traffic flows and performance. There are several open source tools that can be used, including Kafka, Elastic Stack, Grafana and Pnda. The hard part is unlocking the value of all this data to deliver value such as faster root cause analysis, reduced mean time to repair or detection of security threats. To achieve this might require advanced machine learning algorithms that can do predictive or prescriptive analytics. Alternatively, it might suffice to use traditional statistical analysis and correlations. This panel examines the varying approaches to data processing as there is no "one-size fits all" approach to analytics.
