Developing A Business and Technology Strategy to Help Determine the Best Way to Take Advantage of AI Today

Transcription

1 Developing A Business and Technology Strategy to Help Determine the Best Way to Take Advantage of AI Today Kallol Dutta, GM, Delivery & Automation, Spark New Zealand Niall Fitzgerald, GM, Architecture and Design, Spark New Zealand Gnanapriya Chidambaranathan, AVP, Infosys

2 As a digital servicescompany, Spark will be customer centric and data driven. The customer experience of our journeys will be our products of the future. Cross-functionalagile teams will be able to take action at pace, using real-time insights, making our business highly responsive andadaptive.

3 Our data fabric enables a data driven Spark Usingopen source solutions, we ve built the infrastructurefor delivering big data capability for Spark. thiswill enableour agile squadsand tribes to usereal-time/near-timedata and insights to see how our products and journeys areperformingfor customers. INGESTION & STORAGE ANALYSIS & CURATION INISIGHTS Systems Data Lake Visualisation 2018 TM Forum 3

4 Data is enabling the Automation and AI to provide competitive edge Automation will remove high volume and repeatable work freeing up our squads to focus on what really matters for customers Robotic process automation automates, repeatable tasks Machine learning uses data to identify patterns and teach itself Natural language processing allows A.I. to communicate and understand context Automation HUB - Identify, deliver and measure automation 2018 TM Forum 4

5 5 IDENTIFY PATTERNS OF BEHAVIOR for AUTOMATION of CHURN PREVENTION A set of parameters of churners and non churners was fed to machines with details of whether they churned Machine generated algorithms that learned from this data which was then used to predict churn on unknown data Port in, migration or new connections Trends of Data / Voice usage Data / Voice overages JOIN USE CHANGE Last used value pack Roaming packs CARE Calls that ended at Agents Online / Digital activity Act on the data Stickiness Index Targeted retention campaigns Retention initiatives 2018 TM Forum 5

6 Spark JUCCI Journeys set the framework From a customer s perspective, their Spark experience, is not a single interaction but a much more complex relationship. From Spark s perspective we simplify the relationship to create actionable tools and alignment conversations TM Forum 6

7 Journey Catalogue 2018 TM Forum 7

8 The Journey Catalogue allows us to understand our performance in a much more holistic way, across multiple dimensions Volume Success Exceptions NPS Performance Availability Profitability Investment Effort Cost to Serve Order/ % of journeys Stuck orders, Interaction and End-to-end Journey and Revenue, Capex Development Credits by transaction/ and sub- incomplete journey NPS journey and sub-journey ARPU, margin, investment in effort and journey, total interactions journeys journeys sub-journey availability/up- EBITDA, journeys, technical debt cost to serve, volumes completed end transaction time NOPAT return on modem/ to end times investment hardware cost Segment Product Offer Channel Access 2018 TM Forum 8

9 Demo Video Journey Catalog 2018 TM Forum 9

10 Our BOT SQUAD in Action FIBRE BOT Fibre BOT processes fibre orders for connections, plan changes and address moves. Processes that used to be highly manual, prone to data errors and created friction Tinker BOT A first edition artificial intelligence robot trained by our customer-facing engineers, proactively looking for customers experiencing poor broadband performance and diagnosing and resolving their issue Fibre BOT was awarded best robotic process automation bot for customer experience at the Intelligent Automation Awards in Sydney Some Key BOTS Security and Service operations: Verity Mario Mabel Field Services: Sapiens customer bill processing IT Operations: Johnny5 error handling 2018 TM Forum 10

11 Demo Video Fibre BOT 2018 TM Forum 11

12 Data driven, AI enabled Evolved B/OSS platform Improve Customer Experience & NPS Improve Network Utilization Prevent Incidents Evolved B/OSS Predictions Integrations Analytics Data Lake (Customer, Product, Offer, Resource, Service, Network, Tickets) Software Defined Operations (SDO) Enterprise Knowledge Intelligent Business Process Orchestrator (Closed Loop Automation) Machine Learning Supervised Un-Supervised Hybrid Regression, Classification, Clustering, Dimensionality reduction, Anomaly detection Rules Engine Customer Journey Views Channels & Customer Experience Network Customer Problem Management Customer Experience Management Service Problem Management Physical / Virtual Infrastructure Service Quality Management Customer Product / Offer Channels Bill Inventory Configuration, Orchestration Events, Incidents (Graph) Policies Test & Performance Faults, Alarms Trouble Tickets Diagnostics Multi Vendor Multi Version Multi Technology Multi Domain AI based Automated Operations, RPA Predictive Analytics, Insights 2018 TM Forum 12

13 Data driven, AI enabled Evolved B/OSS platform Journey Views Channels, Customer Experience AI based Automated Operations, RPA E2E view from channels to systems and networks Join, Use Care, Change, Involve journeys Products Business Process, deep dive Systems & Integration Fall outs Performance (Revenue, Cost, Business KPIs) Channel Preferences BOTS Personalization Contextualization Drives more Digital (Self Service, Guided Service) Analytics, Insights Predictive Analytics Insights (Customer, Product, Network, Service) Real Time View Network Planning & Engineering Network Assurance Field Services Fraud Management Revenue Assurance Service Delivery Security Supply Chain Management Marketing & Campaign Management, Personalized Offers Real Time New Age Services Contact Centers 2018 TM Forum 13