Published on November 1, 2016
1. Automotive data aggregation and analytics platform: enabling new business models for vehicle OEM's and service providers Yaroslav Domaratsky, PhD https://www.linkedin.com/in/yaroslav-domaratsky firstname.lastname@example.org
2. Product concept Target market Target customers and customer needs Product idea Opportunities • Could leverage team experience to minimize product development cost • End customer will minimize investment to IT infrastructure • Could cooperate with local OEMs and service providers to verify the product with real vehicle data. Threats • Vehicle OEMs and service providers do not believe in new business models enabled by prescriptive data analytics and continuous insight • Delays in ADV and (or) Internet of Cars market adoption. Customers Common customer needs Customer specific needs Vehicle OEM Need secure and highly available data aggregation and analytics platform. Want to minimize investment to the platform development and operation. May benefit from new business models enabled by prescriptive data analytics and continuous insight. Own vehicle data. Want to control end user services ecosystem. Automotive insurance service provider Own customer data. Own data analytics algorithms. 1st phase: Develop the platform for vehicle OEMs. Show leadership in the prescriptive vehicle data analytics. Launch the service 2nd phase: Develop IP and data analytics algorithms for the new business models based on ADV and car sharing. Sell the service to the service providers. Monetization strategy Annual WW sales of CVs will exceed 45M in 2020. We target the below customers: • Vehicle OEM’s who not yet launched CV services massively • Automotive insurance service providers who deploy new business models based on ADV and car sharing. CV = Connected Vehicle WW = World Wide OSS = Open Source Software ADV = Autonomous Driving Vehicle IP = Intellectual Property OEM = Original Equipment Manufacturer Provide the following features based on OSS data platform: • Enable new business models through prescriptive data analytics and continuous insight • Real time and batch analytics for vehicle data, full data encryption • Unlimited horizontal scalability, high availability and fault tolerance • The product validated with real vehicle data.
3. Technical details OSS based data platform (*) Available software assets The team already integrated core OSS components and prototyped day 1 services. * - additional information could be provided upon request VAS = Value Added Service VM = Virtual Machine VM layered view Benefits for the customer • Flexible deployment options including on-prem, private and public cloud • High availablity, high performance and fault tolerance • Highest security level, full data encryption • There are no license fees for base SW components • Core data analytics algorithms and services validated with real vehicle data • State of the art continious insight concept supported. Lambda architecture supported Data analytics maturity levels Ourgoal:decision automationwith continuousinsight Competitive differentiation • New business models and unique service differentiation features enabled by prescriptive analytics and continuous insight (see next slide) • New business models enabled by ADV, IoT and Internet of Cars concepts • Customers could use core data analytics algorithms validated with real vehicle data.
4. New features enabled by continuous insight Continuous insight concept Continuous insight through advanced situation detection (*) Decision automation and continuous insight 1. Intelligently aggregate and analyze information relevant to particular vehicle (user) context / situation including the data collected from • Vehicle OEM pre installed and aftermarket devices • Road infrastructure elements, other ITS and smart city devices • Driver and vehicle occupants personal devices • Other devices related to vehicle (user) context / situation. 2. Analyze the current vehicle (user) situation, predict the situation progression, formulate decisions and to trigger actions to: • Minimize risks for • Driver and vehicle occupants • Other vehicles and pedestrians • Vehicle OEM and insurance company • Maximize ROI for • Driver (vehicle owner) • Vehicle OEM and insurance company 3. Constantly adjust system operation to • Improve customer relationships • Avoid negative situations and encourage positive ones to occur. * - IBM SG24-8293-00: Systems of Insight for Digital Transformation With the product you could The solution enables new business models for vehicle OEMs and service providers Specific use cases could be prototyped based on customer needs