Leveraging big data in automotive to solve key business problems
Dramatic shifts in the way customers view the driving experience are changing the way automakers interact with customers and require new approaches to maximize profitability and revenue. Big data presents a huge, new opportunity for automotive companies to meet the demands of their more demanding, educated customers - if they can harness it.
Big data is characterized by the tremendous volume, variety, velocity and veracity of data generated by a wide array of sources including vehicle sensor data, warranty claims and consumer sentiment data from multiple sources. To sustain growth, leaders across the automotive industry are prioritizing these key imperatives:
- Rapidly launch increasingly sustainable, connected vehicles
- Capitalize on services opportunities for intelligent connected vehicles
- Optimize the global value chain
IBM can help you achieve your business objectives by applying big data solutions to key business use cases. These include:
Data warehouse optimization
The automotive industry is projected to be the 2nd largest generator of data by 2015, stressing existing warehouse infrastructures well beyond their intended capacity. IBM's Data Warehouse Optimization solution is the only big data offering that addresses these needs by providing the industry with a common, integrated platform for all big data capabilities. The solution acts on a variety of structured, unstructured and streaming data to extend the warehouse infrastructure by optimizing storage, maintenance and licensing costs, reducing storage costs and improving warehouse performance.
Big data enables automakers to stage data before determining what data should be moved to the data warehouse, offload infrequently accessed or aged data from warehouse and application databases and analyze data in-motion to optimize the warehouse and enable new types of analyses. Benefits include:
Predictive asset optimization
Companies in the asset intensive automotive industry are continuously looking to reduce costs, meet quality targets, optimize equipment life, performance and availability. IBM's Predictive Asset Optimization solution captures and integrates vehicle in-motion and at-rest data for a single, integrated view of the vehicle enabling real-time insight into the performance of the various vehicle sub systems.
IBM's Predictive Asset Optimization solution leverages big data and analytics to maximize asset performance, predict asset failure and optimize quality and supply chain processes to drive enterprise-wide efficiencies and profitability. Benefits include:
Gaining access to vehicle information may not be new, but integrating it with information about a vehicle's operating environment at a given moment in time is revolutionary. Increasingly, automakers are connecting data from the vehicles, or the devices they integrate with, to the data about the environment in which the vehicle is operating (weather, traffic, hazardous situations, etc.). But this new data is being generated at incredible velocity and volumes.
IBM's big data and analytics platform, now known as IBM Watson Foundations, is able to capture and integrate data-in-motion and data-at-rest for a single, integrated view of the vehicle providing automakers with real-time insight into how the various vehicle systems are performing under specific driving patterns and environmental conditions. Benefits include:
Actionable Customer Insight
Automakers are increasingly prioritizing strategies which require significant improvements in customer acquisition, customer retention and return on marketing investment.
IBM's big data and analytics solutions provide a single, extensible repository for all multi-channel customer information enabling advanced analytics of all customer transactional data and external data sources (e.g. social media).
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