A Tier 1 mobile service provider used an IBM big data solution to ingest large device manuals from multiple vendors and create digestible chunks of information (sub-documents) on a topic that the call center representatives can use to resolve customer issues. Over 40,000 call center agents access this targeted information from the central knowledge management application, combined with information from other sources. This helps resolve customer issues faster and more reliably, resulting in lower average handling time (AHT) and improved customer satisfaction. Service provider also saved hundreds of thousands of dollars spent in manually segmenting and processing information.
Several years ago, NYSE Euronext had used traditional database technology to drive analytics. But with steadily growing data volumes, data analysts found it increasingly difficult to process the data—especially when searching for questionable trading activity. Then they discovered IBM PureData System for Analytics.
Battelle is spearheading a bold experiment in electric power conservation in the U.S. Pacific Northwest that will help reduce the region’s carbon footprint, smooth out peaks in electricity use, and better integrate intermittent renewable resources—like solar and wind power— to help keep future costs from rising as quickly as they otherwise would. The project provides unprecedented insight into the cost of electricity at any point in time, relaying information about varying demand levels to support informed consumption decisions.
To maximize its ability to meet members’ healthcare needs, Blue Cross Blue Shield of Massachusetts (BCBSMA) is a careful steward of the premium dollar. Nearly 90 percent of every premium dollar received is used to pay the medical expenses of its members – which means that operational costs must be kept to 10 percent or less. Achieving this target requires a detailed understanding of cost and risk in all areas of the business, creating a significant demand for business analytics. BCBSMA has combined IBM Cognos Business Intelligence with an IBM Netezza data warehouse appliance to provide lightning-fast analysis of medical and financial data. The solution is used to create sophisticated reports on clinical and financial risk, operational efficiency, and helps to identify opportunities for strategic and competitive advantage.
A financial software company sought to analyze customer engagements to improve product quality and increase retention. It also wanted to increase marketing return on investment and targeting precision using behavioral variables. The company deployed an IBM Netezza data warehouse appliance, which enables it to perform next-generation analytics in order to consistently and ontinuously improve its service. As a result, the company has achieved higher customer satisfaction scores; projected USD10 million revenue lift within 12 months; and improved its ability to detect and correct cross-channel cannibalization.
Macys.com sought to create a more personalized shopping experience as the brand transitioned from regional to national. In order to accomplish this, the company worked with IBM to establish a foundation for a more dynamic, data-driven and integrated website.
University of Ontario Institute of Technology needed a better system to leverage key data to provide proactive patient care in their research institution, SickKids. In order to do so, the institute developed a first-of-its-kind, stream-computing platform to capture and analyze real-time data from medical monitors, alerting hospital staff to potential health problems before patients manifest clinical signs of infection or other issues.
The Marine Institute Ireland, seeking to gain more value from its existing SmartBay environmental monitoring project, worked with IBM to develop a pilot information system to feed environmental data into a data warehouse where it is processed, analyzed and displayed in new ways. This provides a broad range of benefits, from safer navigation to flood warnings and much more.
Researchers at KTH gather real-time traffic data from a variety of sources such as GPS from large numbers of vehicles, radar sensors on motorways, congestion charging, weather, etc. Collected data is now flowing into IBM InfoSphere Streams software—a unique software tool that analyzes large volumes of streaming, real-time data, both structured and unstructured. Analyzing large volumes of streaming data in real time is leading to smarter, more efficient and environmentally friendly traffic in urban areas.
Working with IBM and IBM Premier Business Partner IT Consultings, Automercados integrated data across its 15 stores and corporate systems to enable the sharing of trusted information and gain greater insight into operations.