As a top U.S.-based insurer of property, casualty and surety, Westfield realized progress depended on gaining a better understanding of their business. With The Analytics Resource Center (ARC), data is now more accessible, encouraging decisions based on hard evidence rather than intuition.
The Vassan Group struggled to accurately forecast fluctuating sales orders across the Nordic region. As a result, they couldn't effectively plan their resource and production schedule. With IBM Big Data & Analytics, Vaasan gained the ability to predict production requirements and prepare for fluctuating orders ultimately fulfilling 30 percent more orders.
Mueller needed a customer-focused approach to sales and more data transparency so information could easily be shared throughout the company. With IBM Big Data & Analytics solutions, Mueller empowered all employees to view and analyze company data in near real time, measure individual performances and assess how their work affects the bottom line.
With increasing numbers of people turning to social media to reach out to insurance companies, Security First sought a way to better manage its interactions over Facebook, Twitter, LinkedIn and email policyholders in the wake of a catastrophic event.
Luxottica Retail North America is the world's largest designer, manufacturer, distributor and seller of luxury and sports eyewear. To make better use of the data on its 100 million customers, and increase marketing effectiveness, Luxottica turned to IBM.
Seattle Children's Hospital, one of the leading children's hospitals in the U.S., needed a solution to manage and extract valuable insights from vast amounts of complex data.
This 2013 IBM Institute for Business Value study surveyed 900 businesses and IT executives from 70 countries, asking more than 50 questions. The questions were designed to reveal how to translate high-level concepts associated with delivering exceptional business value through analytics into actions that can truly deliver value.
Leveraging predictive analytics, First Tennessee Bank is combining a granular understanding of the needs of customer segments with real P&L data to optimize its marketing spend, focusing on programs that deliver the highest ROI.
The world of big data is expanding quickly and adding value requires establishing speed and confidence in every decision, interaction and process.
This use case looks at how savvy retailers can use "big data" - combining data from web browsing patterns, social media, industry forecasts, existing customer records, etc.