HP Labs has a long history of innovation in applied analytics driven by HP enterprise needs for strategic and operational decisions. More recently, HP is gearing towards providing business services to manage big data and information optimization solutions for our enterprise customers. This talk will highlight select successful applications of Operations Research and related analytical disciplines. One common theme of these applications is need for effective use of multiple analytical methodologies to address large scale industrial problems. Generally, these methodologies include: large scale optimization, advanced statistical modeling, data mining/machine learning, text mining/information extraction, marketing science, game theory/behavioral economics and others. Our HPLabs team is building methodologies and deploying tools for strategic and operational planning of workforce for our IT Services business, with about 200K highly skilled employees to meet HP’s enterprise customer demands in a dynamic and uncertain environment. This work addresses a difficult problem of optimal matching of complex demand & supply under uncertainty. Additional novel feature of this work is that we exploit unstructured information about demand and supply through advanced text mining and information extraction technologies and feed its result to large scale optimization for structured information processing. Another exciting work at HPLabs is in Live Analytics area, where we exploit information from sensors, real time events, and vast amount unstructured data and web contents to transform the way we manage our customers, resources, and environments. I will brief highlight the work in product portfolio optimization, which is the winner of INFORMS Edelman prize of 2009 and also our work in demand modeling & pricing optimization, for which HP was recognized by INFORMS Revenue Management and Pricing Practice Award of 2012.