Hewlett-Packard (HP) offers many innovative products to meet diverse customer needs. The breadth of its product offering has helped the company achieve unparalleled market reach; however, it has come with significant costs and challenges. By offering multiple similar products, a manufacturer increases its overall demand volatility, reduces forecast accuracy, and can adversely affect revenue and costs across the entire product life cycle. At HP, these impacts included increases in inventory-driven costs and order-cycle time; liabilities to channel partners; and costs of operations, research and development, marketing, and administration. Furthermore, complexity in HP's product lines confused customers, sales representatives, and channel partners, sometimes driving business to competitors. HP developed two powerful operations research-based solutions for managing product variety. The first, a framework for screening new products, uses custom-built return-on-investment (ROI) calculators to evaluate each proposed new product before introduction; those that do not meet a threshold ROI level are targeted for exclusion from the proposed lineup. The second, HP's Revenue Coverage Optimization (RCO) tool, which is based on a fast, new maximum-flow algorithm, is used to manage product variety after introduction. By identifying a core portfolio of products that are important to order coverage, RCO enables HP businesses to increase operational focus on their most critical products. These tools have enabled HP to increase its profits across business units by more than $500 million since 2005. Moreover, HP has streamlined its product offerings, improved execution, achieved faster delivery, lowered overhead, and increased customer satisfaction and market share.

HP Labs' Business Optimization Lab is a group of researchers focused on developing innovations in business analytics that deliver value to HP. This chapter describes several activities of the Business Optimization Lab, including work in product portfolio management, prediction markets, modeling of rare events in marketing, and supply chain network design.