Airlines have been early adopters of cutting-edge revenue-management (RM) technologies since the 1970s. They were among the first companies to use dynamic inventory pricing, and some of the forecasting and inventory-management models they introduced in the 1980s and 1990s - including sequential upgrades to forecasting and optimization engines and the expanded use of fare restrictions, or fences - represented the vanguard of advanced analytics at the time. These and other RM tactics successfully clustered customers according to their key attributes; for example, they distinguished the occasional leisure vacationers from the weekly business travelers. This clustering generated significant additional revenue and contributed significantly to the growth and success of the airline industry. To date, airlines have focused mostly on how to price core tickets. However, this approach ignores a recent, fundamental industry change: an increasing percentage of revenue now comes from ancillary items such as checked baggage, onboard food, premium seat selection, and extra legroom. Given the growing importance of ancillary sales, airlines cannot continue simply to tweak their existing RM strategies and models expecting to optimize total revenue. Instead, airlines must optimize total revenue by taking attribute-level customization a step further. They have an opportunity to adopt bundling tactics, product-suggestion analytics, and dynamic pricing to create customized recommendations for additional purchases, both at the original point of sale and over the course of the travel journey. These tactics are already employed by other industries (notably online retail), and with the increasing power of advanced analytics, airlines can profile customers in ways not possible just a few years ago. To move toward the next frontier of optimized total RM, airline industry leaders must overcome significant complicating organizational factors. For instance, RM departments at most airlines are siloed from other departments, such as sales and marketing, which hinders their ability to collect and wield the customer data needed to optimize total revenue. In addition, few airlines employ data scientists, which prevents them from harnessing the latest advanced analytics tools to create cutting-edge predictive and prescriptive revenue-optimization models. If airlines work to address these shortcomings, we estimate they could reap a 5 to 10 percent improvement in total revenue. To achieve this goal, however, airlines must act soon, and they must develop these capabilities in-house. If they wait along with all the other airlines for RM systems providers to innovate on their behalf, they will lose their chance at a competitive edge. In an era when optimization of distinct processes and departments has met its ceiling, this opportunity is too big to pass up. Get the full story at McKinsey & Company