Premier Analytics and O.R. Competition Showcases Significant Economic and Societal Impacts around the Globe
INFORMS, the leading international association for professionals in operations research and analytics, has selected six finalists for the 49th annual Franz Edelman Award for Achievement in Advanced Analytics, Operations Research and Management Science, the world’s most prestigious award for achievement in the practice of analytics and operations research (O.R.).
For more than four decades, winners of the Edelman Award have been recognized for transforming how we approach some of the world’s most complex problems. This year’s finalists are no exception, with revolutionary contributions in robotics, cruise industry pricing and booking, railway planning and productivity, IT system sustainability, corporate decision-making, and retail inventory operations. Finalists for the Edelman Award have contributed to a cumulative impact of more than $257 billion since the award’s inception.
The finalists for the 2020 Edelman Award are:
Amazon.com. Amazon fulfillment centers are the bones of the company’s global operations network. Order picking plays a significant role in the overall process and accounts for a large part of the building’s ability to drive faster cycle times and higher throughput. Amazon’s revolutionary robotics system has reduced costs by identifying ways in which Amazon can process the picking of items faster and more efficiently across multiple floors and pick stations. The technology overall has led to significant performance improvement through stowing and picking inventory to facilitate sortation of multi-item shipments, reducing robotic systems travel by 31%. This has resulted in millions in savings per Amazon Robotics fulfillment center.
Carnival Corporation & PLC. Carnival & PLC built Yield Optimization and Demand Analytics (YODA), a cutting-edge program using advanced analytics and algorithms to provide dynamic price recommendations and inventory management. The program is a global collaboration involving leaders from six brands and teams across three continents who manage prices in six currencies. Since the system deployed in late 2017, it has been used to set prices on thousands of cruise voyages. The system was built in collaboration with Revenue Analytics.
Deutsche Bahn. The largest European railway company is moving more efficiently thanks in part to a new decision support system. The system optimizes train rotations in cargo, regional and long-distance passenger transport divisions. The changes have resulted in direct savings in addition to better planning and productivity. The productivity of the locomotives and railcars has increased up to 10% while the time savings were up to 80%.
IBM. IBM Services (Global Technology Services Unit) has developed a cutting-edge system that utilizes machine learning and advanced data analytics to identify devices, such as servers, that are at risk for an outage. The system determines contributing risk factors, e.g., outdated hardware, and prompts a fix before the problem occurs. Since 2013, executing recommended actions has reduced outages by 23%. This translates into savings of more than $1 billion every year for IBM’s clients. The IBM team is also using this system to drastically reduce the number of problematic systems for clients by as much as 85%.
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Intel. Efficient product feature design coupled with supply chain planning is critical to Intel’s success given its scale, complexity of its products and manufacturing processes, and the highly capital-intensive nature of the semiconductor business. In response to an exponential increase in complexities, Intel developed an innovative set of capabilities using advanced analytics that span product feature design through supply chain planning with the goal of maximizing revenue while minimizing cost. This set of capabilities is fast and effective, enabling analysis of many more business scenarios in much less time than previous solutions while providing superior results including faster response to customers. Implementation of this capability over the majority of Intel’s product portfolio has provided average annual benefits in increased revenue and decreased cost of $1.9 billion and $1.5 billion, respectively, with a total benefit of $21.2 billion to date while also contributing to Intel’s environmental goals of reducing water usage and preventing wastewater.
Walmart. Walmart’s model of offering consistently low prices depends on constantly innovating to find new ways to reduce costs. The company developed a new system using machine learning to help perfectly time markdowns to optimize sales and clear excess inventory in its stores. The technique relies on operations research and provides feedback to help avoid excess inventory ordering in the future. The technology has already helped the company save millions of dollars.