This prize is awarded annually to the company that effectively integrates analytics into organizational decision-making, and has repeatedly applied ORMS principles in pioneering, novel and lasting ways. The 2018 prize winners, BNSF Railway will describe their innovative O.R. work in the INFORMS Prizes and Special Sessions Track. The 2019 winner will be recognized at the Edelman Gala on Monday evening.
Previous winners include Disney, U.S. Air Force, GM, Chevron, Memorial Sloan-Kettering Cancer Center, Sasol, Jeppesen, Intel, General Electric Global Research Center, Schneider National, Air Products and Chemicals, Procter & Gamble, UPS and other leading companies.
UPS George D. Smith Prize
The George D. Smith Prize is aimed at strengthening ties between academia and industry by rewarding institutions of higher education for effective and innovative preparation of students to be good practitioners of operations research. The Prize is generously underwritten by UPS. Awarded for the first time in 2012, past winners are Carnegie Mellon University, H. John Heinz III College, Sauder School of Business, University of British Columbia – Center for Operations Excellence, MIT Leaders for Global Operations, Naval Postgraduate School, and Tauber Institute for Global Operations at University of Michigan.
Competing for the 2019 Smith Prize are:
- University of Cincinnati Operations, Business Analytics and Information Systems Department
- University of Maryland Department of Decision, Operations & Information Technologies
- University of South Carolina Operations and Supply Chain Program,
Management Science Department
The teams will present their work to the judges on Sunday, April 14.
The Smith Prize winner will be announced at the Edelman Gala on Monday, April 15. The 2019 winner will give their presentation on Tuesday, April 16 in the INFORMS Prizes & Special Sessions Track.
Daniel H. Wagner Prize for Excellence in Operations Research
The Daniel H. Wagner competition is held each fall at the INFORMS Annual Meeting. The 2018 Wagner Prize Reprise will take place on Monday, April 15 in the INFORMS Prizes & Special Sessions Track.
The 2018 Wagner Winner is Cornell University for their work, “Analytics and Bikes: Riding Tandem with Motivate to Improve Mobility,” which provided unique application of analytics and O.R. to improve the placement of bike docking stations and create an inventive approach to replenish and rebalance these docking stations, was presented by Daniel Freund, Shane G. Henderson, and David B. Shmoys and Eoin O’Mahony.
This prize emphasizes the quality and coherence of the analysis used in practice. Dr. Wagner strove for strong mathematics applied to practical problems, supported by clear and intelligible writing. The Wagner Prize recognizes those principles by emphasizing good writing, strong analytical content and verifiable practice successes. The competition is held and the winner is announced at the INFORMS Annual Meeting in the fall.
Past awardees include practitioners and researchers from Lehigh University and the Pennsylvania Department of Corrections, The Forestry Research Institute of Sweden, CDC, Ford, U.S. Coast Guard, Intel, IBM T. J. Watson Research, Schneider National, Boston University, University of Florida, and others.
Innovative Applications in Analytics Award
Sponsored by Caterpillar and the INFORMS Analytics Society
The IAAA Finalists will present on Tuesday, April 16 in the INFORMS Prizes & Special Sessions Track. The winner will be announced at the conference.
The teams competing for the 2019 IAAA are:
- jet.com/Walmart Labs for “A Machine Learning Approach to Shipping Box Design”
- Singapore University of Technology and Design for “InnoGPS: Innovation Global Positioning System”
- Center for Operations Research in Medicine and HealthCare for “Machine Learning: Multi-site Evidence-based Best Practice Discovery”
- Washington University in Saint Louis for “Taking Assortment Optimization from Theory to Practice: Evidence from Large Field Experiments on Alibaba”
- University of Wisconsin, Duke University, Harvard University, and Massachusetts General Hospital, Westover for “Transparent Machine Learning Models for Predicting Seizures in ICU Patients from cEEG Signals”
- Verizon for “Using Advanced Analytics to Rationalize Tail Spend Suppliers at Verizon”
The purpose this award is to recognize the creative and unique application of a combination of analytical techniques in a new area. The prize promotes the awareness and value of the creative combination of analytics techniques in unusual applications to provide insights and business value. The Analytics Section leadership would like to cordially thank all the members of the judging committee for their hard work in selecting these finalists.
INFORMS O.R. & Analytics Student Team Competition
Finalist Competition – Conference attendees invited!
The finalists will present on Monday, April 15. The winners will be announced on Tuesday, April 16 during the conference.
INFORMS introduced the O.R. & Analytics Team Competition in 2017 to highlight young talent and provide O.R. and analytics students the opportunity to solve the kinds of real-world workplace challenges they will face during their careers.
Student teams are given the same business problem, data sets, and access to software to solve a challenging problem using an OR/analytics approach. A panel of industry and academic experts judge written submissions based on teams’ use of the full analytics process, from framing the problem to methodology selection, data use, model building and innovation. Teams selected as finalists present their solutions to a judging panel at the INFORMS Business Analytics Conference in April, with the winners announced at the conference.
Syngenta Crop Challenge in Analytics
Today, the agriculture industry works to optimize the amount of food we gain from plants by breeding plants with the strongest, highest-yielding genetics. Scientists at R&D organizations like Syngenta create stronger plants by breeding and then selecting the best offspring over time to provide to farmers. Data-driven strategies can help our industry breed better seeds, faster. Developing models that identify robust patterns in our experimental data may help scientists more accurately choose seeds that increase the productivity of the crops we plant – and help address the growing global food demand.
How can we use data to address the growing global food demand?
The finalists will present on Monday, April 15. The winner will be announced on Tuesday, April 16 during the conference.