May Hicks Award

The OR Society funds its annual awards for student projects from a generous bequest from the estate of Mrs May Hicks, wife of Donald Hicks OBE, a major contributor to operational research and the first treasurer of The OR Society. Projects entered are OR projects carried out for a client organisation rather than within the university.

Citation for the May Hicks Awards 2021

The OR Society is delighted to announce the winners of the 2021 May Hicks prize for Best Post-graduate Project. The winner, Rachael Carpenter from Cardiff University, received £1000. The runners up were Alexander Heib (University of Southampton), and Joan Mo (University of Southampton), each of whom received £250 each.

Thanks go to the Universities who submitted their student projects. It was pleasing to read about such a range of practical problems and how well they are being addressed by OR techniques.


Rachael Carpenter (Cardiff University

Project ‘Cancer Breach –NHS Delivery Unit’

Rachael’s project created a process to identify and resolve common data quality issues, and analyse cancer breach reports (detailing patient pathways from cancer diagnosis to treatment where the pathway took longer than the target 62 days). She mainly focussed on word analysis of free text fields to allow common bottlenecks and delays to be identified. It is hoped that with continued use, this process will be able to determine where changes could be put in place to reduce waiting times, as well as whether any changes put in place to reduce waiting times are effective.


Rachael Carpenter May Hicks Award Winner 2021 with certifcate


Alexander Heib

Alexander Heib (University of Southampton)
Project ‘Modelling Technology Migration in Telecommunications using System Dynamics’–BT

Alex’s project supported technology migration. Migrating infrastructure away from legacy technology is a key strategic challenge for the company, and required a fuller understanding of the migration process needs to take into account network roll-out, marketing, engineering capability, customer migration as well as the competitive landscape in which the migration takes place.

Joan Mo

Joan Mo (University of Southampton)
Project ‘Data Fusion and Machine Learning Approaches for Lubricants’ - Zeller and Gmelin (Z&G)

Joan’s project created a data processing technique for sensor readings of chemicals in lubricants deployed in a drive train. This technique enabled the user to compare the expected load map with the load capability of the lubricant and to be alerted to a possible breakdown scenario before anything has happened.

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