Operational Research, known as ‘the art and science of decision-making’, is a hidden gem that is a transformative tool for businesses. It combines advanced mathematics, data analytics and human insights to provide a comprehensive toolkit for businesses. This discipline goes beyond simple data analytics, turning data insights into real-world solutions for complex problems. Seb Hargreaves, Executive Director of The OR Society, discusses how Operational Research can help businesses.
Operational Research (OR) specialists work closely with businesses to understand their unique challenges and goals. They create mathematical models, algorithms and customised tools to address specific problems.
For example, an OR expert might help a logistics company to optimise its delivery routes by considering factors such as traffic, fuel expenses and delivery deadlines. Similarly, a retailer might use OR to analyse sales data and determine optimal stock levels, balancing customer demand with inventory costs through predictive analysis.
Members of The OR Society have also worked with e-commerce giant, Amazon, to achieve more efficient scheduling of delivery routes and, the most recent availability of vast amounts of data has further enhanced OR’s capability to aid complex decision-making.
Looking back at the roots
OR evolved in World War II, when scientists and engineers developed innovative methods to enhance military operations. By analysing military data, mapping processes, simulating scenarios and devising optimal routes and logistics strategies for merchant ships, OR played a crucial role in reducing military losses and ensuring mission success.
Today, executives across organisations large and small, private and public, are using OR to unlock value from their data, model complex systems and make better decisions with reduced risk.
Tackling complex business problems in retail and manufacturing
One notable example is glass company, Pilkington UK, part of the NSG Group, which used OR techniques to reduce glass waste and optimise its manufacturing processes.
By analysing its order data using OR techniques, Pilkington UK was able to better plan manufacturing processes to align with specific customer orders. This led to varied sizes of glass being cut to match orders – optimisation that reduced waste, saved costs and improved customer satisfaction.
Tesco, Britain’s largest grocer, also turned to OR solutions to manage its expiring stock more effectively. The final stage in the value chain – selling or donating items near their expiration – poses a significant challenge for all retailers.
Tesco’s data science team used OR methods to develop a multi-stage clearance-pricing optimisation system applied to thousands of products across all Tesco stores. This system helped the retailer cut food waste by 5% while boosting revenue by up to 13%.
Case study: streamlining cancer diagnosis and treatment in Wales
OR has proven to be a game-changer for healthcare organisations too. In Wales, OR interventions have led to significant improvements in cancer survival rates. Wales faced a significant challenge with cancer survival rates lagging other developed nations.
A key issue was the existing of different diagnosis and treatment pathways for cancer in Wales, leading to patient treatment bottlenecks and delays, sometimes proving fatal.
Patients with obvious cancer symptoms seen by their GP were placed on an ‘urgent’ pathway, starting treatment within 62 days. However, patients with ambiguous symptoms entered a ‘non-urgent’ pathway, with a treatment deadline set only after cancer confirmation through diagnostic tests.
The Wales Cancer Network approached a team of OR specialists to address the issue. They embarked on a project to implement a Single Cancer Pathway (SCP) in Wales.
One key recommendation was the need to reduce the different pathways and determine the necessary resources to meet SCP waiting time targets. The OR team analysed over 6,000 cancer referrals across 10 cancer types and 30 diagnostic test categories. They identified the need for a 20% increase in diagnostic resources and the establishment of ‘rapid diagnostic hubs’ to achieve the project’s goals.
The research findings were presented to the Welsh Government Minister for Health and Social Services, who subsequently released £3 million in funding to support the transition to the SCP. As a result, Wales became the first UK nation to introduce a single waiting time target for cancer patients. The SCP changed the diagnosis and treatment pathway for approximately 60% of cancer patients who would have previously been on the ‘non-urgent’ pathway.
Netherlands’ transition to electric buses by 2030
When RET, Rotterdam’s public transport operator, wanted to switch to electric buses there were several challenges to address. These included the limited electric bus range and long charging times that would affect the regular service and any potential delays could leave buses stranded with insufficient charge.
RET turned to the Rotterdam School of Management, Erasmus University (RSM) to use OR to find a solution. RSM developed a simulation model to assess the impact of electrification on RET’s scheduling considering factors including battery capacity, energy consumption patterns and the capacity of the charging infrastructure.
The simulation revealed existing schedules couldn’t accommodate electric buses without major planning adjustments.
RET adapted its planning, and the simulation model was used to optimise the charging strategy, accounting for bus delays. The model revealed a real-time charging approach to reduce charging moments and maintain the bus service reliability.
With the initial deployment of 50 electric buses in December 2019, attention shifted to introducing electric buses in the south side of Rotterdam. Clustering charging activities at common terminal stations presented opportunities for local renewable energy generation. The RSM team then did a feasibility study of having a solar park at the bus station, which would allow for energy generation uncertainties. Results showed that up to 70% of energy for charging could come directly from solar panels during the summer, with the potential for a 7% increase in renewable energy use through energy storage.
The key learnings were that:
The electrification of the bus network required significant operational changes and real-time adjustments were essential to handle delays and ensure buses had adequate charge. They also learned that hub-based charging networks were ideal for local renewable energy usage.
The collaboration between RSM and RET and the use of OR has enabled a smooth transition to electrics buses. The model was integrated into RET’s day-to-day planning software, contributing to the successful electrification of Rotterdam’s bus fleet.
A growing field with huge potential
OR offers solutions to complex problems, cost savings and improved decision-making.
It is a transformative tool that leverages data, mathematics and human insights to solve complex business problems. Its applications span industries, from healthcare to transportation, and its potential continues to grow with advancements in technology.