Manchester Metropolitan University

Case StudyService Power

State of the art software helps industry improve vehicle logistics by up to 10%

A Knowledge Transfer Partnership at Manchester Metropolitan University helped develop a state-of-the-art software algorithm, underpinned by quantum physics, to help deliver lorries’ goods faster and at lower cost.

The Challenge

ServicePower is a company that provides field service software for companies that manage the installation, service or repair of systems and equipment. Industries and organisations can use this software to ensure that projects run on time and to budget.

The company sought a way to calculate the best routes and times to send vehicles on the road in the most efficient way. For example, by minimising the number of miles travelled by lorries when delivering goods to multiple locations.

Previously it used a computing system known as simulated annealing. Yet this solution was not powerful enough to manage vehicles on the scale the company required.


Through previously established connections with Dr Alan Crispin at Manchester Metropolitan, ServicePowerbecame aware of PhD student Alex Syrichas, who was completing research on quantum annealing.

Inspired by the laws of quantum physics, quantum annealing is a software algorithm that uses enhanced search techniques to solve problems that are difficult to manage on an industrial scale. ServicePower recruited Alex through a Knowledge Transfer Partnership to develop the software into a commercial product.

One of the major problems the team had to overcome in making the product commercially viable was the great demands quantum annealing makes on computer memory and processing power. These demands make it difficult for the software to run on desktop computers commonly used in industry. Also, quantum computer hardware is very expensive, and is only used by a very small number of large organisations. Alex managed to overcome these problems by developing the product so that the software can work on the kinds of computers commonly used in business.  

The team also helped with scaling requirements. The algorithm was integrated into a piece of software called optimisation on demand (OOD). This allows services to book jobs for customers, set appointments, and order these so that they work in the fastest and most cost-effective way. However, OOD is aimed at organisations with a customer base of around 600, and ServicePower required the software to work for a customer-base at least ten-times that figure. The team were successfully able to adapt the software so that it could run to ServicePower’s requirements.

Benefits to the company

Benefits to the academic