Case Study: Blind Veterans UK


Blind Veterans UK support people who have served in the Armed Forces and are now living with sight loss.  The charity runs a fleet of 93 cars and vans.  Until 2016 they had been managing their fleet administration through a variety spreadsheets, databases and other paper-based methods.  These were becoming increasingly fragmented and time consuming, and Head of Transport, Chris Kirk lived with constant anxiety that something important may be overlooked.  It was time for a change.

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Case Study: Hydrock


Hydrock is a multi-disciplinary engineering consultancy and specialist land remediation contracting business.  Recently ranked 9th in the 2016 Sunday Times 100 Best Companies to Work For, Hydrock’s people work in a variety of complex and high profile environments spanning the UK, and their fleet is of course integral to the successful mobilization of their business.

Hydrock have a varied mix of cars, light commercials, 4x4s and minibuses making up a fleet of more than 250 vehicles, as well as a sizeable grey fleet element too.

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Case Study: Melksham Motor Spares


Melksham Motor Spares are a distributor of quality automotive parts and accessories in Wiltshire, Somerset and the surrounding areas. A family firm established in the 1960s, they have enjoyed consistent growth and earnt an enviable reputation as the region’s premier motor factor.

It goes without saying that Melksham Motor Spares relies on its fleet to keep business moving.  They currently run 24 light commercials, 2 trucks and 2 company cars.

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Case Study: Barlows Electrical


Barlows UK Ltd run a fleet of 234 vans. They were relying on a combination of spreadsheets and paper-based systems to store all of their vehicle and driver information. With a sizeable fleet, multiple branches and a hectic driving schedule to juggle, they were finding it increasingly hard to keep track of data – spreadsheets were becoming overly complex and retrieving information quickly was practically impossible. As the data bank grew, the fleet manager was also struggling to compare and analyse fleet activity, and was concerned that he may be missing instances of excessive cost, high risk or poor vehicle/driver performance.

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