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Kristian

Commercial Manager

0161 883 2655

Problem

Inconsistent quotation templates being used across the business were causing significant issues with pricing and creating difficulties within operations.

Solution

A tailored quotation tool allowed Anglian to remove inaccuracies whilst also saving them a considerable amount of time .

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The challenge

A-Plant is one of the UK’s largest plant, tool and equipment hire companies. They form part of the FTSE 100 company Ashtead Group plc, the second largest equipment rental company in the world. As well as A-Plant, Ashtead Group also comprises Sunbelt Rentals, the second largest equipment rental business in the USA with over 550 locations, as well as over 10,000 members of staff.

As a result of being one of the largest and indeed most well-known companies of their type in the UK, A-Plant have thousands of customers across thousands of construction and engineering projects, all asking for hire tenders in their own way. As a result of this, huge amounts of manual effort were haemorrhaged into comparing customer requirements to A-Plant’s extensive “product catalogue”, thus slowing down the process of being able to get a price for a customer and start the hire process, often resulting in uncertainty around tenders.

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The solution

The first part of Bespoke’s solution was a data conversion template, designed to allow the easy import of customer data in any format, and converting it into a single, common format suitable for onward use.

The second part of Bespoke’s solution was to bring in variable search strings to allow for parts of customer product descriptions to be compared with A-Plant’s product database. This used several algorithms to rank the potential matches from most likely to least likely and provide an output to A-Plant’s users.

The third part of the solution was to create an exceptions management process for escalating items where the user could not find a match. Additionally, once all items were matched, the customer search terms were added to a library for future reference, reducing the need to do as many manual iterations on any subsequent uploads as the tool’s “knowledge” continues to grow.

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The result

Increase speed of matching and reduction in manual effort, allowing the finance team to refocus on value-add tasks and move away from time consuming administration activities.