Provider of software and data solutions MAM Software has announced details of a new big data solution that enables the analysis of parts lookup and fitment trends from across the industry.
The platform is part of the MAM catalogue data suite and provides access to data compiled anonymously from thousands of users of MAM’s Autocat catalogue and Autowork Online garage management software.
Garages, suppliers and distributors can all benefit from big data. MAM is launching a free monthly ‘Insights’ ebulletin, which highlights key performance indicators from across the industry.
Companies that require more detailed information can purchase bespoke reports for in-depth monitoring, trend analysis, reporting and analytics.
A data feed service will additionally allow subscribers to manipulate and analyse data in third-party tools.
MAM’s big data offering is designed to give companies within the automotive aftermarket a valuable competitive advantage by bringing together historical data and predictive analytics.
Through its new data and reporting service, MAM is able to illustrate the best-selling regions for specific parts, and regions where parts are not selling.
This can help factors assess and adjust their stock levels accordingly.
Factors can also see where opportunities for sales have previously been missed; having this information can help avoid sales being lost in the future due to a lack of part availability.
Analysis of historic trends can also predict the failure rates of specific parts. MAM’s data is capable of indicating the probability of a replacement or repair when a vehicle arrives at a garage with a given mileage.
Nigel Clemett, general manager at MAM Software, said: “Garages, suppliers and distributors process large amounts of data on a day-to-day basis, and we’re offering a solution that will put all this information into a useful, insightful format.
“Suppliers can gain an invaluable insight into the popularity of certain parts, while garages can use the data to better guide fault diagnosis. The potential of big data is endless.”
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