Designing, engineering and manufacturing cars requires immense precision. Not only should cars look, feel and sound great, but they also need quality, longevity and perhaps most importantly, safety. Manufacturers and consumers want their new cars to be perfect – and rightly so. Building cars is as big an investment as buying them.
Sometimes though, for all the many millions spent by the industry on research, development and testing of cars, problems occur and in the worst of all cases, vehicles must be recalled. Just recently, in fact, General Motors issued a recall for some of its Chevrolet Colorado and GMC Canyon pickup trucks in the US due to a fault in the transmission shift lever. In this instance, around 7,000 vehicles in total are set to be recalled, no doubt at considerable cost to GM, but recall figures can often stretch to hundreds of thousands or even millions of units. Needless to say, this can have catastrophic repercussions for a brand’s reputation.
Should a problem be identified two months into production and corrected right away, it will safeguard future output, protecting not only potentially hundreds of thousands of vehicles, but also priceless brand reputation.
To minimise the disruption and cost associated with large scale vehicle recalls, and to keep customers happy, manufacturers are now looking to analytics to predict and prevent potential future recalls before the cars have left the assembly-line.
Boasting one of the most admired and recognised brands in the US, American Honda ensures the continued quality and performance of its vehicles by listening closely to its customers – and its data. After all, there’s plenty of data to make use of. Warranty claims, technical helpline data, customer feedback, parts and vehicle sales can all be analysed to gauge quality and safety, essentially by looking at anything that could possibly go wrong with a vehicle.
By comparing customer and technician feedback against manufacturing and other systems data, American Honda has been able to develop an early-warning system which searches for recurring patterns and trends that could indicate a problem. As soon as an area of possible concern is identified, the team can immediately alert engineering, manufacturing, or even the dealers’ repair shops.
Analytics is helping car manufactures make better decisions and discover potential issues before they ever become problems – as well as ensure that they are addressing the right causes.
By making use of the data it already possesses, American Honda is supporting engineering improvements to build better vehicles, meaning less cost to the company and in turn, less expense and inconvenience to its customers. After all, should a problem be identified two months into production and corrected right away, it will safeguard future output, protecting not only potentially hundreds of thousands of vehicles, but also priceless brand reputation.
Analytics is helping car manufactures make better decisions and discover potential issues before they ever become problems – as well as ensure that they are addressing the right causes. For companies like American Honda, this can mean savings of hundreds of millions of dollars.
The opinions expressed here are those of the author and do not necessarily reflect the positions of Automotive World Ltd.
Cindy Etsell is a manufacturing specialist at SAS UK.
SAS (www.sas.com) is the leading provider of enterprise intelligence software and services.
For more information about SAS, please visit: www.sas.com/offices/europe/uk/ or www.sas.com
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