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Analytics improves design and production processes for BMW

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Automobile manufacturer BMW Group is using big data and analytics technology to optimize products, repairs and maintenance.

The car company has chosen IBM Big Data & Analytics to gain insights from large amounts of data that can be incorporated into product design and production processes. Predictive analytics helps detect and fix vulnerabilities before new models are launched. The analyses include product and development data, as well as warranty, diagnostics and repair information that is gathered and evaluated globally. Analyses that used to take several months are available within a few days, so that potential issues are discovered and repaired quickly, according to IBM.

Further, the company reports its IBM SPSS predictive analytics software, for example, helps to combine and analyze data from test drives of prototypes, an average of 15,000 faults recorded by vehicles and details from recent workshop reports. Vulnerabilities are quickly identified and eliminated before new models go into series production. The results of the analyses are immediately directed back to operations, helping to lower error rates and save money, IBM says.

Another benefit, according to IBM, is the automation of certain analyses, because different business divisions and subsidiaries often have similar analytics queries. For those recurring questions, a solution can be used to provide answers to a range of queries. About 250 of those analytics applications are available, enabling more than 500 users from BMW Group to perform their own analyses. The proportion of analytics provided on a “self-service” basis is rising continuously, IBM reports.

(Image courtesy of ShutterStock.com)

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