Auto industry is one of the prime movers of a country economy. In the auto industry, it’s been estimated that warranty costs automotive companies more than $35 billion in the US annually. That’s a huge amount considering the tough economic conditions most companies are operating in.Considering this tough environment, it’s imperative that Auto companies explore all opportunities for reducing costs. Optimizing warranty cost is a very important lever in the cost equation for automobile manufacturers. If one is able to get even a marginal improvement in money spent in warranty cost, it can have a multiplier effect on the overall bottom line. One of the most underutilized dimensions to optimizing warranty cost is inputs from service technician’s comments. The intelligence embedded can be extracted and acted upon
Its very important to formulate some of the business questions which can be answered by the text mining process. Here are a few indicative business questions
1.Which are the prominent problem areas to be concentrated upon at individual dealer levels based on comments from the technicians?
2.Which are the top 5 Car components mentioned in terms of frequency of occurrence in service comments in the last 3 months and what does that tell us about suppliers and/or internal manufacturing processes?
3.Is their seasonality to occurrence of key words related to component failure? Is there a sudden spike in the keyword ‘OIL SPILLAGE’ , 'FUEL PUMP', 'COOLANT' , 'BRAKE LINING', 'SHORT CIRCUIT', 'FLIMSY' during the winter season?
4.Is there a strong association between the keyword frequency and a components rank in terms of warranty cost?
5.Which supplier part frequently comes up in technician’s comments regarding faulty products observed while servicing a car in its warranty period?
This forms the first step in a journey to completely extract 'signal patterns' buried in years of interactions a technician has with servicing a vehicle. This experential knowledge can be chunked and built upon to further reduce warranty cost which is a huge sword hanging over most Automotive organisations
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