For those who are familiar with the concept of Big Data, it is a subject most frequently discussed with large retail empires like Amazon or Walmart in mind – i.e. those with millions of daily transactions and sophisticated online sales tools. But automotive and commercial vehicle industry players would be seriously short-sighted to think that the use of Big Data is not coming to their corner of the market. However, the fact remains that many decision makers are still in the dark about what ‘Big Data’ actually is.
Gartner defines Big Data as “high-volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimisation”. Based on this description it seems obvious that any OEM, supplier or even service provider would be foolish not to sit up and take notice of this new information available to them – so why then has the commercial vehicle segment been so slow to adopt Big Data into decision making?
Data analysts have rarely served on the inner circle of executive committees in the past, but with the importance of data increasing, it is as of yet unknown how organisations will breed the kind of insight required to integrate complex data into strategic decision making
Daimler Trucks North America, for example, has only started to discover the opportunities that the correct application of Big Data presents in the CV industry. At present, next generation projects being considered include: tying full specification information to customer data to help them build the best truck for their application; combining repair data and on-board diagnostic data to help purchasers find the break-even point when it becomes financially feasible to buy a new truck; or combining social media and web analytics to purchase data, to help the company understand the dynamics of customer sentiment and loyalty.
However, there are still a few significant barriers which prevent CV OEMs from adopting enterprise-wide data solutions. Amongst these concerns lies the issue of Big Data’s role in decision making. Data analysts have rarely served on the inner circle of executive committees in the past, but with the importance of data increasing, it is as of yet unknown how organisations will breed the kind of insight required to integrate complex data into strategic decision making. On that matter too, comes the question of where so-called ‘data scientists’ will come from. This role combines the skills of a database developer and statistician with the high-level thought of an executive. There are currently very few other roles which would see these skills being combined, leaving industry players unsure who will meet this pressing need.
No new technology is without its drawbacks, and utilising Big Data will see CV players incurring expense, not only through having to directly maintain the data but also via the need to build expertise throughout the company
There is also the matter of ‘Dark Data’, which includes data sets such as social media feeds or qualitative customer feedback. These sets have traditionally been ignored in favour of data which is easier to process but with social media in particular playing an ever important part in customer relations, it is time to take note.
No new technology is without its drawbacks, and utilising Big Data will see CV players incurring expense, not only through having to directly maintain the data but also via the need to build expertise throughout the company, teaching staff to translate analytics into insight.
So, is it worth it? For the near future at least, utilising this information is guaranteed to put CV players one step ahead of the game. Our job now is to continue to translate this opportunity into business growth and profit.
The opinions expressed here are those of the author and do not necessarily reflect the positions of Automotive World Ltd.
Kristen Santos is Manager of market planning and analysis at Daimler Trucks North America.
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