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The big three of tomorrow will be winners of data analytics

Posted by Bala Deshpande on Fri, Apr 17, 2015 @ 08:00 AM

For those of us with backgrounds in the automotive industry, the age old term "Big 3" is synonymous with analytics-for-smart-carsGM, Ford and Chrysler. What typifies the big three companies are huge workforces (hundreds of thousands employed), dozens to literally hundreds of assembly plants, and millions of automobiles produced every year. This has been the norm for nearly a hundred years. Is this likely to remain the same?

Recently Fortune magazine reported an interesting aspect about manufacturing: They found that auto companies, specifically GM have signficantly increased their R&D efforts in software, with patents in software increasing to nearly 15% of all their filings in the last 5 years. On the other hand we now have silicon valley companies like Apple and Google entering in to the car market. Apparently, a little known fact about the valley is that manufacturing employs nearly 50% of the workforce! 

What do these trends suggest? 

It seems clear that there is a strong convergence between two of the biggest sectors of the US (and global) industry. According to some, "Today's manufacturers produce more data in a single day than they did in a full month just ten years ago: sensor data, camera images, PLC data, digital gauge data, bar code scans, and much, much more".

This will lead to a shift in the power base - the data "have's" and "have-nots". According to the Financial Times, "When cars were mechanical, the companies that assembled them from thousands of parts wielded more power than their myriad small suppliers, even though they were heavily outnumbered. As cars turn electronic, the suppliers are building a bigger proportion of each one. The cost of the electronic parts in the average vehicle will rise from 20 per cent in 2004 to 40 per cent this year, according to Boston Consulting Group."

An upscale brand of car today may contain more than 100 CPU-equivalents and requires hundreds of millions of lines of software code to operate. A by-product of this technology is of course data. Each of these 100 or so control units pump out operating parameter data by the millisecond. They convey to us valuable information about what is happening in every sub-system of the automobile at every instant. Making sense of this data - gaining real time, actionable intelligence from this flood of data - is the challenge. 

Industry is recognizing the value of data

Ford's Mark Fields acknowledged this mega trend and stated that Ford aims to become much more than an auto company, and transform into an information services company. This makes complete sense because according to Ford, each of their vehicles can generate up to 25 GB of data per hour! Cars are truly the ultimate bastion of data.

We have worked with product development teams in the auto industry which typically only use a small fraction of this data. One reason was simply inability to handle the volumes. Another reason was lack of imagination about what this data could be used for. A third reason was the absence of tools to effectively use this data. All of these reasons were closely inter-twined. But today's technology puts this in the past. Today, and going into the future, if this data is not properly utilized, it would amount to a tragedy. 

Thankfully this environment is changing. According to another recent report, "Manufacturing is emerging from a brick and mortar mentality, realizing that long-term sustainability pivots on the ability to exploit machine-learning algorithms by employing predictive analytics."

It is clear that today's technology giants recognized the importance of data in their business model very early on. It is time for the traditional industries to do the same - otherwise future generations might be calling Apple, Google and Tesla the "Big Three".

Optimize production planning with data analytics

 

Topics: manufacturing analytics

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