When, in 2011, the Bosch subsidiary Robert Bosch Engineering and Business Solutions was on the lookout for digital trends to diversify its business portfolio, Sri Krishnan and his team identified data mining as one of the possible new business fields for Bosch in India. For the country that contributed the concept of zero to the world of mathematics, it is only natural that it should be an early adopter of this technology wave. Drawing the right conclusions from huge amounts of data sounded pretty straightforward, but turned out to be a highly complex undertaking. “We didn’t let it remain a theoretical exercise; instead, we got straight to work and turned it into a business model,” Sri Krishnan says. They had the full support of Volkmar Denner, the chairman of the Bosch board of management, since big data is one of the elements that is paving Bosch’s way into the connected world.
After all, data is the oil of the global economy. When the India team took its first steps in this area, the Bosch Research and Technology Center in California was already exploring this new field. Since then, the data scientists in the U.S. and in India – 12,500 kilometers apart – have joined forces in a newly established agile service team. The team members share the findings of their data analytics projects and use them as the basis for deriving best-practice solutions. Currently, more than 50 data scientists share in the digital back and forth between the two locations. Hauke Schmidt – the head of the global data mining organization – and Lavanya Uppala confer with each other nearly every day, the former in Palo Alto and the latter in Bengaluru. They run their teams like a start-up business.
Bosch embraces big data, and the associated analytics algorithms benefit its core business. In the information society, mass is the basis for quality. The ability to generate new knowledge from big data is a key competence of the future. That’s why, on the new Renningen research campus and in California’s Silicon Valley, the corporate research sector is not only concerned with practical applications, but also has its own expert teams dedicated to developing new methods of evaluating increasing amounts of data.
The first data mining trials at Bosch manufacturing facilities in India resulted in an immediate major improvement to processes. A similar success was scored in the open market by a pilot project with a major railway company; the goal of the project was to get a handle on electronic ticket fraud. “In every internal project, we generate new knowledge for customer projects – and vice versa. This benefits both sides,” says Lavanya Uppala. One of her favorite examples concerns BSH Hausgeräte GmbH. When a customer reports a fault, the patterns derived from big data allow a conclusion as to the most likely cause – and as to the spare part needed – to be drawn very quickly. The benefits of this method of finding solutions faster will soon also be available to car drivers who come to Bosch Car Service for repairs and maintenance.
Data is increasingly generated along the entire life cycle of connected “things” – from their development, manufacture, and delivery to their use and maintenance. “Our experience lies in analyzing the data from such industrial processes and sensor streams to predict actions that optimize the use of materials, energy, and resources – and in the process generate huge commercial value. This is in line with our ‘Invented for life’ ethos,” Schmidt says. Compelling evidence for this assertion can be found in the automotive aftermarket. When it applied this approach in partnership with an international automaker, Bosch was able to identify potential warranty cases earlier and improve diagnostics readiness at the automaker’s service centers. Uppala sees this as a perfect example of the interplay between the two teams: “We conducted the analysis, and our colleagues in the Automotive Aftermarket division made the diagnosis. Together, we were able to quickly offer a solution.”
To get to the office of the data scientist Rama Mohan D in Bengaluru, visitors have to pass an emergency cabinet, with axes and helmets mounted behind glass. There’s hardly a better visual for the subject of data mining. It’s all about digging deep, extracting, and mining in a constantly growing mass of data. A single set of data of the kind used by analysts comprises 1,000 columns and 20 million rows. And the volume of data keeps growing – by three to four terabytes a year in some projects.
The formula that the Bosch associate appears to be writing so casually on a magnetic board will ultimately be the key with which to wrest a solution and a new business model from ostensibly impenetrable heaps of data taken from various sources. Regardless of where the data comes from – connected industry, social media, or handwritten records – it has to be cleaned up, organized, validated, and prepared. People will always have a key role to play in big data, and not just as programmers. They first have to ask the right questions in order to collect the necessary data, and then compare the analysis with the experience and expectations of practical application. “More than anything else, we have to understand not only the data, but the customers as well,” Mohan D says. “That’s the only way they will be able to gain valuable insights from the data later on.” And it is only then that the big data formula will make sense.
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