Big data analysis: Networking and IT security will determine the success of companies
Big Data

Big data analysis: networking breeds success

How managers in industrial companies are laying the foundation for successful big data analysis.

Big data analysis will also play a critical role in the success of the IoT and Industry 4.0. However, studies show that industrial companies have fallen behind in terms of security and networking.

Big data analysis is somewhat of a bet on the future. And forecasts that envision gigantic sales and hip business models can be described as fairly bold. With almost absolute certainty, it can be said that the IoT and Industry 4.0 will likely become the most important generators of big data. However, generating data is one thing; income-generating analysis is something else altogether. The key to integrated big data functionalities is a high-performance ICT infrastructure. And this is precisely where many companies have some catching-up to do, according to a new PAC study about the state of IoT in Germany. Companies are skeptical of digitization, particularly because of security concerns, the study's authors noted.
But there is some good news to report as well: industry has recognized, in principle, the value of this method – this is particularly true for automakers, a business that, by tradition, is interested in innovations. “The industrial sectors of mechanical and plant engineering and automakers are discovering how to profitably use data analysis,” consultants at KPMG say in their latest study on the issue. As part of Industry 4.0 solutions, managers in these industries are busy compiling systematically produced information like sensor data and location data and then analyzing it, the study says. The findings are primarily flowing into efforts to further optimize product planning and production system monitoring. “The car is a gigantic data-generating machine,” says Dieter Becker, an automotive expert at KPMG. “The intelligent linking and analysis of big data will join the art of engineering to become a vital core area of expertise for innovative automakers.”

New automotive paradigm created by networking

Experts at the Fraunhofer Institute know why companies are very involved with this topic: the automotive industry is anticipating a trend that will lead to the “completely individualized product.” The era known as “lot size one” will represent a paradigm shift in the automotive industry. Up to now, the automotive industry has focused on economies of scale as a way of lowering the price. It will now need completely new processes covering development, production and sales. But: “In the past, attempts to place the car customer at the center of the business failed because automakers frequently lacked the necessary data and communication platform,” the Fraunhofer experts say. That is: the databases were located internally not just among different departments such as development, production and sales. They were also found at independent dealers and automotive banks. In a nutshell: There was even more catching-up to do regarding the degree of networking in the assessment of data. KPMG manager Becker confirms that this was the case. In the future, behavior-driven vehicle and customer data will become the guarantee for long-term revenue, he says. The key to successful analysis will involve the following process: upstream data related to the vehicle and operating conditions (generated by the vehicle) and downstream data related to customers (generated by passengers) must be intelligently combined to meet the challenges of the multi-mobile and multi-networked age.

A self-learning system knows what the customer wants

The practical application of this future networking is reflected in Mercedes-Benz’s new lifestyle configurator, for instance: a real-time recommendation system designed especially for the needs of the automotive industry. This solution was developed by Berylls Strategy Advisors with the help of the Fraunhofer Institute for Intelligent Analysis and Information Systems and consultants of Nolte & Lauth. The configurator considers several hundred thousand possible vehicle configurations, individually per customer, and a number of other parameters. The system does not just deliver precise recommendations. It is also a self-learning device that expands its knowledge base as it works.

No success without IT security

Another learning need is causing anxiety in the industry as well. Even though companies have apparently made major strides in terms of their analytics tools and their solutions have reached a certain level of maturity, security continues to lag. This means that the discussion about the security of these new networks must be intensified. Analysts at Gartner estimate there will be 21 billion IoT devices around the world by 2020. To be prepared for attacks on IoT devices, companies urgently need to update their network access guidelines. About 6 percent of these devices will be used by industry, the consultants estimate. But managers are having difficulties in their work to identify these connected sensors and devices and to designate them in their own network access guidelines.
Late last year, experts at IDC presented a similar argument: “The number of security incidents in production areas has already reached alarming levels. They require immediate action and better solutions and concepts.” More than halfof all manufacturing companies have already experienced unauthorized access. A company's chances of falling victim to cyber-criminals rise as its size increases. For this reason, IT security and compliance must become top priorities when smart and connected manufacturing begins. “The security concerns about Industry 4.0 have nothing to do with ‘German angst.’ They are a real problem,” said the IDC expert Mark Alexander Schulte. “Decision makers must take action right now. If solutions and concepts are not appropriately implemented, IT security will be a show-stopper for Industry 4.0 projects” – and for analytics-driven sales as well.
The bottom line: the industry has apparently understood the meaning of Big Data analysis in the IoT and Industry 4.0 and is busy spinning together effective networks. But these nets must be sewn much more tightly together to prevent bad “by-catch” from coming on board.

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