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PUBLIC RELEASE DATE:
17-Dec-2012

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Contact: Stefan Wrobel
stefan.wrobel@iais.fraunhofer.de
49-224-114-3015
Fraunhofer-Gesellschaft
@fraunhofer_en

CeBIT 2013: New big data survey shows potential for business

IMAGE: Every industry has specific use cases for big data applications.

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It reveals opportunities and challenges for business. To give companies some orientation concerning big data technologies and applications, the researchers develop an experimentation platform which will be shown at CeBIT fair 2013.

Wouldn't it be helpful if we could just predict business demand or fraud attacks ahead of time? Or justify medical decisions on a more well-founded basis? Or if energy rates could be set on a more customized basis? What if we could make equipment more robust and more intelligent? Lurking somewhere under those mountains of data that accumulate at companies, factories and households every day is the potential that can resolve these questions. Provided, of course, that you know how to use these data efficiently. In this respect, Germany still has a considerable amount of catching up to do, because the issue of "big data" is strongly dominated by the US.

Therefore, over the past several months, the IAIS in Sankt Augustin conducted an extensive survey on the use of and the potential for big data, with financial support from the Federal Ministry of Economics and Technology (BMWi). The objective is to establish a more solid foundation for big data within the German economy. The project has three parts: 1) an international research about big data research and business cases 2) an online questionnaire about big data know how at German companies 3) workshops with representatives from several key-industries. The results have now become available, and first and foremost, they reveal three major key opportunities for the use of big data at German companies:

1. Big data foster more effective business management

So, for example, in the retail business, more precise demand forecasting can be made. The energy industry can better predict how much power will be needed. And for simple processes - like inbound mailings - self-learning systems can achieve greater efficiency through automated procedures.

2. Big data facilitate mass customization

If systems can learn about customers, then businesses could offer more customized services. "This could soon give rise to entirely new service concepts - such as, for instance, virtual assistants that organize individualized car-sharing based on historic mobility patterns," as Prof. Stefan Wrobel, director of IAIS, affirms.

3. Big data lead to more intelligent products

Even today, many systems and types of equipment come with sensors that provide information about maintenance conditions. In the future, these machines could also be equipped with big data intelligence, so that they can process sensor data directly; this would enable them to learn, for example, to adjust to peak loads, and even learn when to repair themselves.

Additional findings from online questionnaire and workshops: Why big data?

Decision-makers from a total of 82 small and medium-sized companies and major corporations from a wide array of industries participated in the online survey. Relevant data available within the participating businesses primarily included CRM-data, emails and letters, as well as logs, master data and case data. When asked to specify the primary goals they pursue with big data, 69 percent said strategic competitive advantages; 61 percent indicated increasing sales, while 55 percent pointed to both higher productivity and to cost reduction.

The companies surveyed indicated that they would absolutely implement big data applications, above all to attain projections on advertising effectiveness (55%), to observe brand perception (53%) and to adjust prices more dynamically (45%). Still, almost half of those surveyed believe that the biggest hurdles they face are the prevailing data protection and security provisions in Germany. In addition, 43 percent pointed to the lack of budget and more urgent priorities. Another 78 percent believe that skilled resources need to be improved. Although all participants had indicated specific goals, one-third of the companies surveyed currently had neither the budget for big data purposes, nor had they planned for these purposes yet. Among the funding measures that companies desire, their greatest wish is for better networking, best practices, training programs and educational measures, as well as revised data protection standards.

The data from the online questionnaire were also validated in the future workshops with representatives from the telecommunications/media industries, as well as e-commerce/mail order business, financial management, insurance and market research. The findings from the discussions about needs, goals and challenges for the use of big data were aggregated into roadmaps. What the quantitative analysis indicated in general was that big data is not technology in the absolute sense, but a strategy issue, first and foremost: "Both in the findings from the online questionnaire and in the roadmaps from the industry workshops, we mainly found aspects related to business administration and corporate policy, in addition to technological challenges," concluded Prof. Stefan Wrobel.

The "Big Data Living Lab"

To seize the opportunities that big data presents, there is a demand for new skills, especially in small to medium-sized companies. "For this reason, our scientists developed the 'Living Lab' experimental platform specifically for this target group. Based on various technologies - both open source and commercial - companies can initially try out a sample data set, to see what is possible in the area of data evaluation," explains Wrobel. Over the long term, the plan is for these companies to bring in their own data, and be able to analyze them. The platform will be unveiled for the first time at CeBIT in Hannover (Hall 9, Booth E08) from 5 to 9 March, 2013. As a supplement to this, starting at the beginning of the year, IAIS will be offering training sessions to companies, where they can discuss the specific requirements and solutions for big data analytics.

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