New Value Generated by Big Data (Part 2)

In business, how can we effectively use the massive amounts of data available in society to achieve innovation? This is where we turn to data-analysis experts. In the second of a two-part series, we interviewed Mika Kawai, Director of the Fujitsu Big Data Initiative Center, and Isamu Watanabe, member of staff at the Big Data Initiative Center and General Manager of the Fujitsu Laboratories Second Solution Research Division. Our discussion centered on the Big Data Initiative proposed by Fujitsu.

New Value Generated by Big Data (Part 1)

In addition to in-house company data, external data is released by government organizations, public transportation agencies, and social media. Is this kind of data also important?

On March 29, 2012, President Obama announced the Big Data Research and Development Initiative, with a budget of about USD $200 million. The initiative aims to encourage the use of Big Data as it keeps rapidly increasing in volume. This initiative was based on proposals by the President's Council of Advisors on Science and Technology, a presidential advisory committee. The aim is to increase government investment in Big-Data-related technologies. In response to this announcement, the United States government is moving to release data owned by government and public agencies at an accelerated pace. The resulting Big Data can be used to resolve urgent issues that may face the nation, including natural disasters and security breaches.

In coordination with these efforts, the Japanese government also declared its intention to step up initiatives to develop Big Data technologies under its leadership. The main trend in Big Data in the near future will be information innovation generated by combining two different types of data: external data, called "open data," which is owned by governments and public agencies, and internal data owned by companies. Big Data on earthquakes, which was hotly debated after the Great East Japan (Tohoku) Earthquake, is one such example. Moves are now being made in regions across Japan to use the massive amounts of diverse data gathered from car navigation systems and mobile phones during earthquakes for disaster prevention and community development in the future (Watanabe).

Could you tell us about the Big Data Initiative proposed by Fujitsu?

The Big Data business requires us to analyze the data that is valuable to our customers. There's no point from a business sense in proposing things that may or may not be of value to customers. We're the ones who deal with the customers' Big Data, so to understand what is of value we need to understand our customer's business operations.

Fujitsu intends to contribute to business and society through the use of ICT; to this end, we're already offering on-site services to support a variety of corporate activities. In the area of Big Data analysis, just as in other areas, getting on-site operational experience from a company serves as the most useful business tool. Fujitsu has some 1,000 Big Data experts, including data analysts specializing in statistical analysis, machine learning, and algorithm development - Mr. Watanabe is a leader in this field. Furthermore, we have experienced system engineers, consultants, curators (data scientists) and data architects. Using big data, these data-analysis experts propose business ideas that are best suited to customers' industries and business sectors. The Fujitsu Big Data Initiative is outlined in the diagram below (Kawai).

Fujitsu Big Data Initiative: Chart of Products and Services for the Utilization of Big Data

Highly experienced specialists provide consulting services that meet the needs of different industries and business sectors.

Fujitsu is working hard on developing professional personnel in this area. However, we have to avoid a situation where only certain staff members can perform analysis (though this isn't exactly the same thing as individualizing big-data analysis). So, we always use cutting-edge ICT. To encourage our customers to develop their own data-analysis experts, we also provide Fujitsu learning-media services and training programs for on-site innovation.

Software packages for simple behavior analysis and demand prediction are already on sale to customers. However, Fujitsu's Big Data Initiative provides services delivered by our experts for customers who need special data analysis, such as selecting multiple software applications or customizing them to meet specific requirements.

We believe that to gain a competitive advantage, customers need to innovate by using both internal and external data to develop new services across companies and industries. To this end, it's necessary to promote inter-industry collaboration between our customers and ourselves. As we announced last week, we also offer opportunities for co-creation in our new IoT initiative, to encourage customers to make full use of Fujitsu's technologies and professional services.

To begin with, Fujitsu has developed 10 categories of offerings based on our past case studies to provide customers with tips for data utilization.

We once had a company consulting with us about how to use Big Data in marketing. The customer wanted to analyze the Big Data within the company and to create an in-house market research system designed to allow the company's marketing staff to do marketing analysis on their own.

So, to meet the customer's needs, we held a marketing workshop on strategies designed to reach individual customers. This was using the omni-channel solution called the "Customer-Experience Solution Based on the Sharing of Customer Contact Information," which is one of Fujitsu's offerings. Our goal wasn't to create a conventional system for POS analysis at the Head Office. Rather, we wanted to show how to use on-site data on individual customers to increase sales. In other words, we were required to create innovation through the use of ICT, including methods of gathering, analyzing, and presenting data (Kawai).

Finally, explain the challenges that need to be overcome to promote Big Data use, and your thoughts on the future prospects of Big Data.

There certainly are challenges that need to be overcome to promote the use of Big Data for corporate decision-making and business process innovation. How best to deal with personal information is one of these issues. Data that contains no personal information is of no value as information. So we have to develop privacy protection technologies that allow us to use data as information without identifying individuals. Fujitsu Laboratories is doing research and development on these kinds of technologies. As well as that, it's important to develop public consensus on the secondary use of in-house personal data as Big Data.

The fact is, many business managers are reluctant to release data that might reflect badly on their companies when they collaborate with us on the use of Big Data to predict demand or detect problems.

A lot of the companies that are hesitating to use Big Data are big, with different divisions in charge of storing data. That means business managers aren't always able to use their company data without restrictions. To achieve innovation through the use of big data, it may be necessary to consider the possibility of reorganizing corporate decision-making processes themselves.

There's no doubt that the use of Big Data will accelerate in the future across society. In an IoT society, there's not just mobile data, but also security and cloud data. Any discussions about how to use such data will necessarily involve discussions about Big Data. In the future, the existence of Big Data will be taken for granted. So, there may come a time when the idea that people should be encouraged to use Big Data in business will become meaningless as such.

At the same time, data gathered from sensors installed everywhere in our social environment will be used more and more often. How can we provide professional information analysts who can sensitively capture such trends and make new proposals one step ahead of the times? This is the opportune time to show Fujitsu's true value (Watanabe).

New Value Generated by Big Data (Part 1)