What's the next frontier for big data?

MGI (McKinsey's Global Research Institute) and McKinsey's Office of Business and Technology show that the amount of information in the world is exploding, and that large analytical datasets--so-called big data--will be one of the key foundations for a new round of productivity growth, innovation and competition.

The rise of multimedia, the increasing amount of information captured by social media and Internet of things, will lead to exponential growth of data in the foreseeable future.

McKinsey has studied big data in five major areas – health care in the United States, the European public sector, American retailing, U.S. manufacturing and global personal location data. For each area, large data can create value.

For example, if you make full use of large data technology, retailers can increase their operating profit rate by about 60%. Large data can also be tapped in the public domain, and if the US healthcare industry can creatively and efficiently use large data to improve its efficiency and quality, it can generate more than 300 billion of billions of dollars a year. With big data in Europe's developed countries, government managers have saved at least about € 100 billion (about $149 billion trillion) in terms of increasing operational efficiency, excluding the use of large data to reduce fraud and errors.

In addition, users who use personal location data to provide services can also create 600 billion of dollars in consumer surplus. The study presents seven key points:

1. The data has been deeply related to various industries and business functions, and has now become another important factor in productivity besides labour and capital. It is estimated that by 2009 companies with more than 1000 employees in all sectors of the United States would have at least 200 megabytes of storage data (twice times the size of the U.S. retailer's Wal-Mart Database in 1999).

2. The following 5 ways of using large data can create value. First, large data can release enormous value through transparent information and more efficient data utilization. Second, as organizations create and store more transaction data in the form of data, they can gather more accurate and detailed performance information from product inventories, identifying improvements and improving performance. Some backbone enterprises are using data collection and analysis to carry out control experiments in order to make better management decisions. Other companies are using large data for low-frequency forecasting and High-frequency short-time forecasting, in order to adjust the operating lever in time. Third, large data can be more segmented user groups, thereby customizing more accurate products or services. Four, complex analysis can significantly improve decision-making. The use of large data can improve the next generation of products and services. For example, the manufacturer can use the data embedded in the product to create more innovative after-sale services, such as proactive maintenance (i.e. preventative measures taken prior to or aware of a failure).

3. The use of large data will be a key basis for individual companies to enhance their competitiveness and promote growth. From the point of view of competitiveness and potential value, all companies should take big data seriously. In most industries, similar competitors and new market entrants will use data-driven strategies to innovate, compete, and gain value from deep and real-time information.

4. The use of large data will trigger a new round of productivity growth and consumer surplus. For example, we estimate that a retailer that makes full use of large data can raise its operating profit rate by about 60%. Large data can bring significant benefits to consumers, companies and organizations. For example, users who use personal location data can also create 600 billion of dollars in economic surplus.

5. Although large data can be used across sectors, we contrast the historical productivity of the US sector with the potential value of these sectors from large data (using indexes to combine some quantitative indicators), and find that opportunities and challenges vary from sector to department. Computer Electronics and Information departments, financial insurance and government can derive greater benefits from the use of large data.

6. Some organizations will lack the appropriate talent to use large data. By 2018, only the United States would have lacked 140,000 ~19 data analysts and 1.5 million managers and analysts who knew how to make effective decisions using large data analysis.

7. In order to fully exploit the potential of large data, some problems must be solved. In the world of large data, policies on privacy, security, intellectual property, and even legal liability need to be established. The organization needs not only to put the right talent and technology in the right place, but also to build workflows and incentives to bring together information from data sources, often from third parties. In addition, incentives must be in place to ensure that this can be achieved.