The big data is one of the solutions that will change the future of business. Some companies are already making decisions, developing strategies, and changing their future plans, designing their products based on what they say the data analysis and establish how to reach consumers on that basis.
But yet, despite the importance of big data business analysis, only 29 percent of companies surveyed in the report Industrial Internet Insights for 2015, prepared by Accenture and GE, has been mapped for predictive analysis or improve their business operations, although respondents generally believe that big data is important in making business decisions.
For now, big data is lagging especially in more technical aspects. According to the study, 65 percent of companies are using big data for equipment control and monitor possible operational problems (making it a pre-warning system technology failures) and a 62 percent used to collect large amounts of scattered data, which come from various and very different sources.
The report noted the Industrial Internet, fueled by machine-to-machine data inputs, has the potential to drive trillions of dollars in new services and overall growth. But to reap those rewards, industrial companies will need to use insights about their customers and their customers’ use of industrial goods to build new offerings, reduce costs and reinvest their savings. To get there, many must work through a multitude of issues to use their machine data for more advanced forms of predictive data analytics, including sourcing the right analytics talent to ensure effective execution and scaling of analytics programs.
The payoff from joining industrial big data and predictive analytics to benefit from the productivity gains the Industrial Internet has to offer is no longer in doubt. The tally of success for industry is evidenced by the greater visibility and speed-to-decision across operations and asset performance management. But data alone won’t generate value. To make information useful requires an investment in new capabilities and talent that will serve as a catalyst for extracting value quickly.
This situation, according to different studies conducted over the years, is still somewhat risky. The potential of big data goes beyond serving simply sneak tech. Few technological areas have been much potential to improve the financial position and the overall commercial position of an enterprise predictive analysis.
The starting position painting this report does not imply that companies are not interested in big data. A recently Gartner study indicated that 73 percent of companies plan to jump into big data in present and immediate future.
This study also allows for a first approximation of what businesses expect from big data. Nearly 49 percent of respondents indicate that their companies want the big data will help them create new business opportunities, while 60 percent are convinced that they will get to improve their economic performance through improved management of the company.
Moreover, 66 percent are said that their companies could lose market position within three years if they don’t adopt a strategy of big data. In fact, 88 percent respondents said that big data is a top priority for the business operations.
Another Accenture report also indicated that big data is changing the conduct of business for companies and executives to get the most from their big data projects and help ease big data challenges. These forecasts are very much in line with what companies have waited recursively of big data. The increase in profits, resource utilization, and customer experience are the usual points of improvement are put forward when discussing the advantage of big data.