Sanjay Ravi, Worldwide Managing Director for Discrete Manufacturing, Microsoft Corp.

Manufacturing executives are seeing big results from big data. The capacity to mine and manage data by connecting factory floors, enterprise IT and analytics software creates one holistic, intelligent system—and it’s empowering companies around the world. Data is the new currency for manufacturers and when companies bring together four big Vs of big data—velocity, volume, variety and value—they are realizing the “Data Dividend” and can witness the transformative effect of this technology. The ability to analyze all this data is making manufacturers more productive, enabling them to transform their business models and allowing them to offer not only products but services as well.

ThyssenKrupp is a good example. As one of the world’s leading elevator manufacturers the company maintains more than 1.1 million elevators worldwide, including those at the 1,263-foot CMA Tower in Riyadh, Saudi Arabia. Officials at ThyssenKrupp have connected their elevators to the cloud, collecting data from sensors and converting that data into valuable business intelligence. The ability to continuously monitor elevator performance lets ThyssenKrupp offer predictive and even preemptive maintenance to customers, without having to send a tech to check on the elevator in person. This enables it to modernize the way they offer services and be more efficient.

Another example of data’s value is Advanced Micro Devices, Inc. (AMD). In testing semiconductor wafers, AMD analysts use a data warehouse to store and process more than a terabyte of data a week. When the company’s legacy data warehouse began to falter under the load, AMD migrated to a high-speed, parallel data warehouse platform from Microsoft. With vastly improved data warehouse performance, analysts can quickly understand performance trends, uncover issues and generate data required by engineers across AMD. The company is now processing up to 13,000 queries a day with a runtime of a few seconds. Additionally, the backup that used to take the warehouse team a week, now takes about two hours. The new platform has also reduced the support work required of the data warehouse team by about 90 percent.

Ultimately, all of this helps AMD develop microprocessors faster and get them to the market sooner—and potentially gain an edge on the competition. The AMD case underscores why big data is seen as the new currency in industry, especially for manufacturers.

More than any other industry, manufacturing stands to gain the most from the value big data provides.

A recent International Data Corporation (IDC) study commissioned by Microsoft concludes that the manufacturing sector stand to gain $371 million in value from data analytics in the next four years. At Microsoft, we refer to this as the Data Dividend. The study also found that the potential value of data affects manufacturing more than any other industry, given the extensive investments in capital goods and fixed assets in this sector. Researchers reported that more than half of the companies participating in the study expected to generate new revenue streams from big data projects, and more than a third anticipated an increase in operational efficiencies from those initiatives.

While the promising yield from data is enormous, most data in manufacturing remains underutilized. At many businesses, data is still kept in silos, its use hampered by old and overly complex analytics tools. As a result, extracting insight from data is often limited to a small number of people, such as IT professionals and data scientists, rather than key decision-makers across the organization.  Moreover, the researchers at IDC concluded that many companies still do not have the capabilities to address the range of technology, staffing and process requirements needed to capitalize on big data assets and deploy analytics on a large scale.

Manufacturers dragging their heels on big data need to recognize getting insights from data is a fundamental investment for building a complete picture of what has happened, what is happening right now and what will happen in the future. Companies can gain this data dividend by combining diverse data streams with their enterprises, using new data analytics tools, delivering data insights to more people in the organization and doing it all faster than anyone could have imagined even a few years ago.

In addition, the impact of big data strategies can be amplified by leveraging other trends such as social networking, mobility and cloud computing, which help manufacturers communicate better, react faster, and fuse innovation into businesses processes, operations and strategies. The intelligence derived by looking at trends can drive growth with smarter product planning and better quality control decisions.

Companies need to be agile enough to get ahead of fast moving global trends that will inform strategies around big data in manufacturing. Social media, for example, spawns intelligence that can drive business growth with smarter product planning and better quality control decisions. Consumer conversations over growing social communities, such as Facebook and Twitter, are creating massive volumes of unstructured data that contain intelligence about product performance and preferences. The intelligence mined from social networks can be used to pinpoint new business opportunities or future production planning and direction. On the other hand, data extracted from social media can also help preempt issues around product quality.

Other trends that impact big data are globalization and emerging economies—and the ability to connect people, processes, systems and equipment across the world. As data solidifies its position as the new currency, the barriers to smaller players in the global manufacturing value chain have been lowered. The connectedness of the new currency lets them penetrate and scale into previously inaccessible markets through newly formed partnerships.

The trend toward connectedness is also reflected in the internet of things, which is more than the latest catchphrase in tech world. It is happening today. Sensors connected across the enterprise to “things” – physical components, devices and other assets critical to mechanized processes—combined with data-analytics software and the cloud are transforming manufacturing plants.

Kuka Robotics Corp. in Michigan, for instance, is bringing the internet of things to the shop floor. The company uses Microsoft technologies to run an automated manufacturing plant that connects assembly line robots with a controller, applications and backend systems to produce eight different Jeep Wrangler bodies on the same production line, enabling the production of a car body every 77 seconds.

The Kuka Robotics case shows that despite major challenges to the manufacturing sector in recent years due the economic downturn, big data is bringing a Renaissance-like transformation to industry, propelling new business models, a boom in analytics-driven decision-making, the emergence of intelligent factory floors, the capability to mine of fresh perspectives on customer wants and smarter supply chains and product re-engineering.

To be sure, the noise around big data can be overwhelming and distracting for executives and decision-makers. But to cash in on this new currency and realize the data dividend, manufacturing firms must make use of data driven intelligence as a central business objective.