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Big data revolution takes root among manufacturers

The big data revolution is making its way into manufacturing, where big data and analytics are being used to solve critical business problems.

For today's manufacturing and industrial firms, the big data revolution is upon us. Not only is the Internet of Things accelerating the use of big data, but the maturing mobile device marketplace is accelerating the growth of big data and its use to drive every decision imaginable.

From customer feedback found on social networking sites to a granular analysis of jet engine defects, today's manufacturing environment is strongly influenced by big data in more ways than one.

Jerry Foster, CTO of Plex Systems, finds that its manufacturing market is continuously experimenting with new tools and technologies to embrace big data. Plex found that 55% of its customers use IP-enabled tools and machines, which automatically adjust to meet product specifications and capture rich, real-time data for traceability.

Also, the convergence of big data and cloud technologies has allowed companies to use business intelligence and predictive analytics in ways that they couldn't before. Now, companies can track trending data and perform predictive and prescriptive analysis by accessing and storing data in the cloud.

Industrial firms embrace big data

The prevalence of big data means industrial firms need to embrace it and use it to not only identify problems, but solve them and affect bottom-line results.

John Kelly, managing director of New York-based Berkeley Research Group, said that industrial firms are most definitely joining the big data revolution. He cited the example of one of his clients, a tire manufacturer that embarked on a customer-centered strategy. Kelly explained that the tire industry is challenged by a fragmented distribution channel of stores without the resources to gather valuable manufacturer data about customer trends.

"This tire manufacturer has made a commitment to gather the data itself. It created a significant social media presence and harvests data from its massive YouTube and Facebook following and related enthusiast feedback," Kelly said. "It scrapes competitive and retail pricing data from online retailers. It monitors new tread interests discussed in online forums. It monitors constantly updated government data on average miles driven per person and numbers of cars sold by type to inform its predictive models." 

Kelly said that the company benefits, knowing precisely what its customers want and when, and can use this insight both for itself and its distributors, improving loyalty to its brands in the bargain. Ultimately, the data is used to change everything from pricing to inventory allocation to the production equipment investment schedule.

Harvesting failure data to improve products

Other manufacturers are harvesting failure data to further improve complex products and technology. Stephen Baker, CEO at Attivio in Newton, Mass., also sees industrial firms joining the big data revolution. He cited the case of GE Aviation.

"They are leveraging big data for predictive maintenance of jet engines they sell to airlines around the world. By correlating data from multiple sensors and sources, such as engine diagnostic data, engine service status, and engine maintenance system notes, GE Aviation can proactively identify the root causes of problems and take corrective action before the cost soars. The direct result is a strong level of customer satisfaction and repeat business with the airlines."

Within the large GE infrastructure, other business units also see the merit of big data. Rich Carpenter, chief technology strategist for GE Intelligent Platforms Software in Charlottesville, VA, said the industry is just starting to experiment with some of the consumer Internet technologies for handling big data.

"At best, we are at the very early stage of this phase," he said. "For less automated industries, the situation is still characterized by a lot of manual paper travelers and very limited visibility to equipment such as CNCs to know how well they are performing. GE views a 'get connected' strategy as critical to these customers."

Other business challenges slow big data adoption

Although the merits of big data are many, its adoption competes with all the major challenges and initiatives that globally competitive firms face today. This means that many manufacturers and industrial firms are slow to fully adopt big data and harness its use to drive decisions that make them more competitive.

"Big data is still struggling with an identity crisis," said David Giannetto, author of Big Social Mobile and How Digital Initiatives Can Reshape the Enterprise and Drive Business Results. "Senior management knows it is important but is still struggling to relate it to their business in tangible ways. As a result, most big data is used for periodic analysis, to either support [or] change an organization's approach to the market."

Giannetto said that big data allows them to survey the market more efficiently than before, in a much shorter time period, and then include findings in nearly every area of their business: from R&D to customer service to add-on products and services.

"Every area of the business can understand big data when it is used in this fashion," he said. "Beyond that, only marketing is used actively in their tactical operations, commonly in the form of personalization or to create a more effective digital omnichannel."

Multiple data sets equal multiple applications

Because data exists in all corners of an enterprise, it's not just the manufacturing production line that stands to benefit from the big data revolution.

Gregg Gordon, senior director of the big data practice group at Kronos, based in Chelmsford, Mass., said that manufacturers can now look at tens of millions of rows of data containing the audit trails of edits made to time cards and schedules.

"A specific example for multiple data sets include labor cost variance analysis," he explained. "This type of reporting is common for most manufacturers, but it is generally a highly summarized and static view of labor costs reconciled with production outputs. By leveraging state-of-the-art business intelligence and visualization tools, manufacturers have now taken a slow and summarized process and turned it into an interactive continuous improvement tool that benefits both operations and cost accounting."

“By leveraging state-of-the-art business intelligence and visualization tools, manufacturers have now taken a slow and summarized process and turned it into an interactive continuous improvement tool that benefits both operations and cost accounting.
Gregg Gordon

In the future, big data should rise in both prevalence and relevance, according to James Quin, senior director of content and C-suite communities for CDM Media in Chicago.

"Three years ago big data could best be characterized as a solution looking for a problem -- businesses could see that there was theoretical value, but just had no idea how to go about getting it," Quin said. "That's no longer the case and big data and analytics are being used to solve key business problems on a daily basis."

Next Steps

Understand data integration issues of smart sensors

Read about lean benefits of IoT data

Learn how wearables impact manufacturing data

This was last published in July 2015

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