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- 68% of manufacturers are currently investing in data analytics.
- 46% of manufacturers agree that implementing and using data analytics is no longer optional.
- 32% see the potential for big data analytics and Industrial Internet of Things (IIoT) to improve supply chain performance and increase revenue.
- Manufacturers perceive data analytics as a key component of a successful Industrial Internet of Things (IIoT) strategy across their operations.
The insights gained from big data analytics and the Industrial Internet of Things (IIoT) to drive greater manufacturing intelligence and operations performance is considered essential by 68% of manufacturers. These manufacturers are planning to increase their investment in data analytics in the next 12 months to improve operational performance and gain greater insights into how they can excel. These and many other findings are from Honeywell’s latest survey, Data’s Big Impact on Manufacturing: A Study of Executive Opinions. The survey was jointly conducted by Honeywell (NYSE: HON) Process Solutions (HPS) and KRC Research Inc., from May 23 to June 8, 2016. More than 200 North American manufacturing executives took part in the study. An infographic of the results is provided here.
Key takeaways of the study include the following
- The majority of manufacturing executives interviewed (68%) see analytics as a must-have to improve revenue, strengthen competitive advantage and streamline their businesses. 67% of manufacturers are pressing ahead with plans to invest in data analytics even as they pare back spending in other areas to combat tough business conditions.
- Using Industrial Internet of Things (IIoT) technologies and solutions to capture equipment data, combined with big data analytics to interpret data sets can reduce equipment breakdowns (26%) and alleviate unscheduled downtime (23%). Also, combining IIoT and big data analytics can help to reduce unscheduled maintenance (43%). Gaining greater insights into advanced manufacturing metrics including Overall Equipment Effectiveness defined in the post 10 Ways Machine Learning Is Revolutionizing Manufacturing is now achievable. The following graphic provides insights into eight areas manufacturing executives predict big data analytics can contribute to improving manufacturing performance.
- Gaining greater insights and creating more valuable manufacturing intelligence leading to well-informed decisions in real-time (63%), optimizing operating costs by reducing wasted resources (57%), and predicting the risks of downtime (56%) are the top three benefits big data is delivering to manufacturers. Big data analytics combined with IIoT systems can significantly increase the accuracy of maintenance and repair schedules (51%), find quality problems and defects in work products (43%) and predict workloads (43%). Manufacturing executives consistently rate big data analytics and IIoT as being pivotal in improving supply chain performance (46%).
- Enabling real-time decisions and avoiding unplanned downtime, and improving supply chain performance (both 32%) are the two areas where big data analytics can have the greatest impact on manufacturing. Big data analytics can also help manufacturers be more efficient in how they use and manage resources (31%). Gaining greater manufacturing intelligence into operations can also lead to making facilities safer and more secure (28%). The following graphic provides a comparison of nine areas where manufacturing executives see big data analytics making the greatest contributions to their businesses.
- Manufacturing executives now see analytics as integral to their current and future strategies and are confident their teams are going in the right direction. 50% of executives believe their company is right on track in its use of data analytics, and 16% believe they are ahead of the curve. 87% are confident in the direction their company is headed regarding big data and predictive analytics.
