Recently, LNS Research and MESA International completed the fourth edition of the biennial Metrics that Matter research study, which focuses on identifying the key trends within industry and the performance measurements that are driving value for companies today. In this iteration, the evolution of emerging technologies like the internet (and industrial subset) of things (IoT/IIoT), the cloud, and big data analytics was shown to be a substantial factor in how organizations are investing in financial and operational improvements and trying to drive ROI. There were some particularly interesting results on how companies are approaching analytics today and what trends are being seen within the areas of maintenance and asset performance management (APM).
In this article, we’ll dive deeper into the methodology of the study, important trends around awareness and adoption of technology, and how manufacturers are approaching analytics capabilities today to improve APM, minimize risk, and start the transition toward new business models enabled by new levels of reliability and uptime.
Changing view of manufacturing
The traditional view of manufacturing as a series of self-contained islands of automation, expertise, and control is becoming at odds with the situational reality. Both executives and IT staff are taking more interest in the interconnectedness of these areas than has been typical in the past. As the relationship between manufacturing performance and profitability becomes easier to identify and articulate, the C-suite is perking up to how manufacturing can be leveraged to transform business and the bottom line.
This is seen partly in an examination of who took the current Metrics that Matter survey (N = appx. 250 respondents). With respect to industry, geography, and revenue, the survey breakdown was in line with what we’ve come to expect in our surveys; however, there has been a shift in the individual respondent roles that reflects this evolution in how manufacturing is viewed within the enterprise.
We’re beginning to see more IT and operations management personnel take interest in the survey, while staff are tending to dominate in engineering roles.
Gap in IIoT knowledge is closing rapidly
The skew toward more IT executive participation makes sense given the technology changes coming down the pipeline. There is evidence that the IIoT is starting to factor more into manufacturing considerations, as the survey revealed a large bridging of the gap in IoT awareness and education over the past year: The percentage of survey respondents who indicated that they did not understand the internet of things went from 44% in 2015 to 19% this year. As this education trickles down into investments and implementations, over the coming years the use and sophistication of analytics within and outside the enterprise should continue to grow. Manufacturers already are beginning to use analytics in ways that are advancing maintenance, delivering new value to customers, and enabling new revenue streams/business models.
Analytics use cases inside/outside the enterprise
Not just big data but different data is a key theme as manufacturing software and its use evolves. The survey revealed some interesting use cases of data, both inside and outside the enterprise. While external data sharing instances are concentrated on improving quality and product delivery upstream to suppliers and downstream to customers, 8% of respondents today are sharing data to elevate equipment providers’ maintenance and quality processes.
Inside the plant, we see big data analytics used for a broader range and a larger number of activities. Though process improvement takes the top spot, it is clear that manufacturers are putting a high priority on a better understanding of the performance and output within individual plants and across them. Additionally, the focus on continuous improvement specific to APM is garnering considerable mindshare, with nearly a quarter of respondents indicating this.