A challenge with wider spread adoption of IIoT has been in pinpointing use cases that showcase real ROIs from effective implementations. There have been numerous proof of concepts conducted across industries but not many actual implementations to study and gather evidence on ROI impact.
The team at Bsquare, a company that provides IIoT software solutions, recently conducted its Industrial IoT (IIoT) Maturity Study, which begins to gather some promising data. The study was conducted among 300 respondents at companies with annual revenues in excess of $250M and evenly divided among three industry groups including manufacturing, transportation and oil/gas. Respondent titles included senior-level personnel with operational responsibilities. On the surface, it appears like a nice sampling across these industries. Keep in mind, these industries represent the most bullish ones for adopting the IoT.
According to the study, Bsquare’s maturity model was broken into five levels with “device connectivity” as the lowest maturity level to “edge computing” as the highest one. Data monitoring, analytics and automation represented levels two, three and four, respectively. Here are a few worthwhile results from the study.
- “86 percent of industrial organizations have adopted IoT, but fewer than half are using advanced analytics and only a quarter have taken steps to automate the application of insights.”
At this early stage, gathering data is the primary focus. However, as we have pointed out before, the higher level value gained from IoT is absolutely through the actionable insights gained through real-time business intelligence. I believe this simply represents a market in its early stages though and not a impediment to growth. In other words, where enterprises are today is a greater reflection of timing and early exploration more so than any other issue.
The study found that the major goals among business managers for IIoT implementations were:
- Gain better visibility into and control over business-critical equipment
- Gathering real-time device information
- Achieve better device management
- Improve device optimization
The study noted that only “a small portion (less than a quarter) wanted to focus on operating cost reduction, increased production volume and better compliance.’ I found the “focus on cost reduction” surprising since other studies seem to portray “cost efficiencies” as a major driver of ROI for IIoT deployments. However, this could be due to enterprises taking baby-steps first before setting hard financial goals that could damage budgets required to figure out the details.
- Majority of IIoT investments are currently focused on the least mature stages, connectivity (78 percent) and data visualization (83 percent). Only half are doing advanced analytics on that data (or stage three) and only a small number (28 percent) are automating the application of insights derived from analytics (stage four).
This last stat really shows the infancy of IIoT in the market. Even with great enthusiasm among enterprises to deploy IoT, there are still many factors to be figured out. Connectivity issues associated with security, data privacy, multiple connectivity options, costs and a lack of standards are major obstacles for enterprises to figure out still. But the fact that enterprises are investing and experimenting in IIoT is a huge sign of its market emergence.
