In the age of IIoT, the Industrial Internet of Things, the magnitude of information that organizations must swim through to analyze to make business decisions is growing exponentially. An almost unimaginable amount of data is created every day. Per a recent Statista report, we create 402.74 million terabytes of data daily. In the next few years, this number will increase substainially as companies continue to invest in IIoT. Such numbers demonstrate an incredible magnitude of information that organizations must swim through to analyze to make business decisions. Whether you are drowning in spreadsheets or lost in data from IoT machine sensors set up in your factories, consider the factors of high-level insights, prioritizing intelligence and optimizing for real time to make business sense from enormous amounts of data.

Shallow Dive Analytics

It is hard to sink when you are staying shallow. Sometimes it is okay to be shallow. If you are responsible for global product quality, do you really need to know the performance of every supplier? The principle of “less is more” needs to be taken into consideration. It is imperative that we focus supply chain executives and knowledge workers on the key set of metrics that provide high-level insight and directions on the areas that need a deeper dive.  Deep dives don’t make sense without first skimming the surface to determine where to explore further.

Real Intelligence

Swimming, just like chasing down issues that impact supply chain performance, can be a very resource-intensive task. Whether you are a VP of Manufacturing or a Plant Manager, you know there are too many issues at any given time to keep up with. What are the key performance indicators that truly influence performance? How can these KPIs be affected? If one metric changes, does it truly impact another one? Real intelligence is not simple “roll-up or roll down analytics.” Real intelligence is understanding which KPIs can be affected by change, and how much those KPIs are altered. Such KPIs are called indirect KPIs—they correlate to other KPIs but not directly, rolled up or rolled down. By providing correlating KPIs, organizations leverage real intelligence to connect the dots.

Real Time

The use of real-time business intelligence can have a strong impact on supply chain performance. However, taking a current analytics and metrics program and simply increasing velocity and frequency of updates can cause a drain on computational and organizational resources. A redesign of a metrics program may be required to truly understand which metrics benefit the organization and if the organization has capacity to manage these real-time metrics. How easy is this? Consider taking daily metrics to hourly refreshes if the information can be acted upon in that time frame. A key element of a redesign is to reduce the metrics to a shallower level, thus providing supply chain teams with the ability to accept, review, and act on such metrics.

Conclusion & Key Takeaways

Organizations must shift from simply collecting volumes of industrial data to making it actionable, in the age of IIoT. Navigating this sea of data requires a strategic and approach to filtering, prioritization and smarter analytics. Here are key takeaways as you chart your course:

• Start with a Shallow Dive: Focus first on high-level metrics to identify where deeper analysis is truly needed. Don’t overwhelm teams with unnecessary details.
• Prioritize Real Intelligence: Understand the cause-and-effect relationships between KPIs, especially indirect ones, to gain meaningful insights and drive performance improvements.
• Optimize for Real Time (Smartly): Speed alone isn’t the answer—ensure your analytics program is redesigned to support real-time metrics only where action is possible and valuable.

Ultimately, making business sense of IIoT data means rethinking how you measure, analyze, and act—ensuring every insight drives smarter decisions without drowning your team in complexity.