5 Key Trends in IIoT and Data Analytics

Industrial IoT Increases Efficiencies, Value Chain with Better Analytics

The industrial/B2B market is rapidly expanding its IoT proficiency – mostly within the automotive and manufacturing sectors, followed by transportation and logistics. The market leaders in these segments are paving the way to a brighter business future and using IoT to connect their products to a more effective and efficient value chain. The global industrial internet of things market size is expected to reach almost $1 trillion within the next six years, according to a report by Grand View Research, Inc. And is projected to expand at a CAGR of 29.4% during that timeframe.

IIoT brings a full list of advantages, but perhaps most noteworthy is new data management systems and platforms along with access to an unprecedented amount of data that can be stored, analyzed and processed to help enhance business function overall. According to some experts, the data coming from this new digital economy is providing significant and valuable insights companies were never before able to capture. Data once viewed as crude or irrelevant can now be finessed and analyzed and turned into valuable business insights.
 
While much progress and change is proliferating the realm of IIoT and analytics, there are some key trends to make note of:

1. Some of the major tools currently being taken advantage of in the analytics artillery are predictive methodologies, prescriptive analytics, machine learning, forecasting models and neural networks. Predictive analytics has been perhaps the most talked about tool because it’s taken so long to reach fruition but we’ll soon see players fully deployed in this area – which will bring more information about how these solutions should be effectively implemented.
2. Organizations are decentralizing their framework because as IoT grows, the industry is quickly learning that having centrally administered networks not only opens up opportunities for hacking and security issues, it prevents data mining and discovery and the ability to fully optimize the work experience.
3. According to an article in Forbes, the top three reasons manufacturers are most relying on IIoT platforms is for general process optimization (43.1%), general dashboards & visualization (41.1%) and condition monitoring (32.7%). Measuring important performance indicators such as these are helping to reduce cost and time.
4. Artificial intelligence is merging with Industrial IoT to digitize production processes. We are seeing reductions in production waste, minimized downtime and more thanks to algorithms from machine learning.
5. The cloud will slowly dissipate as more companies work on the edge. Research suggests the next step in the digital evolution will address the need to convert algorithms to work at the edge in a dramatically smaller footprint. According to Gartner, within the next four years, 75% of enterprise-generated data will be processed at the edge (versus the cloud), up from <10% today. The reason is due to the amount of data needing to be stored but also better security, lower costs and higher fidelity analysis.

The value that big data and IIoT is bringing to the forefront for organizations will continue to transformation how companies do business.  ​