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Published on 2019-03-28

Embracing digital transformation in manufacturing means combining IIoT and real-time data analysis.

March 27, 2019

For manufacturers, the road to digital transformation is lacking signage and direction. It’s a move that often involves adopting technologies, such as AI, automation, IoT, and machine learning into the manufacturing process. But incorporating these technologies into the manufacturing process is tricky for a number of reasons such as a lack of formalized strategy, lack of support from senior management, and even resistance from the departments who could benefit the most from these new technologies. Perhaps this is why there is a noticeable lack of successful case studies to learn from.

A bright spot in the digital transformation journey comes in the form of Industrial Internet of Things (IIoT). IIoT is gaining ground as an important tool to propel enterprises forward in the age of digital transformation, and manufacturers are taking notice.

According to our recent report, The Challenge of Turning Data into Action, 40% of manufacturers said their companies are collecting IIoT data via remote sensors.

And the future looks bright for IIoT.

IIoT can be used to collect critical data in the manufacturing process. While manufacturers are still trying to figure out how to use other digital transformation technologies, IIoT is growing across various verticals. In fact, North America is the largest consumer of IIoT technology with a 35% share of the market in 2017.

Looking ahead, the industry is expected to continue to grow and not just in the US. Worldwide, the industry is expected to grow at a continued annual growth rate of roughly 22.9% over the next five years, becoming a $32.9 billion industry by 2024.

Implementing IIoT technology is a great step toward adopting a digital transformation strategy, but embracing this technology is only the first step. Manufacturers must figure out a way to put the increased amount of data collected by IIoT sensors to use.

Manufacturers are likely already collecting vast amounts of data, as it would be impossible for manufacturers to operate without vital stats such as the amount of materials, labor, and energy used. Unfortunately, the current data collection and analysis are often done with disjointed, disconnected manual data collection systems that are embedded into day-to-day operations. According to our recent report, nearly half (48%) of manufacturers still use spreadsheets and other manual data entry tools. These legacy systems often create inconsistent data, causing cost overruns, and imperiling regulatory compliance.

Compounding the problem, these disjointed, disconnected data analysis systems are inhibiting manufacturers from unlocking the full potential of their data collected from IIoT sensors. In fact, only 12% of manufacturers said they were able to take immediate action on data insights automatically. What is to blame? Nearly two-thirds (61%) said it was because some of their processes are automated, but most are manual and 37% said that it was due to a lack of trust in the accuracy of data.

These legacy systems don’t just inhibit manufacturers’ ability to embrace digital transformation but also bring risks to the company. These risks include lack of process improvements (65%), lower response time in informed decision-making (60%), as well as increased waste (59%).

So the question becomes — how can manufacturers move past the barriers set in place by legacy data collection systems, avoid unnecessary risks that come with these collection systems, and move forward in embracing digital transformation technologies?

Over three-fourths of manufacturers (76%) said in order to take immediate action based on collected data, they need software solutions that analyze data in real-time. Manufacturers also identified needing a more efficient way to communicate these updates to people on the line as well as software that can be integrated with other systems so all data and information can be viewed in a single platform.

Software solutions that provide a trustworthy and real-time look at the data collected during the manufacturing process is an essential piece of the puzzle that comes with fully embracing digital transformation technologies. Companies must do more than sprinkle new technologies amongst their processes. They must fully assimilate these technologies into their strategies and make it part of their day-to-day operations.

About the Author
Prateek Joshi is a published author of 9 books on Artificial Intelligence. He has been featured on Forbes 30 Under 30, CNBC, TechCrunch, Silicon Valley Business Journal, and more. He is the founder of Plutoshift, a venture-funded startup based in Palo Alto that provides a performance monitoring SaaS solution for industrial processes. He has been an invited speaker at conferences such as TEDx, Global Big Data Conference, Machine Learning Developers Conference, and Sensors Expo. His tech blog (www.prateekjoshi.com) has received 1.9M+ page views from 200+ countries and has 7,500+ followers. You can learn more about him on his personal website at www.prateekj.com.














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