The process manufacturing industry is experiencing a talent shortage that could potentially worsen with time if not proactively addressed. Faced with an aging population of workers, the manufacturing industry skills gap will only continue to widen if the industry as a whole does not do more to attract millennials and Generation Z.

When good operators retire, they take all of their operational knowledge with them due to lack of digitized documentation. With careers spanning 30 to 40 years, these operators are walking encyclopedias of knowledge. Companies lose these knowledge databases when they retire. The industry has not done a great job of backfilling these positions and documenting this trove of expertise. An inexperienced operator manages assets and processes poorly, which leads to inefficient production in terms of energy, chemicals, and labor costs.

This is where Artificial Intelligence (AI) and emerging technologies can help bridge the skills gap. They allow process manufacturers to thrive and attract new and emerging talent.

Are you feeling the strain of talent management within your manufacturing operation? If so, consider the following three areas.

Fixing the “old school” mentality to address the skills gap

According to Deloitte, the manufacturing skills gap will widen so much by 2025 that it will create 3.4 million openings for skilled workers and 2 million of those roles will go unfilled. Driving this will be the 2.7 million workers that will retire or leave the industry, combined with the roughly 700,000 jobs that will be created by growth within the industry.

A perfect storm of factors and misperceptions are potentially exacerbating the industry’s lack of appeal to emerging workforce. This will ultimately hinder talent acquisition and retention. Reasons include the perceived lack of innovation and use of antiquated technology systems that are siloed from each other.

For example, a single process analyst at a bottling company can be responsible for maintaining assets at 12 plants. At each facility, there might be five different types of software systems that house data within complex and aging, on-premise environments. As a result, industrial plant operators have to make decisions based on years of on-the-job experience and cumbersome tools to monitor the performance of assets. However today, with a strong performance monitoring technology, that process analyst extracts data from their systems, determines if the data can solve their particular problems, then applies AI to analyze and provide a greater level of data intelligence.

How can AI help bridge the legacy technology gap?

One of the biggest areas where AI can help immediately is by providing data that is mobile and on-demand. Our performance monitoring solution leverages AI to collect data from disparate, legacy systems, many of which emerging operators have no interest in learning because they are hard to use and not intuitively designed. For example, it is not uncommon for a process manufacturer to have sensor data located on one legacy platform, maintenance data in another, and financial data in a third system. This makes it difficult and time intensive to extract the data. Plutoshift connects all the data sources, extracts the relationships, and converts that data directly into actionable intelligence by surfacing relevant information at the right time.

AI can add years (of experience) to a person’s life

AI can help a more inexperienced engineer perform at a higher level. By collecting data across the organization, identifying trends, and discovering correlations, AI can then focus on living up to the second part of its name: Intelligence. After performing advanced analytics on the right kind of data, Plutoshift’s performance monitoring solution presents information to an engineer that allows them to make decisions in an intelligent way. No longer are 40 years of on-the-job expertise required because AI’s capabilities can fill that void. But do keep in mind that this person is absolutely still required to do the job. This is a common fear. No piece of analytics software, no matter how insightful, can replace that person. In fact, PwC reports that robotics and AI will create a net gain of 200,000 jobs in the U.K. alone by 2037.

The skills gap is a very real concern. The challenge in attracting the younger generation to work in the process industry is shedding the outdated notion that they’ll be working the factory floor like their grandparents did. The industry is evolving just like others. It is no longer about being covered in grease and carrying a big wrench to adjust machines. Today, it’s about leveraging advanced and emerging technologies capable of tasks that older generations couldn’t even imagine. It’s going to be the promise of working with these innovations that attract the next generation of the process industry workforce.

To learn more about how AI can help your organization, please read: 5 Things to Consider When Implementing Advanced Analytics for Industrial Processes