3 challenges to overcome in the rise of the new industrial IT workforce

May 11, 2022

These challenges are golden opportunities for our industry to make an urgent and overdue change in our approach to people.

Two years ago, industrial organizations faced shifting market demands, new technologies, and difficulty managing the growing volume of data generated by Industry 4.0. That was before a global pandemic and a labor movement in which a record number of employees left their jobs. Combined, these factors have now created a perfect storm of generational changes in the industrial sector.

These changes are challenges but also golden opportunities for our industry to make an urgent and, frankly, overdue change in our approach to people. It’s time to cultivate and support a new kind of IT workforce, built around a new breed of tech-savvy domain experts and industrial data scientists.

Facing industrial workforce headwinds

Developing a new generation of industrial IT workers means recruiting and retaining greater numbers of industrial data scientists—data scientists with specialized domain expertise in manufacturing backgrounds. 

But as our industry builds this new generation of domain-expert data scientists, there are three main challenges to overcome:

  • Overall labor shortages: Industry labor shortages extend beyond the Great Resignation. For years, there has been a shortage of IT talent. Despite a 98% increase in the number of computer-related grad students over the past decade, supply just can’t keep up with the demand. Growing data volumes and increased adoption of industrial digital-transformation strategies mean organizations are constantly trying to hire new data scientists with the skills to manage these workloads. But there just aren’t enough data scientists and engineers available to meet demand, and the competition to recruit them is fierce.  
  • Skills gap: Beyond recruiting and retention, veteran industrial workers are hitting retirement age, taking with them decades of historical industry knowledge and domain expertise. This is fueling a growing knowledge gap in the industrial sector. It’s important that new recruits are set up for success right out of the gate, but doing so means bridging the gap between the skills and knowledge that those recruits bring to the table, and the skills needed to successfully execute their jobs.
  • High tech expectations: The next generation of data scientists will have high expectations for the technologies and digital solutions deployed by their potential employers. If industrial organizations are behind the curve in their adoption of AI, automation, and other Industry 4.0 technologies that make jobs easier to perform and add value, then potential job applicants are going to look elsewhere. 

How industrial IT leaders can reimagine their organizations for this new generation

We can overcome these challenges in part by digitally transforming and modernizing technologies and processes. In particular, that means adopting new ways of managing, processing, and acting upon their enormous volumes of industrial data. But technology alone only gets us part of the way there—it can’t single-handedly plug the talent gap and meet the expectations of a new generation of industrial workers and data scientists. 

More than just digitally transforming, we need to develop new ways of working aimed at fostering collaboration across organizational silos, developing novel organizational structures and meeting the demands of a more digitally driven industry. 

Here’s what that would entail:

●      Carve out more specialized roles and team structures for data engineers and scientists. Equally adept in the worlds of data science and industrial-domain expertise, industrial data scientists are poised to serve as the face of the future of the industrial workforce. But that has to start with a combination of more targeted recruiting efforts and allocating resources toward creating and supporting more specialized roles and opportunities for industrial data scientists. This includes taking steps for actively encouraging collaboration between industrial data scientists with other teams, like domain experts and product managers; providing more bandwidth to domain experts, so they have more flexibility and space in their day to engage in that collaboration; and investing in more flexible and scalable tools, like reusable toolchains and automated data cleaning. This will help limit non-value added tasks for industrial data scientists and give them the bandwidth to invest their time in more value-adding work.

●      Encourage more collaboration and eliminate silos. New technologies, like next-generation data historians, help universalize the formatting of and access to industrial data. Using digital solutions to build across-the-board access to the organization’s data, instead of siloeing it on an individual or team basis, helps facilitate cross-team collaboration and eliminates the barriers that separate people from each other. Strive to build up your new generation of industrial IT workers together as one team, not a fragmented group of isolated individuals. 

●      Maintain hybrid and remote work as the permanent status quo, not just a “new normal.” COVID-19 spurred a worldwide shift to remote and hybrid work, and there’s simply no putting that genie back in the bottle. This is partly a recruiting and retention tactic; organizations that don’t offer the opportunity to work remotely will surely lose employees and potential recruits to competitors who do. But beyond that, remote and hybrid work are going to be an important, foundational part of the team dynamics within this new industrial workforce. Not only does the remote work option empower teams to work in a more distributed manner, it also creates a more agile organizational structure suited for meeting cross-functional needs. 

As the industrial sector undergoes the tectonic shifts of Industry 4.0, the Great Resignation, and COVID-19—all at the same time—we have two options facing us: get swept away by these trends or get on top of them. By building specialized roles for industrial data scientists and engineers, eliminating silos that inhibit collaboration, and making hybrid and remote work a permanent part of the work culture (not to mention effective recruiting and retention strategies), industrial organizations can put themselves on the cutting edge of these trends—closing skills gaps and cultivating an industrial IT workforce of the future. 

Dwaine Plauche is product marketing manager with AspenTech