Reinventing manufacturing

How AI and the next generation can bridge the skills gap. By Jean-Baptiste Clouard


The skills gap in the manufacturing industry is a growing problem, and we’re increasingly seeing new ways of talking about an old problem. The manufacturing industry has a historic, old-fashioned perception that can often deter younger workers from choosing it for their career path – it’s an industry that can been seen as stuffy and under-paying.

But we’re slowly seeing a transformation happen that subverts all these perceptions in Industry 4.0. Industry 4.0 is the emergence and increased use of new technologies as part of the new industrial revolution and is shaping the direction of the manufacturing industry today.

New and emerging technologies, and new AI-focused start-ups, are creating career opportunities for the likes of software developers and engineers in the hopes of using AI to automate processes and create innovative ways of addressing problems. But that does leave the need for these skills, and where do manufacturing companies access them?

The greater need for skills
Manufacturers often cite the skills gap as a reason for a slow transition to more innovative ways of working – there is a need for more technical skills to keep up.

The industry needs to encourage people with skills in these sectors to apply for work in manufacturing and to upskill current employees to ensure they are not left behind. According to a study conducted by The Manufacturing Institute’s Centre for Manufacturing Research and the American Psychological Association, around two-thirds of employees under age 25 said they stay with their current employer because of training and development (69 percent) and career opportunities (65 percent).

Along with the concern of retaining younger workers who leave for higher pay or promotions after developing skills during their first few years of employment, it is important to the new wave of workers that their employer invests in continual development.

One of the reasons cited by manufacturers for the skills gap is that within the industrial transition, there is a greater need for workers to have the technical skills to keep up. For example, AI offers the ability to automate processes – which will save time and money – but can often be underused because of the lack of technical skills in the workforce.

AI in manufacturing
Using AI to bridge the skills gap is not about overcoming humans in the workforce but expanding the role that people have in manufacturing. Where workers once were needed to carry out repetitive processes, AI can be used to automate processes which frees up time to upskill employees. For example, using AI-based supply chain software, such as one provided by Flowlity, at every stage of the manufacturing process will reduce time spent on repetitive tasks and quickly identify supply chain issues. Smaller companies especially can reap the benefits of AI-based algorithms as it eliminates the need to hire data scientists, roles that are extremely competitive in the employment market.

Where once, teams had large amounts of data stored across emails and spreadsheets, by using AI software it becomes centralized in one digital database and can quickly be analyzed. This not only saves time but reduces the potential for human error. Mistakes cost time and money to fix, and the use of AI in manufacturing reduces the likelihood of mistakes being made.

When repetitive processes are automated, employees are given the opportunity to train in new areas and further develop their skills, and we know that this commitment to professional development is key in retaining the skilled employees that are vital in closing the skills gap.

AI in learning and development
The emergence of new technologies could be seen as contributing to the skills gap, but the reality is that when utilized properly, AI can improve learning and development in the workplace.

AI-based eLearning platforms can customize content for each employee, be used to create chatbots that are designed to assess employees on their knowledge, and even make the creation of eLearning content easier through automatic translation features.

This is beneficial to new employees who are looking for a viable and varied career in manufacturing, as well as to existing employees who may not have the knowledge to adapt to the digital transformation, and finally to managers who normally would not have the time to create tailored training plans.

Bridging the gap
By using AI to upskill and train employees, companies can retain the skill needed to keep up with the industry 4.0 transition and remain competitive to rivals.

Employee development isn’t just good for ensuring you have a skilled workforce – it ensures they are not lost to competitors, taking the skills needed to bridge the gap with them. This goes hand in hand with leveraging AI to automate processes that free up employees for training purposes and to optimize the manufacturing supply chain.

Gaining and retaining skilled workers is essential to bridging the skills gap, and effectively implementing AI-based systems is key to making this happen.

Jean-Baptiste Clouard
Jean-Baptiste Clouard is the co-founder and CEO of Flowlity, an AI-based stock optimization and forecasting solution. The solution allows supply chain planners to capture market volatility and react to disruptions in an agile and effective way while connecting a company’s planning to its customers and suppliers. The technology takes external and unpredictable factors that could impact stock into consideration to allow businesses to replenish stock uncertainties and have safety stock.
www.flowlity.com