Predicting Manufacturing Competencies of the Future

Posted By: John Hindman, Director of Learning Services, Tooling U-SME on May 30, 2019

Predicting Manufacturing Competencies of the Future

Manufacturers are focused on the digital transformation that has already begun in the industry. In fact, nearly half (47%) plan to invest in digital technology solutions in the next 24 months, according to SME’s Manufacturing in the New Industry 4.0 Era Survey.

Data is at the core of the new technology, which includes assisted devices for automation, robotics, 3D printing, cobots, augmented reality, and more.

Manufacturers are still making things — but a big part of the job now is determining how information and data can help them make better decisions and solve problems related to quality control, operational efficiency, predictive maintenance or overall cost control.

Guess what they need to do that: well-trained, skilled workers.

To ensure that the technology is used to its fullest potential, manufacturers are investing in training programs and using predictive competency models to build the capabilities they require to remain competitive into the future.

Clearly, the skill sets needed today – and to come -- are different than in years past. Today, workers at all levels must be savvy in instrumentation, sensing and actuation, data analytics, computer science, and systems engineering practices, according to Al Sanders, PhD, president and owner of Design-Vantage Technologies LLC in SME’s Smart Manufacturing: Building Talent to Accelerate a Digital Transformation report.

Forward-thinking manufacturers are already starting to map the jobs of the future and build competencies around those.

I covered the basics of competency modeling in my recent blog post, “Are You Doing Competency Modeling Right?” so I’ll just add a reminder here that competency models define desired performance through a specific set of related knowledge, skills, and abilities.

Assessing an individual against these competencies will clearly and precisely identify gaps, define training requirements, and guide development for current and future roles.

That’s why you don’t want to train toward models that are outdated. It will be important to not only know where you are now – but where you expect to be in the next year, two years, and even farther ahead.

It’s about looking at current work and defining competencies for those jobs while also predicting the manufacturing competencies you’ll need in the future.

How do you do that? It starts with gathering together the smartest people in your organization to talk about where you are now and what’s coming. Which equipment do you expect to move to in five years? How will technology evolve? How will your operational needs change?

For instance, maintenance workers may need more skills related to automation. Or, for some jobs, a higher level of troubleshooting and critical thinking may be needed.

Then you take the delta between the two models and develop a plan for your future workforce.

A bonus is that 13 percent of manufacturers say the increased ability to attract younger talent is a powerful benefit of digital technology. And offering training in new advanced technology is a great recruiting tool.

The companies that use competency models to strategically build training and development programs to meet the skills of the future are the ones that will retain their competitive advantage for years to come.

We are here to help.

Tags: "3D printing", "augmented reality", automation, cobots, competency, "competency models", manufacturing, "Manufacturing in the New Industry 4.0 Era Survey", robotics, "Smart Manufacturing: Building Talent to Accelerate a Digital Transformation", SME, technology, "Tooling U-SME", training, workforce