It seems like hiring challenges are dominating the news cycles these days but the labor shortage in manufacturing is having an especially strong impact. A recent study shows that there could be as many as 2.1 million unfilled jobs in the industry by 2030.
Explaining the Labor Shortage in Manufacturing
Like many industries, manufacturing was negatively impacted by the COVID-19 pandemic, with about 1.4 million U.S. manufacturing jobs lost and only about 63% of them recovered by 2020. Aside from COVID, many baby boomers (2.6 million) have retired or are planning to, amplifying the issue.
Unfortunately, the labor shortage in manufacturing began even before the coronavirus impeded production and supply chains, meaning what would have been a challenging issue is now dire for some organizations. The impact of the labor shortage in manufacturing is felt far beyond the bounds of the industry; the manpower isn’t in place to process and transport imports. Delays and shortages are troubling consumers and businesses alike, nationwide.
Manufacturing Data Analytics is Part of the Solution
Solving the labor shortage in manufacturing will require multi-faceted approaches. One key piece of the puzzle is advancing data science in manufacturing production and operations management.
Not only does manufacturing data analytics streamline processes, create efficiencies, and maximize your existing pool of talent, it helps the industry attract new workers who are interested in more technological positions. Below are just some of the ways manufacturing data analysis fits into the labor shortage solutions.
For some people, introducing technology into manufacturing means introducing robots into your operational systems. However, there is a less visible but arguably more powerful shift happening thanks to Industry 4.0 and the Industrial Internet of Things (IIoT). That shift is launching toward harnessing the power of manufacturing big data which offers real time views of current systems and inputs to find efficiencies and maximize resources.
IIoT primarily collects time series data, which is required to uncover insights using manufacturing data analytics. When used correctly, time series data—and the information it contains—can mean higher productivity and improved outcomes within your current labor force. Ultimately, consistent, accurate, real-time data empowers you and your team to make the best decisions for production and operations management.
Faster Response Time
The beauty of manufacturing analytics is that it can help automate historically manual, time-consuming tasks. That means shifting the number crunching to software so your human team members are free to focus on keeping processes on track and running smoothly instead of tracking down a potential problem.
Using data science in manufacturing can alert you to when an anomaly occurs, help you understand how significant it is, and let you know what caused it so you can correct the issue quickly. Decreasing time to identify and resolve issues within the manufacturing process means maximizing time on task for the team members you already have, reducing the need for as many new hires.
Solve Problems Before They Occur
Of course, quicker response times to resolve an issue still means there was likely an impact to operations. By leveraging predictive analytics in manufacturing, you can stay ahead of problems and prevent downtime. Essentially, manufacturing data analysis software like Sightline EDM can shift you from being reactive to proactive by alerting you to when a machine is likely to need maintenance or when you could hit maximum capacity so you can take corrective actions before the issues arise. With the addition of machine learning and AI, your predictions will get better and stronger over time, layering efficiencies on top of already efficient processes.
Protect Your Current Workforce
In addition to hiring new team members, a key part of solving the labor shortage in manufacturing means protecting your current team. Safety is likely a constant topic in your organization, and it’s a vital issue to address. Manufacturing data analytics tools can help. Simply monitoring manufacturing data can help highlight recurring areas where safety issues arise. By using predictive analytics in manufacturing, fewer maintenance emergencies appear, which means fewer risky situations your employees have to be in.
Maximize Efficiency and Human Resources With Sightline
When it comes to leveraging manufacturing data in production and operations management, Sightline EDM has all of the core features to empower you to do the most with the team you have. Some what you can expect includes:
- Automated capacity planning to predict labor or production limits, identify bottlenecks, and prevent downtime across facilities and systems
- Custom reports for anomalies and root cause analysis of the problem even across multiple facilities, machines, and processes within minutes
- AI and machine learning so you more accurately evaluate the impact an anomaly could have on your business and take action quickly
- Documentation support and solutions so you can use past experiences to improve future corrective action and share them across teams, equipping employees to solve problems even if they have never encountered them before
Manufacturing data analytics software is an easy step you can take toward addressing the impacts of the labor shortage in manufacturing on your organization.
Book a conversation with an EDM expert to learn more about how Sightline can help maximize your production and operations management.
What is the labor shortage in manufacturing?
Due to the impacts of the global pandemic and baby boomers retiring, there could be 2.1 million unfilled jobs in the industry by 2030, which in turn impacts supply chains and consumer access to necessary products and services.
How can manufacturing data analytics help?
By streamlining processes, creating efficiencies, and maximizing existing team members’ productivity.
What manufacturing big data solution can help me?
Sightline EDM can automate capacity planning, create custom reports, and enable knowledge-sharing and documentation to maximize production and operations management.