Why is HR Analytics in Manufacturing Essential for 2025?

Workforce Challenges in Manufacturing: How HR Analytics Solves Them

As a manufacturer, you might be dealing with plenty of workforce management challenges. Things like labor shortages, talent acquisition and retention, and rising compensation costs can become a real headache. The stats aren’t reassuring as well:

• Labor shortages. About 61% of manufacturers struggle to fill critical labor gaps, and 69% say shortages directly impact their ability to meet production needs. A 2024 Deloitte study warns that if these issues aren’t addressed, 1.9 million manufacturing jobs could go unfilled over the next decade.

• High employee turnover. Nearly 42% of manufacturers surveyed by the UKG Workforce Institute say turnover has increased year-over-year. Replacing a single skilled frontline worker can cost $10,000 to $40,000, and 56% of manufacturers state that turnover has a moderate to severe impact on their bottom line.

• Rising compensation costs. The Employment Cost Index for total compensation in manufacturing continues to rise, with a 3.8% increase year-over-year as of September 2024. These costs add pressure to already tight margins.

Besides these top challenges, you may be grappling with human resource planning complexities — failing to ensure you have the right number of skilled employees at the right time. Even worse, you may have to tackle absenteeism when your employees don’t show up at work completely.

But how exactly does HR analytics for manufacturing help? Here are just a few solutions it offers:

• Predictive workforce planning. Using AI analytics, you can analyze production demand and workforce availability to optimize workers’ schedules accordingly.

• Turnover risk analysis. AI and machine learning models help you identify employees at risk of leaving by looking into their behavior, attendance, and overall satisfaction. With these insights, you can come up with engagement and retention strategies.

• Cost optimization. AI-powered workforce analytics assists in labor cost reduction by letting you reduce overtime and close unnecessary positions.

Want to learn how other software solutions can help your company thrive? Explore the small business process automation benefits we’ve outlined in our latest post.

Why Custom AI-Powered HR Analytics is the Future of Manufacturing HR

Now that you know the challenges and ways analytics can solve them, there’s one more thing you need to learn. Not all AI solutions are the same.

Off-the-shelf tools indeed help you track basic workforce metrics. Yet, they often fall short in handling complex manufacturing workflows. That’s where custom AI analytics development might be more beneficial — offering solutions that fully match your operations. In particular, it provides:

• Comprehensive analysis. Generic HR tools scratch the surface where AI dives deep. You can integrate custom analytics solutions with all your existing data sources — from HRIS to production systems and even industrial Internet of Things sensors on the shop floor — and get a clearer picture of your workforce. 

• Proactive management. Off-the-shelf tools are often reactive — meaning you can respond to events only after they happen. Custom AI-powered business process management software development, in turn, lets you use predictive analytics to forecast labor shortages, absenteeism, and turnover in advance.

• Improved employee experience. Using AI-powered HR analytics in the manufacturing sector also lets you personalize employee engagement. This becomes possible with performance tracking, individual preferences analysis, and feedback gathering. Ultimately, you ensure your employees feel valued and motivated — improving retention rates.

Make your workforce more productive with AI

From demand forecasting to employee retention, our AI-powered solutions transform manufacturing HR. See how it works!

Must-Have Tech & Features for AI-Driven HR Analytics

Once you’re ready to adopt AI-powered manufacturing HR analytics, choose the right technologies and features. Here are some of the must-haves:

• Data integration platform. This will be the foundation of your analytics system that connects all data sources in one place.

• Machine learning algorithms. These are going to be the brains of the operation. They’ll analyze data to predict workforce trends, helping your HR teams make proactive decisions.

• Natural language processing. This feature will come in handy in case you need to analyze employee feedback and survey responses quickly.

• Real-time monitoring. This will help you track employee productivity, attendance, and performance in real time to optimize scheduling and labor costs.

• User-friendly dashboard. You’ll need this feature to view the insights from AI clearly. The dashboard should provide visualizations, reports, and alerts.

On top of the features, you’ll also need to decide on the types of HR analytics you’re going to use. Here are the main ones: 

To make sure that implementing HR analytics in the manufacturing company is the right move, take a look at Siemens. They used analytics tools for predictive workforce planning. In particular, the company handled competitor benchmarking as well as emerging job roles and skill gap analysis.

AI Analytics in HR: How to Get Started

You’ve seen the benefits — comprehensive analysis, proactive management, and better employee experience. Now, let’s look at how you can implement HR analytics in the manufacturing sector. Here are a few simple steps:

1. Evaluate your HR challenges. Determine your key workforce pain points — whether turnover, labor shortages, or training gaps.

2. Set clear implementation goals. Define measurable outcomes, such as reducing turnover by 20%, increasing manufacturing efficiency, or optimizing scheduling.

3. Partner with the right experts. Collaborate with experienced specialists to develop HR analytics software for manufacturing or choose a suitable off-the-shelf solution, as well as get valuable digital transformation insights.

4. Integrate with existing systems. Make sure your analytics solution connects with your current HR software and other workforce management tools.

5. Train your team. Educate your HR staff on how to use the new AI analytics solution for smarter decisions.

 Best Practices to Follow

When implementing HR analytics in the manufacturing industry, you can make the process smoother by following several helpful tips. Here they are:

• Make sure your data is clean since AI models rely on high-quality data for accurate predictions.

• Choose solutions that are compatible with your existing HR software and workflows.

• Start with smaller projects and scale gradually after your pilot solutions succeed.

Why Choose Us for Implementing AI-Powered HR Analytics?

Bits Orchestra has over 8 years of experience in AI and ML development. With such a background, we know how to deliver HR analytics solutions that tackle high turnover, HR automation complexities, employee training and development, along with numerous other challenges.

Particularly, we work with the following industries:

In case you want to join over 60 of our satisfied clients or simply learn more about business automation solutions and AI-powered analytics, feel free to explore our blog — or contact us right away.