Posts in category: Reporting and Business Intelligence

What is labor productivity and why should you start measuring it?

Labor productivity shows how much value your company can create in a given period. Whether it’s the number of units produced, completed orders, or the volume of services delivered, it always answers the same essential question: What is the output compared to the time, people, and technology required?

That’s why productivity is one of the most important indicators of efficiency. If it’s low, the company must invest more energy, time, and money to achieve the same result, which translates into higher costs, lower competitiveness, and weaker business outcomes. On the other hand, increasing productivity allows you to achieve more with what you already have—without unnecessary investment in new machines or the need to hire more people.

There are various ways to measure productivity. These include metrics such as GDP per employee, GDP per hour worked, output per worker, or machine utilization efficiency (OEE). The right metric depends on the type of production and the goals you aim to achieve.

Since proper measurement is the foundation of all improvement, we’ll cover this topic in more detail in a dedicated article, “How to Calculate Labor Productivity.”

Labor productivity in the EU and Slovakia

Looking at the numbers, Slovakia has long lagged behind the EU average in terms of labor productivity. According to Eurostat, the Slovak economy reaches only about 70 to 80% of the average labor productivity in the EU. This means the average Slovak worker produces less value per hour than their counterpart in Western Europe.

For manufacturing companies, this is not only a warning sign but also a huge opportunity. The productivity gap isn’t necessarily due to a lower quality workforce. More often, it’s the result of insufficient use of technology, a lack of automation, poor production planning, or missing reliable data for decision-making. Simply put, Slovak firms often work more, but achieve less.

Common problems in companies that don’t measure productivity

If a company doesn’t measure labor productivity or relies only on estimates, the same scenario tends to repeat itself. Production may be running, but results don’t match the effort. Everything might look fine on the surface, but beneath that, small inefficiencies accumulate into major losses.

❌ 1. Unclear Downtimes

Without precise measurement, no one knows exactly when and why machines stop, how long downtimes last, or what their real impact is. Planned, unplanned, and short downtimes are accepted as “just part of the job” instead of being systematically reduced or eliminated.

❌ 2. Rapidly Rising Costs Without Clear Cause

Unnecessary waiting, material waste, overproduction, inefficient production cycles, and reduced machine speeds all increase costs, even when no one seems to be doing anything wrong. If these losses aren’t tracked and analyzed, they can’t be identified, quantified, or strategically reduced.

❌ 3. Invisible Quality Losses

Without consistent measurement, only the biggest failures are reported, while smaller but frequent errors during startup or in-process often go unnoticed. These can add up to significant losses. If they aren’t tracked, they won’t be addressed—and remain hidden costs.

❌ 4. Lack of Transparency in Production Processes

If performance, downtimes, and other key data are recorded manually (on paper or in spreadsheets), the outputs are often inaccurate, delayed, and don’t reflect real-time conditions. There’s no clear view of what’s happening on the floor, making it hard to respond quickly. This lack of agility is a serious disadvantage today.

❌ 5. Ineffecient Reporting and Intuition-Based Decisions

Without reliable performance data, decisions are made based on estimates, experience, or gut feeling. The result is often poor planning, unbalanced workloads, unnecessary stress, and ultimately, increased losses.

These problems result in tangible long-term consequences:

• Lower efficiency
• Higher operating costs
• Reduced competitiveness at home and abroad

How to increase productivity without unnecessary investments

The good news is that higher productivity doesn’t necessarily mean buying new machines, hiring more staff, or pushing people to work faster at the cost of quality. In many cases, it’s the opposite. The greatest impact often comes from better use of what you already have. The key is to know where losses arise, why they happen, and how to reduce or eliminate them.

✅ 1. Start by measuring productivity precisely

The foundation of improvement is accurate data. Without measurement, you can’t know where losses occur or how much they impact your performance. In many cases, productivity increases by 10 to 15% immediately after measurement begins—a phenomenon known as the “halo effect,” where people naturally perform better because they know their output is being tracked.

✅ 2. Automate data collection and eliminate manual errors

If you’re still recording downtimes, breakdowns, and other data manually, you’re leaving room for errors and delays. The solution is automated data collection from machines, production lines, and sensors, using IIoT systems or traditional SCADA/MES platforms. These provide real-time, accurate insights into what’s happening in production.

✅ 3. Focus on uncovering hidden losses

Wasted time, frequent interruptions, poor planning—these are common but often overlooked productivity killers. The “Six Big Losses” model helps categorize these losses into availability, performance, and quality. What makes this model powerful isn’t just naming the six main losses, but assigning clear reduction goals to each. Some can be eliminated completely, while others should be minimized.

✅ 4. Optimize production planning

When you have real-time visibility into machine capacities, line status, and resource availability, you can align production with actual demand—avoiding overloads and downtimes. Integrating MES with ERP or BI systems lets you manage production, maintenance, logistics, and inventory as a unified, data-driven process.

✅ 5. Use visualization and clear reporting

Data is only useful when it’s accessible and understandable. Interactive dashboards in tools like Ignition or Power BI give managers and line operators instant insights into production status, performance, and the root causes of downtime. These insights must be available not just at weekly meetings, but in real time and to everyone who needs them.

✅ 6. Make productivity improvement an ongoing effort

A common mistake is to treat productivity improvements as one-time projects. Successful companies know it’s a continuous process. Regular performance reviews, KPI tracking, and strategic adjustments help maintain improvements and adapt quickly to new challenges.

Labor productivity isn’t about making people work more, but about empowering them to work smarter. To reduce downtime, prevent overloads, and make decisions based on real data—not guesses. That’s why measuring productivity isn’t just another metric. It’s a tool for better decisions, sustainable growth, and a stronger operation.