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Unlock This CourseImagine you work in a chocolate factory. Yesterday, 10 workers made 1,000 chocolate bars. Today, the same 10 workers made 1,200 chocolate bars. Which day were the workers more productive? This is exactly what productivity calculations help us figure out!
Productivity is one of the most important measures in business. It tells us how efficiently a business is using its resources - especially its workers and time. When productivity goes up, businesses can make more products with the same resources, which usually means more profit.
Key Definitions:
Higher productivity means businesses can produce more with the same resources. This leads to lower costs per unit, higher profits and the ability to compete better with other businesses. For workers, higher productivity often means better wages and job security.
The most common productivity calculation is labour productivity. It's surprisingly simple to work out and once you understand the basic formula, you can apply it to almost any business situation.
The basic formula for labour productivity is:
Labour Productivity = Total Output ÷ Number of Workers
Or sometimes: Labour Productivity = Total Output ÷ Total Hours Worked
Let's break this down with a simple example. Sarah's Bakery employs 5 bakers who produced 500 loaves of bread in one day.
Calculation: 500 loaves ÷ 5 workers = 100 loaves per worker per day
This means each worker produced an average of 100 loaves. This number helps Sarah understand how efficient her bakery is and compare it to other days or other bakeries.
If those 5 bakers worked 8 hours each (40 hours total), the hourly productivity would be: 500 loaves ÷ 40 hours = 12.5 loaves per hour
Per worker calculations help compare different sized teams. A team of 10 making 800 units has the same productivity as a team of 5 making 400 units (80 per worker)
Productivity figures let you compare performance across different time periods, departments, or even different companies in the same industry
Let's look at some practical examples of how different businesses calculate and use productivity measurements.
TechnoWidgets makes electronic components. In January, their 20 workers produced 4,000 components. In February, the same 20 workers produced 4,800 components after receiving new training.
January productivity: 4,000 ÷ 20 = 200 components per worker
February productivity: 4,800 ÷ 20 = 240 components per worker
Improvement: (240 - 200) ÷ 200 × 100 = 20% increase in productivity
While labour productivity is the most common, businesses use several different ways to measure how efficiently they're working:
How much output a machine produces in a given time. For example, a printing press might produce 1,000 leaflets per hour. This helps businesses decide when to upgrade equipment.
Total revenue divided by number of employees. A shop with £100,000 revenue and 10 employees has £10,000 revenue per employee. This shows the financial productivity of workers.
Let's work through another example. FastFood Express has the following data:
Productivity calculations:
Tuesday was the most productive day, even though they served fewer total customers. This shows why productivity calculations are more useful than just looking at total output.
Understanding what makes productivity go up or down helps businesses make better decisions. Here are the main factors that affect how productive workers can be:
Better trained workers can usually produce more in the same time. Investing in training often leads to higher productivity.
Modern, well-maintained equipment helps workers produce more efficiently. Old or broken equipment slows everyone down.
Happy, motivated workers tend to be more productive. Good management, fair pay and pleasant working conditions all help.
Green Gardens wanted to improve productivity in their plant potting department. They measured baseline productivity: 6 workers potting 300 plants per day (50 plants per worker).
They then introduced new potting tools and gave workers training. After one month:
New productivity: 6 workers potting 420 plants per day (70 plants per worker)
Improvement: 40% increase in productivity
The investment in tools and training paid for itself within three months through increased output.
Calculating productivity is only useful if businesses act on the information. Here's how smart businesses use productivity data:
If productivity suddenly drops, it might signal problems like equipment failure, staff shortages, or quality issues. If productivity is consistently low compared to competitors, it might be time to invest in improvements.
Businesses use productivity data to set realistic but challenging targets. If current productivity is 50 units per worker, a target of 55 units might be achievable with some improvements.
Productivity calculations also help with important business decisions like:
Businesses often compare their productivity with industry averages. If a car factory produces 10 cars per worker per month, but the industry average is 15, they know they need to improve.
High productivity means nothing if quality suffers. A factory might produce 1,000 items per day, but if 200 are defective, the real productivity is much lower. Always consider quality alongside quantity when measuring productivity.
The best way to understand productivity calculations is to practice with different examples. Try calculating productivity for different scenarios and think about what the numbers tell you about the business.
Remember, productivity isn't just about working faster - it's about working smarter. The most productive businesses find ways to produce more value with the same resources, whether that's through better training, improved processes, or smart use of technology.