Learning Curves

Learning Faster to Improve Efficiency

Also Known as Experience Curves

Learning Curves - Learning Faster to Improve Efficiency

© Veer
Tom Wang

Everyone's experienced learning curves in motion.

Cast your mind back to when you first began a new job or project. Do you remember grappling with the basics, and taking a long time to get used to new processes and procedures?

Several months down the line, you're so adept at the job you wonder why you ever struggled in the first place.

There is an explanation for this: if you find that your performance improves with experience, and it takes less time and effort to complete a task after you've done it a few times, then you've experienced the "learning curve" in action.

This learning effect was first described by aeronautical engineer T. P. Wright in 1936, as he studied the time it took to produce airplane parts. He found that as workers gained experience, they were able to produce the parts faster. As workers' experience grew, there was a continuous decrease in the time needed to complete a task. However, the time savings eventually flattened out at a certain point. This indicated that learning was "complete."

This is an important concept for business. You can build on this principle so it has a positive impact on the workplace, because working more efficiently saves time and money.

When you understand the learning curve, you can use it to forecast your resource needs more accurately over time. It also helps you prepare for the initial period after you've introduced changes, when productivity tends to be lower than desired. For example, if you install new software, you can probably expect efficiency rates to be low at first. Then, as people use the software more, their productivity increases over time – until their learning rate reaches a plateau.

You can also use the learning curve to identify and establish improvements in processes and procedures. In a manufacturing context, for example, as staff learn to do their jobs more quickly and efficiently, this is likely to lead to qualitative improvements in the way products are designed and engineered.

Business consultancy The Boston Consulting Group studied the learning curve, and concluded three things:

  1. The time needed to perform a task lessens as a task is repeated.
  2. As more units are produced, the amount of improvement decreases.
  3. The rate of improvement is consistent, and you can create a graph to use as a prediction tool.

Understanding the Tool

The learning curve can be illustrated in a graph showing the time it takes to produce a unit on the y-axis, and the number of units produced on the x-axis (see below). You then get a curve with a downward slope (figure 1).

Learning Curve Diagram

The slope of the line shows the rate of learning. The higher the rate of learning, the steeper the slope. Figure 2 (below) shows a higher rate of learning than figure 1 – in other words, the time it takes to produce each unit decreases at a faster rate.

There is a misperception that the term 'learning curve' implies a positive slope. Some people may talk of a steep learning curve when describing a task that's hard to learn at first. Mastering this task then produces huge gains. However, an actual learning curve is the negative, or inverse, slope seen above.

The formulas used to create the curve are helpful when you want to forecast how production times and costs will decrease over time as you start making new products. However, in more general business situations, there's usually no real benefit to determining exact numbers for activities such as producing a new weekly report, or calculating month-end figures.

Applying the Learning Curve

Other ways of speeding up learning include developing effective training programs, and ensuring that adequate support is available.

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The learning curve can also help you and your team prepare for the effects of change. When you use the learning curve to describe the effect on efficiency, you can help people deal with the difficulties of learning something new. It also helps workers understand why their efficiency gains slow down over time.

For example, sometimes teams become negative when they see their productivity gains decrease after an initial period of huge increases. Using learning curves, you can explain in advance what they should expect.

If you've introduced new systems or technology, then it pays to invest in an extensive training program, and ensure that adequate support is available. This will help speed up workers' rate of learning.

It is also a good idea to create a project team, with a brief to identify and capture the benefits and improvements gained by workers learning quickly. This team can then make sure that these improvements become embedded in everyone's way of working.

This is also a great time to emphasize why continuous improvement is so important to a healthy organization. There's a limited amount of efficiency that you can gain from one new initiative. To keep moving forward, you need to look constantly for new ways of doing things.

Limitations of the Learning Curve

The learning curve idea assumes that taking less and less time to do something is always a good, and possible, outcome. Typical applications are manufacturing, construction, and document processing. Sometimes, however, the learning curve doesn't apply, especially if the following is true:

  • Production is irregular.
  • Production quantities are small.
  • Products are highly customized.

In situations like these, workers can't usually benefit as much from learning and experience. That's because each situation presents a new learning challenge, and people don't necessarily repeat the same tasks.

Another point to consider is the cost of investment. Before using the learning curve to justify implementing a change, make sure that your savings from faster learning will be higher than the cost of the investment. Doing something faster may be better – but only if there's a financial benefit associated with it.

Key Points

Learning curve theory is mainly about learning by doing. Mathematical models have shown that experience gained over time leads to improved performance, so costs may decrease as production progresses. This helps you gain a competitive advantage by finding ways to speed up the learning within your organization. To take advantage of these benefits, look for better processes – and implement those processes as soon as you can.