The Learning Curve Theory: Types, Benefits, Limitations (2023)

learning curve

When new processes, tools, or technologies are introduced into the workplace, employees may experience a steep initial learning curve.

Typically, most learners experience a learning curve at the beginning of a new experience, and that incline tapers off as they gradually learn more about the subject matter. 

The idea behind the learning curve concept is simple: the more an employee practices something, the better they become at it. This translates to lower cost and higher output in the long term.

What Is the Learning Curve Theory?

While the term “learning curve” came into use in the early 20th century, Dr. Hermann Ebbinghaus described this theory in 1885. Ebbinghaus tested his memory over various periods and came up with a visual representation of how learned information fades over time. The Ebbinghaus Forgetting Curve demonstrates how information is lost over time when there is no effort made to retain it.

Memory retention and Forgetting Curve

Later, Arthur Bills described the learning curve in his paper “General experimental psychology.” He says, “the learning curve is a graphical device for picturing the rate of improvement in terms of a given criterion of efficiency, as a result of practice.”

The learning curve theory is based on the concept that there is an initial period where the amount invested in learners is greater than the return. However, after overcoming the learning curve, the return is much greater than the investment. The idea here is that the more an employee practices a task, the better they become at it, which translates to a lower cost of training and higher output over time. The learning curve model helps track training progress, improve productivity, and predict learners’ performance and improvement over time.

However, the relationship between the amount of time spent practicing an activity, and the overall performance is not linear. There will always be specific periods for each activity where a small amount of practice would yield massive improvement in output or where even minor improvements may require many hours of work. This variance in the relationship between practice and proficiency over time is known as the ‘learning curve.’

What Is a Learning Curve?

The learning curve is defined as the correlation between a learner’s performance on a task or activity and the number of attempts or time required to complete the activity.

Learning curve formula -> Y = aXb


  • Y = average time over the measured duration
  • a = time spent to complete the task the first time
  • X = total amount of attempts completed
  • b = slope of the function
Learning Curve Formula
Related Resources

Types of Learning Curve

Here are some common types of learning curves:

1. Diminishing returns

In the diminishing-returns curve, the rate of progression increases rapidly at the start of learning and decreases over time. 

Diminishing returns

The graph above graph describes a situation where a task or activity may be easier to learn, initially resulting in a fast and rapid progression. Activities that follow a diminishing returns learning curve are more straightforward when measuring and predicting how the performance and output of the workforce will change over time.

In terms of decision-making, this result means that the employee is performing well, but you need to keep the costs down after the initial plateau.

2. Increasing returns

In the increasing-returns curve, the rate of progression is slow at the start and rises over time until full proficiency is achieved. 


increasing returns

This graph describes a situation where a complex task is learnt with the learning rate being prolonged initially.

In terms of decision-making, no action items are required here, as the initial cost of slow learning is quickly returned upon reaching the high-efficiency phase. However, if the rest of the data shows that the task should not take very long for employees to learn, this graph is taken as an indication to modify your employee training method.

3. S-curve

This increasing-decreasing return learning curve model is the most commonly cited learning curve known as the “S-curve” model.


The bottom of this curve indicates slow learning as a learner works to master the skills and takes some time to do so. The latter half demonstrates that the learner is now taking less time to complete a task and has become proficient in the skills. At this point, the learner’s performance will level off, after which only slight increases can be expected over time.

This type of learning curve may be encountered when a new productivity tool is introduced to employees.

If the plateau is closer to the X-axis, it represents a highly efficient performance. On the other hand, if the plateau is closer to the top half of the graph, performance may not be as efficient. In terms of decision-making, take a closer look at the training method and other variables that impact the cost of ongoing performance in the plateau phase.

4. Complex curve

The complex learning curve represents a more complex learning pattern and reflects more extensive tracking. 

complex curve

This suggests that the task being measured is challenging to learn and takes a certain amount of practice before an employee becomes proficient. 

  • Stage 1 – indicates a slower initial learning phase.
  • Stage 2 – shows an increase indicating that the learner is becoming proficient in the skill.
  • Stage 3 – indicates that the learner is plateauing in his proficiency once they have mastered the skill.
  • Stage 4 – represents that the learner is still working on improving the skill.
  • Stage 5 – represents the point at which the skill becomes automatic, muscle memory for the learner, also known as “overlearning.”

The complex learning curve model looks different for each activity, individual, or group. Learners encounter multiple peaks and plateaus when learning tasks with complex learning curves.

For decision-making, look for ways to improve training or reduce costs by hiring candidates who already have the experience required to reach peak efficiency for this task.

The learning curve model helps monitor various aspects of company performance and identify areas that need improvement. It provides insights into employee training and performance, but some limitations exist. Let‘s examine some key advantages and disadvantages of the learning curve model.

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Advantages of the learning curve model

The learning curve model helps monitor various aspects of company performance and identify areas that need improvement. It provides insights into employee training and performance, but some limitations exist.

Here are a few of the advantages of the learning curve model for organizations:

  1. Better understand employee progress – Comparing different learning curves helps understand an employee’s progress while learning a particular task, allowing companies to make training adjustments accordingly. 
  2. Strategic planning – The learning curve helps build strategic plans to improve the output of employees or an entire department.
  3. Create a learning culture – The learning curve helps motivate a workforce by creating a culture of ongoing learning and training evaluation.
  4. Decision making – The learning curve helps identify trends for making viable business-related decisions and better forecasts for the future.
How to Build a Corporate Learning & Development (L&D) Strategy in 2022

Disadvantages of the learning curve model

Here are a few of the disadvantages of the learning curve model for organizations:

  1. Cannot accurately predict future curve – The learning curve recognizes current skills but cannot predict the future with complete accuracy.
  2. Misleading data – The learning curve is influenced by variables such as time, previous experience, quality of training, etc. As a result, tracking only one of these variables might result in misleading data.
  3. Creates differences – Some employees are more skilled than others at specific tasks, giving them an advantage. This difference is displayed while comparing the learning curves, creating unnecessary hassles and judgments.

8 Tips To Flatten The Learning Curve For Effective Employee Training

Here are 8 effective tips for organizations to use the learning curve for designing effective employee training programs.

1. Define your unit of output

Set long and short-term measurable outcomes to evaluate employee performance and training effectiveness. Make the purpose of your training program clear by identifying what employees are expected to accomplish by the end of training.

2. Efficient onboarding

To help a new hire acquire competence and remain confident in their role, be sure to create an efficient onboarding process. A strong onboarding process provides newly hired team members with the right information, training, and tools during their first few weeks at a company, making their learning curve more productive and much shorter in the future.

3. Personalized training

Create personalized learning programs with training content tailored according to individual job roles and learning types. Personalized training boosts employee engagement, improves training effectiveness, and helps flatten the learning curve.

4. Make informed decisions

If the data from the learning curve shows that the current training process is not working, explore alternative employee training methods and implement other modifications to fine-tune your training programs. It might take a few rounds of trial and error to find the right change that improves performance.

5. Mentor coaching

Often no matter how well a formal employee training program is structured, it does not impart all of the knowledge and information employees need to perform their roles effectively. This is when real-life coaching from an experienced professional – a supervisor, mentor, or veteran employee – can be effective to acquire knowledge in real-time.

6. Invest in training technology

More organizations are leveraging employee training software to implement effective training with personalized learning content that uses user analytics to help shorten the learning curve across employees. 

There are a few different types of employee training software that can be leveraged for creating and managing employee training programs.

  • Corporate LMSCorporate LMS tools help L&D teams identify and assess both individual and organizational learning goals, build learning content, track progress towards meeting those goals, and collect data for supervising and improving the learning process. 
  • Digital Adoption Platform – A digital adoption platform (DAP) integrates with existing digital tools to provide automated, personalized training – in the flow of work. DAPs assign each learner a contextual task list containing interactive walkthroughs and other in-app content based on a learner’s profile. Walkthroughs are step-by-step prompts that guide users through certain tasks or processes.
  • Video Training SoftwareVideo training software enables creating, publishing, sharing, training videos – as well as analytic tracking features to measure the rate of training and learning progression. Training videos are created to provide knowledge and information for employee onboarding, compliance training, software education, etc.

7. Establish time frame

To shorten the learning curve, you must establish a time frame for achieving the set of desired outcomes to understand whether or not your training methods are providing the expected results. For example, new hires should be able to create and manage leads and accounts on a company’s CRM platform after completing a 3-week CRM training program.

8. Continuous monitoring

The learning curve theory shouldn’t only be applied during times of change or when training difficulties arise; instead, monitor the learning curve year-round. Continuous monitoring uncovers problems as soon as they appear, allowing you to easily correct and modify your approach as required.

Invest in effective training software to maximize the learning curve

Invest in Digital Adoption Platforms such as Whatfix to augment your training programs by enabling interactive, hands-on learning directly within a software application or digital process. DAPs eliminate the gap between theory and practice, which automatically engages employees’ memory and accelerates learning.

DAP promote effective employee training by:

  • In-app guidance: DAP gives employees access to all relevant information, resources, documentations, and workflows they need to learn a new process or application. 
  • Interactive walkthroughs: Guides users step-by-step through every task or process within an application. Interactive walkthroughs are used for customer and employee onboarding and training programs to encourage a higher level of employee understanding and engagement.
  • Contextual self-help: DAP provides contextual support in real-time without employees having to raise support tickets and wait for a resolution for their queries. Contextual help is provided directly inside the software and the guided steps can be immediately applied without having to break from the current task or search for answers online.
  • Microlearning: DAP enables microlearning by bringing in short and concise snippets of training which are conducive to how the human brain remembers information.
  • Learning analytics – DAP helps companies identify trouble spots or blind spots in employee learning. The powerful analytics tool monitors user analytics to see whether employees are getting stuck and creates additional walkthroughs or self-help articles if needed.
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