The Learning Curve Theory: Types, Benefits, Limitations (2024)
- Published: April 14, 2022
- Modified: January 11, 2024
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 costs 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.
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
Where:
- 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
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.
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.
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.
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.
Advantages of the learning curve model
Here are a few major advantages of the learning curve model.
1. Cost reduction
As employees or processes become more experienced and efficient, the time taken to complete tasks often decreases, leading to a reduction in labor costs. Furthermore, with experience, there’s a better understanding of how to optimize resource usage and minimize waste, which also contributes to lower production costs.
2. Improved quality
With increased experience, workers develop a better understanding of their tasks and processes. This enhanced knowledge and skill lead to a decrease in errors and defects, resulting in higher quality products or services. The learning curve allows for the refinement of techniques and processes, enhancing overall quality.
3. Enhanced training and skill development
The Learning curve model emphasizes continuous improvement and learning. As workers become more skilled, they also become more valuable assets to their organization. This model also supports the idea of ongoing training and skill development, ensuring that employees are always up-to-date with the latest techniques and technologies in their field
4. Predictable performance
Over time, the learning curve model helps in establishing predictable patterns of performance improvement. This predictability is valuable for planning and forecasting. Organizations can use historical data to predict how long it will take for new employees to become proficient or for the implementation of new processes to become fully efficient.
5. Risk mitigation
With experience, organizations learn to identify and avoid potential risks and pitfalls. The learning curve allows them to develop strategies and contingency plans based on past experiences. This knowledge helps in mitigating risks associated with new projects or the introduction of new processes, as the organization becomes more adept at foreseeing and managing potential issues.
Disadvantages of the learning curve model
Here are a few major disadvantages of the learning curve model.
1. Limited applicability
The learning curve model is most effective in environments where tasks are repetitive and consistent over time. In industries or job roles where tasks are highly variable or require significant creative or adaptive work, the benefits of the learning curve may be less pronounced. For instance, in artistic or research-based fields, the notion of efficiency and productivity improvement over time may not apply in the same way as in manufacturing or routine service tasks.
2. Initial inefficiencies
At the beginning of the learning curve, there is often a period of lower efficiency and higher costs. This is because employees are still acquiring the skills and knowledge needed to perform their tasks effectively. During this phase, errors and rework may be more common, leading to higher initial costs and potentially slower production or service times. For organizations that require quick results or have tight budgets, these initial inefficiencies can be a significant drawback.
3. Inflexibility
As employees or processes become more efficient at specific tasks, there can be a tendency towards rigidity. Workers may become so specialized in their current methods that they resist changes or innovations. This inflexibility can be a disadvantage in rapidly changing industries where adaptability is key. Furthermore, a strong focus on current processes and efficiencies might discourage exploration of potentially more effective methods or technologies, leading to a stagnation in innovation.
How to Flatten the Learning Curve to Enable Employees
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 LMS – Corporate 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 Software – Video 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.
Examples of the Learning Curve Theory
The learning curve theory, fundamentally, posits that as individuals or organizations perform a task repeatedly, they become more efficient at it over time. This concept can be applied to various fields, such as project management, employee training, technology adoption, healthcare, and medicine. Let’s explore how the learning curve theory applies to each of these examples:
1. Project management
In project management, the learning curve is observed as project teams become more proficient with repeated tasks or similar projects. Initially, a project may take longer and involve more resources due to unfamiliarity or unanticipated challenges. However, as the team gains experience, they develop more efficient processes, better problem-solving skills, and a deeper understanding of the project requirements. This leads to reduced time and cost in subsequent projects.
2. Employee training
When new employees are trained, there’s often a steep learning curve at the beginning. They might take longer to complete tasks and require more guidance. However, as they gain experience and knowledge, their productivity increases. The learning curve in this context can be influenced by the quality of training programs, the complexity of the job, and the individual’s learning capabilities.
3. Technology adoption
Introducing new technology in an organization typically involves a learning curve. Initially, employees may struggle to adapt to new systems or software, leading to reduced productivity and potential resistance to change. Over time, as they become more familiar with the technology, their proficiency improves, leading to increased productivity, innovation, and often a competitive advantage.
4. Healthcare and medicine
In healthcare, the learning curve can be seen in various aspects such as surgical procedures, diagnosis methods, and patient care techniques. For instance, surgeons may take longer to perform a particular procedure initially, but as they repeat it, their speed and efficiency improve, often leading to better patient outcomes. Similarly, healthcare professionals become more adept at using new medical technologies or treatment protocols with experience.
With a digital adoption platform (DAP) like Whatfix, organizations enable employees to overcome steep learning curves that come with complex software applications and digital processes through role-based in-app guidance and real-time support.
With a DAP, organizations can enable their employees with:
- In-app guided Flows that walk employees step-by-step through complex CRM, HCM, ERP, or any application workflow.
- Onboarding tours and Task Lists that enable employees to reduce their time-to-proficiency on essential tasks and software.
- Contextual Smart Tips that provide additional information and nudges end-users to take specific action.
- Pop-Ups and Beacons that alert end-users to new updates, process changes, new features, or team announcements.
- Field Validation that ensure data is entered correctly, in the right format.
- Self Help that provides real-time performance support for employees right inside their applications.
- Enterprise Insights and User Actions that empower IT and L&D teams to track application adoption, end-user friction, employee flows, and any custom in-app action.
DAPs eliminate the gap between theory and practice, which automatically engages employees’ memory, accelerates learning, and promotes continuous training.
Above: In-app employee guidance created with the Whatfix Digital Adoption Platform
Whatfix’s DAP empowers organizations with a no-code editor to create in-app guided flows, onboarding tasklists, pop-ups, tooltips, alerts, reminders, self-help wikis, and more to enable employees to use software better. Enable your employees to become proficient in new applications faster, create interactive process documentation, guide users through process changes, assist employees through infrequent tasks, and provide self-help performance support on your CRM, ERP, HCM, or any desktop, web, or mobile application.
Request a demo to see how Whatfix empowers organizations to accelerate their employee learning programs
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