Employee Learning Curve (Why It Matters & How to Speed It Up)

"Learning curve" is a commonly used term in workplace training. It helps L&D and business executives track how quickly (or slowly) employees develop new skills and adapt to their roles.

Like you can see in the image below, learning doesn't happen overnight. It starts with uncertainty, but with time and practice, the skill is acquired.

By mapping this curve, L&D and business leaders can identify ways to accelerate learning for employees facing steep curves and minimize setbacks along the way.

In this blog, we’ll break down the learning curve, dive deeper into why it cannot be ignored, and explore its established types and find out ways you could speed it up exponentially.

Take a look at what’s covered:

• Origin and History of Learning Curve Theory
• What is an Employee Learning Curve
• Types of Learning Curves
• Why do employee learning curves matter?
• Formula to Calculate Learning Curve
• How AI is Transforming Learning Curves in the Workplace?
• What is the Digital Learning Curve?
• Why Digital Learning Curves Are Hard to Climb?
• How To Reduce Digital Learning Curves?
• Why Choose A DAP For Minimizing Digital Learning Curve?

Let’s dive in.

Origin and History of Learning Curve Theory

The idea that people improve with practice has existed for centuries, but the formal study of learning curves began with psychologists like Hermann Ebbinghaus.

In 1885, he explored:

• The learning curve of someone trying to learn a new skill sees the fastest knowledge gains in the first attempt, with retention decreasing over time.
• Humans forget nearly half of what they learn within days or weeks unless they actively revisit the information.

This led to early research on learning rates.

Learning curve theory, as we know it today, originated with Theodore Paul Wright, an American aeronautical engineer, who also gave us Wright’s Law and laid the foundation for modern learning curve analysis.

If you’re wondering when it became part of business strategy, it was in the 1960s when the Boston Consulting Group (BCG) expanded Wright’s Law.

They introduced the Experience Curve, showing that as cumulative production increases, costs decline. This became an unignorable method for creating competitive strategy, market-entry, and cost management.

[Sidenote: The learning curve is also known as the efficiency curve, experience curve, or productivity curve, depending on the specific metric an organization aims to measure.]

Today, learning curve theory is widely used in manufacturing, software development, training, and corporate learning. Understanding and applying it can help leaders optimize onboarding, upskilling, and performance improvement.

What is an Employee Learning Curve?

The employee learning curve is the link between an employee’s performance/productivity and how much effort (whether in time or attempts) they take to successfully understand, apply, and master a work task/concept. It’s typically visualized as a graph where:

• X-axis = Time or Experience
• Y-axis = Performance or Proficiency

An ideal employee learning curve looks something like this:

However, the learning curves in the real world are far from ideal—there’s more nuance than you might think. Influenced by factors like prior experience, learning preferences, and motivation, they can vary greatly from person to person.

That’s why we’ll explore different learning curves, each representing a unique learning journey.

Types of Learning Curves

Employees experience learning curves in different ways, and as a training manager, you can shape these experiences for better efficiency. Identifying the right learning curve helps you apply the right training strategy.

We've mapped out the key learning curves and what training managers can do in response (keep this handy for future reference).

Learning Curve Type 1/ Diminishing Returns

The diminishing returns learning curve shows that while employees make rapid progress initially, their rate of improvement plateaus (slows over time). This is common in highly skilled roles, where proficiency takes much longer than basic competency.

Here’s What Training Managers Can Do If They See Such Curve:

• Add advanced concepts, real-world scenarios, or stretch assignments to sustain learning.
• Rotate roles, expose employees to new domains, or offer multi-skill training to reignite growth.
• If traditional methods no longer work, gamification or experiential learning might help.
• Keep learning engaging by defining higher-level objectives that push the employee beyond routine tasks.

Learning Curve Type 2/ Increasing returns curve

In increasing returns curve, learning starts slow but accelerates over time. Once a critical skill level is reached, progress becomes more and more rapid. This type of curve is common in creative roles, where proficiency leads to compounding improvements.

Here’s What Training Managers Can Do If They See Such Curve:

• Let the employees (and stakeholders) know that slow progress is expected at the start.
• Use mentorship, guided learning, or structured onboarding to help them reach the breakthrough point faster.
• Once they reach the acceleration phase, give them autonomy to take on complex challenges.

Learning Curve Type 3/ Negative Learning Curves

A negative learning curve is a red flag. It is when an employee’s performance keeps declining over time instead of improving. This can indicate that the current learning method does not suit the employee’s learning preference or is too complex. This curve is standard when learning complex tools, new workflows, or unlearning old habits.

Here’s What Training Managers Can Do If They See Such Curve:

• Talk to the employees. Find out if the training is too complex. Are they feeling overwhelmed? Are they lacking support?
• Address external factors before assuming it's just a training issue. Is the employee struggling due to stress, workload, or personal challenges?
• Reframe mistakes as learning opportunities. Use positive reinforcement to rebuild confidence and motivation.

Learning Curve Type 4/ S-curve

An S-curve suggests steady, long-term development. It is when learning starts slow as the employee builds basics, then accelerates as concepts click. Once mastered, progress slows. This curve is typical in technology adoption, leadership development, and skill acquisition in stages.

Here’s What Training Managers Can Do If They See Such Curve:

• You can use microlearning training during the initial phase. Break down complex topics into small, digestible modules to reduce cognitive overload.
• When they start improving rapidly, give them complex challenges to keep momentum high. Instead of giving direct answers, guide them toward finding solutions independently.
• As different employees move through the S-curve at different speeds, you might need to combine digital tools, self-paced learning, and instructor-led training to cater to different learning preferences.

Learning Curve Type 5/ Complex Curve

A complex learning curve requires patience, support, and iterative learning, as progress is unpredictable, with multiple ups and downs. The employee might improve, then struggle, then improve again. This curve is common in multifaceted roles, problem-solving tasks, and mastering skills with a high cognitive load.

Here’s What Training Managers Can Do If They See Such Curve:

• Use hands-on training, case studies, simulations, and mentorship to deepen understanding. Repetition and real-world application help complex skills stick.
• Acknowledge progress, no matter how small. Create an environment where failures are learning moments, not performance setbacks. Encourage reflection and improvement.
• Set a clear timeline for learning milestones, but also allow room for delays. Anticipate challenges and communicate realistic expectations to higher-ups to prevent unnecessary pressure on employees.

Why do employee learning curves matter?

Learning something new at work comes with unfamiliar tasks, shifting dynamics, and different tools to adapt to. By understanding your team’s learning curve, businesses can:

• See how quickly employees pick up new skills.
• Spot when someone needs extra help.
• Know when your team is ready for bigger challenges.
• Design training programs that work for your team.

For example, if you know your developers need three months to learn a new coding language, with the fastest progress in the first month, you can plan tasks accordingly—starting simple and getting more complex later.

Formula to Calculate Learning Curve

A learning curve can be measured in two ways:

• Qualitative: Focuses on understanding how employees learn a skill or process using descriptive insights like experiences rather than numbers.
• Quantitative: Tracks progress using measurable data, such as task completion time.

Change advocates must determine whether to use one or both when guiding organizational transitions.

To measure the learning curve quantitatively, use the Learning Curve Formula.

Y = aX^b  ; where:

• Y is the average time to complete the task after X attempts.
• A is the time required to complete the task for the first time.
• X is the number of times the task has been performed.
• b is the learning rate, which is a constant that determines how quickly the learning curve declines.

Let's apply the Learning Curve Formula to a real-world example.

Scenario: A new sales rep is learning how to research hot leads.

Given:

• Y = 3 hours (time taken after X attempts)
• a = 6 hours (time taken on the first attempt)
• X = 2 weeks (assuming they did it once per week, so X = 2)

We need to find b, the learning rate, which tells us how quickly they are improving.

What This Means

b = -1 → A b value of -1 means that every time the sales rep doubles the number of times they research hot leads, the time required is cut in half.

Now, let’s answer the decade's question – how can AI enhance learning curves?

How AI is Transforming Learning Curves in the Workplace

AI is reshaping how we learn at work, making training faster, smarter, and more personalized. According to McKinsey, most companies are already experimenting with AI in some capacity.

For L&D leaders, this means they can create learning paths tailored to each employee, helping them pick up skills at their own pace (& without the overwhelm).

GenAI takes it a step further by automating training content, generating interactive materials and hands-on simulations that make complex skills easier to grasp.

For example, if you need ideas on the best training methods, AI can give you a solid starting point. If you have a practical question, you can ask this chat-ready assistant, who's always there with answers.

If your employees often struggle with the forgetting curve, AI has a fix for that too. Let’s say a tech company wants its developers to learn a new programming language quickly.

Instead of sitting through long training sessions, they can use AI-powered coding assistants like GitHub Copilot. These tools give real-time code suggestions, help debug errors interactively, and even create personalized coding challenges based on skill level.

This way, employees learn by doing (constantly improving as they go) with instant feedback keeping them on track.

That said, businesses need to address concerns about AI replacing jobs. Resistance often comes from fear, and the best way to tackle it is by creating a work environment where employees feel safe to experiment, learn, and even make mistakes.

Bottom line?  We’d say AI has the potential to simplify the learning curve, but success depends on its seamless introduction and positioning it as an enabler rather than a disruptor.

Speaking of AI, it’s the perfect segue into understanding digital learning curves.

What is the Digital Learning Curve?

A Digital Learning Curve shows how employees adapt to new digital tools, software, and technologies over time. It tracks their progress from initial exposure to full proficiency, showing how quickly they overcome challenges and become efficient users.

Here are three digital learning curve phases that your employees face:

First: The "Help, I'm Lost!" Phase

• Everything looks confusing
• Lots of clicking random buttons
• Wondering why they need to move on from the old systems

Second: The "Getting the Hang of It" Phase

• Starting to remember where things are
• Getting work done
• Questions evolve from "How do I...?" to "Can we...?"

Third: The "I Could Do This in My Sleep" Phase

• Showing others how it's done
• Creating shortcuts you won't find in any manual
• Knowledge sharing happens organically

Why Should L&D Care?

It’s simple: The faster your team masters new technology, the less time they spend struggling, and the more efficiently they work. A well-trained, digitally savvy workforce leads to higher productivity, fewer errors, and smoother work operations.

More importantly, when employees are enabled with the right tools and knowledge, they’re more likely to embrace change rather than resist it. This means smoother digital transformations, faster adoption of new processes, and ultimately, better business outcomes.

Remember: Everyone's learning curve is different, and that's okay! The goal isn't to create fast learners but to well-equip your employees enough to get the job done well.

Why Digital Learning Curves Are Hard to Climb

1/ When the Interface is Complex

How do you expect employees to pick up a new tool when it looks overwhelming? Endless menus, too many buttons, and an unintuitive layout make even the simplest digital tasks feel harder than they should be.

As a result, employees flood of IT support tickets for tasks that should’ve been easy.

2/ When “Figure It Out Yourself” Is the Default Approach

Some organizations mistakenly believe that employees will just figure things out if given vague directions like:
→ “Just explore the features.”
→ “It’s pretty intuitive.”
→ “Check the manual.”

These statements sound optimistic but often lead to technostress. They assume employees will instinctively grasp complex systems without real guidance.

But here’s the reality: every team has different types of learners:
🔹 Natural tech adopters → Quick to embrace new tools, enjoy a challenge
🔹 Methodical learners → Prefer structured, step-by-step guidance
🔹 Hesitant tech users → May resist change, need extra support

Innovative organizations design training programs that cater to all three.

3/ When Support Determines Learning Success

How well employees learn depends on the support they receive. Strong support builds confidence, weak support slows progress, and no support? That leads to frustration. Let’s break it down.

→ Great support is ACCESSIBLE AT ALL GIVEN STAGES. From onboarding to training to ongoing troubleshooting, employees should always have help at their fingertips. Contextual walkthroughs, live chat, help articles, video tutorials, and user forums—whatever they need, whenever they need it.

→ Poor support is when instructions aren’t contextual (or worse, not personalized). Too general or use jargon that doesn’t make sense to the average user. They are more challenging to follow as they don’t have screenshots or videos attached.

→ No support is when you see a high level of frustration and decreases learner satisfaction. Imagine a team abandoning a $50K software investment because the support was basically, "Here's a 200-page manual. Good luck!"

4/ When the Task Is Complicated

Not all tasks need the same amount of time to learn. Some tasks are more time-consuming, some aren’t. So, it’s a good idea to categorize tasks in terms of complexity:

→ Basic tasks (such as logging in, navigating menus, and completing simple actions) should take 1-2 weeks for most employees to get familiar with.

→ Medium complexity tasks (such as using intermediate features or setting up workflows) typically need 3-4 weeks of training and practice.

→ Advanced features (such as customization, integrations, and analytics tools) may take 6-8 weeks for employees to grasp fully.

Customize these timeframes by talking to your learners and adjusting your training schedule, making sure employees aren’t rushed or overwhelmed.

How To Reduce Digital Learning Curves?

Digital learning curves can be extended. Most of the time, the S-curve best represents them. If you want steady progress and don’t want it turning into an increasing returns curve (where adoption spikes suddenly but isn't sustained), investing in proper training and development tools is key.

Here’s how you can minimize the digital learning curve:

🔹 Know the end goal
Whether you’re tracking productivity, efficiency, or another metric, clarity is everything. Define and communicate your goal clearly to employees.

For example, if you’ve rolled out a new CRM, don’t just say, “We want sales reps to learn it.”

Instead, be specific: “By the end of the first week, we want our sales reps to be proficient in logging in and managing client profiles.”

🔹Provide Clear & Accessible Training Resources

Make learning seamless with well-structured training materials like an employee handbook, an online resource center, or even a simple list of helpful links. Break learning into bite-sized chunks to enable the microlearning approach. Personalize training materials based on job roles.

Keep resources online and mobile-friendly, making sure employees can access training anytime, anywhere, breaking down barriers to learning.

🔹Plan for Software Onboarding

With employees needing to familiarize themselves with 11 different applications on average, software onboarding can quickly become overwhelming.

Instead of overwhelming them with all training materials at once, a structured onboarding approach works best—providing application-specific guidance only when needed.

Here’s how the right training tools can help this approach:

• LMS (Learning Management System) – Provide self-paced courses to introduce platforms and build foundational knowledge.
• Knowledge Base Platform – Centralize software-related documents, FAQs, and troubleshooting guides, making it easy for employees to find answers on demand.
• Digital Adoption Platforms (DAPs) – Embed real-time, step-by-step guidance directly within applications. New app users learn on the go without searching for external resources. Step-by-step walkthroughs provide real-time, contextual guidance, resulting in a smoother digital learning curve.

For experienced users, DAPs like Gyde offer an Assist Mode, which doesn’t restart a complete walkthrough but provides help only when users face difficulties. This way, training adapts to the user’s context, enhancing efficiency.

🔹Monitor Progress

Learning curves aren’t a one-time assessment—they require continuous tracking to ensure employees progress effectively. Instead of waiting for annual performance reviews, set a regular check-in schedule every two months to analyze how the learning curve is evolving.

DAP makes this easy by providing detailed analytics. You can track which walkthroughs are most viewed, where users drop off, and get micro-level insights through an easy-to-understand dashboard.

For added accountability, automate report generation and have them emailed as proof of tool adoption. You can identify gaps, improve training strategies, and ensure that your onboarding efforts drive tangible results by monitoring engagement levels.

Why Choose A DAP For Minimizing Digital Learning Curve?

Now, there’s a reason DAP is mentioned so often. Instead of going for LMS, knowledge bases, or any such software, this is an internal solution to all problems that speed up the digital learning curve.

It fits perfectly with situations where you want to see software ROI, increased productivity, and heightened performance.

[Read more: Everything You Need to Know About the Best DAPs]

One such DAP solution is Gyde.

Gyde shows your employees where to click and what to do next and gives them all the help they need in real time through step-by-step guides.

With Gyde,

• Employees can access support in different formats. They can see real-time guidance in form of walkthroughs, watch videos, or read screenshot-based instructions or help articles.
• You can test users right inside the app to check if they’ve actually grasped the process with its in-app assessments feature.
• You can also personalize walkthroughs for specific roles. For example, a sales rep has access to client module walkthroughs in a CRM, whereas, the sales manager has access to advanced CRM module walkthroughs.
• You can provide walkthroughs and help articles in multiple languages, ensuring to get global users get the support they need in their preferred language.

This tool itself has a quick learning curve. It has no complicated setups. Gyde’s no-code walkthrough creator captures user clicks and actions to create step-by-step tutorials without manual input. It uses AI to automatically generate descriptions and titles based on user interactions.

FAQs

What are the pros of digital learning curves?

Here are some key benefits of digital learning curves:

• Employees can learn at their own speed, revisiting concepts as needed instead of struggling to keep up with a one-size-fits-all approach.
• Digital learning removes the barriers of location and time, making it easier for employees to learn whenever it fits their schedule.
• Employees can get real-time assessments and insights on their progress, helping them improve faster.
• Digital training eliminates travel, venue, and printed material costs, making it a budget-friendly option for companies.
• Organizations can measure learner progress, completion rates, and knowledge retention through analytics, helping them refine training programs.

What are the cons of digital learning curves?

Here are some downsides of digital learning curves:

• Some skills, especially technical or practical ones, require real-world practice that digital learning alone may not provide.
• Spending too much time on digital platforms can lead to eye strain, reduced focus, and overall burnout.
• Without in-person discussions, employees may miss out on the collaborative and social aspects of learning.
• Digital learning demands a high level of motivation and time management, which some learners may struggle with.
• The sheer volume of content available online can overwhelm learners, making it harder to focus on key takeaways.

How to Reduce the Learning Curve of New Team Members?

Combine the following strategies to minimize the learning curve and help your team become productive faster.

• Break down training into manageable steps with clear objectives, ensuring new hires are not overwhelmed.
• Provide in-app guidance, step-by-step walkthroughs, and real-time support to help employees learn as they work.
• Let employees practice in a controlled environment instead of relying solely on theoretical training.
• A buddy system can help new hires feel supported and accelerate their learning process.
• Monitor progress, address challenges, and refine training programs for continuous improvement.

What are the key differences between a vertical learning curve and a horizontal learning curve, and how do they impact employee training and skill development?

• A vertical learning curve shows a rapid increase in knowledge or skill over a short period. It typically occurs in high-intensity training environments, where employees must quickly acquire expertise. While this curve shows accelerating competency, it may also sign towards cognitive overload or burnout.
• A horizontal learning curve, on the other hand, signifies slow and steady progress, with knowledge or skills developing over a longer time. This often happens in self-paced learning environments. While this kind of curve means deeper understanding and long-term retention, it might show slowed down productivity gains in the short term.

Balancing both approaches in a corporate learning strategy can help organizations develop agile, competent, and well-rounded employees.

What KPIs best indicate whether employees are progressing along the expected learning curve?

The best KPIs to track employee progress along a learning curve include:

• Time-to-Competency – How quickly employees reach expected proficiency levels.
• Training Completion Rate – The percentage of employees who finish required training.
• Assessment Scores – Performance in quizzes or skill evaluations.
• Task Efficiency – Speed and accuracy in completing job-related tasks post-training.
• Error Rate – Frequency of mistakes before and after training.
• Knowledge Retention Rate – How well employees retain information over time.
• Employee Feedback & Confidence Levels – Self-reported readiness and ease in applying skills.
• Productivity Metrics – Impact on work output and quality post-training.

Tracking a mix of these KPIs helps ensure employees are not just completing training but actually improving in their roles.