Why Effective Learning Design Starts With the Business Problem

When a business comes to a learning and development professional with a request for training, the natural response is to start thinking about the course. What should the content include? What platform should we use? Should it be eLearning, instructor-led training, video, or microlearning? What activities will make it engaging? These are all important questions, but they shouldn't necessarily be the first questions we ask.

The first question should be: What problem are we actually trying to solve?

That distinction is important because not every performance problem is a learning problem. A team may be making mistakes because a process is unclear, information is difficult to find, expectations have changed, or employees don't have the right tools to perform their jobs. Customers may be contacting support repeatedly because onboarding doesn't adequately prepare them, but they may also be struggling because a product experience is confusing or important information is buried in too many different places. Building a training course won't automatically solve those problems.

This is where I believe instructional design has become much more strategic than simply creating courses and learning materials. An effective instructional designer needs to understand the business problem, the audience, the environment in which people are expected to perform, and what successful performance actually looks like. The goal isn't simply to give people more information. The goal is to create a solution that helps people apply the right information at the right time and ultimately perform better.

For example, imagine a company is seeing an increase in customer support tickets related to the same product features. The initial request might be to create a customer training course. That could be the right solution, but I would want to understand the problem before making that recommendation. Are customers unaware that the features exist? Do they understand how to use them but struggle with a particular step? Is the existing documentation difficult to navigate? Is the onboarding experience missing critical information? Are customers receiving inconsistent information from different members of the organization? Each of those situations could require a very different solution.

The same principle applies internally. If employees are repeatedly asking the same questions, creating another course may not be the most effective answer. Sometimes employees don't need additional training—they need better access to information. A searchable knowledge base, quick-reference resource, process guide, short video walkthrough, or performance support tool may be more useful than asking employees to complete another hour-long course.

That doesn't mean traditional training or eLearning is no longer valuable. It means we need to be more intentional about when we use it. There are situations where people genuinely need to develop new knowledge or skills, and structured learning can be extremely effective. The key is understanding what learners need to know, what they need to do, and what support they need after the formal learning experience ends.

This is also why I believe learning should be designed as an experience rather than treated as a single event. Someone may complete onboarding on their first week, but that doesn't mean they will remember everything they were taught three months later when they encounter a new situation. A customer may complete product training but still need a quick walkthrough when they use a feature for the first time. A manager may attend leadership training but need a practical conversation guide when they actually have to deliver difficult feedback.

Good learning design considers what happens before, during, and after the learning experience. It considers how people access information, how they practice new skills, how they receive reinforcement, and where they can find help when they need it. That is where learning starts to connect with enablement, knowledge management, customer education, and performance support.

Technology has also changed what is possible. Tools such as Articulate 360, learning management systems, knowledge platforms, video tools, analytics, and AI can help us create and deliver learning in ways that weren't possible years ago. But having access to more technology doesn't automatically mean we are creating better learning experiences. The tool should support the strategy, not determine it.

AI is a good example. It can help instructional designers brainstorm, organize information, create drafts, develop variations of content, and accelerate parts of the production process. Those capabilities can save significant time. However, AI doesn't replace the need for instructional strategy, audience analysis, stakeholder collaboration, or critical thinking. Someone still needs to determine whether the content is accurate, relevant, accessible, appropriate for the audience, and connected to the desired outcome.

The same principle applies to data. Completion rates, assessment scores, survey responses, customer feedback, support tickets, and product adoption data can all provide valuable information. But data is only useful when we know what question we're trying to answer. If a course has a 98% completion rate but employees continue making the same mistakes, the completion rate isn't telling us that the learning solution was successful. It may simply be telling us that people completed the course.

This is why I like to think about learning in terms of performance and outcomes.