Learning Systems Mapper Preview

Map the system around the learning problem.

Member Workflow Preview

A course is not the system. It is one part of the system.

Learning Systems Mapper is planned as a guided Studio workflow for diagnosing what surrounds a learning problem: the work environment, manager support, workflow clarity, feedback loops, reinforcement, confidence, tools, incentives, and moments of transfer. The goal is to stop treating every problem like a course request and start mapping what actually needs to change.

Planned workflow

Systems Mapper should help designers find where the real problem lives.

01

Name the performance problem

Start with what people need to do differently, not the deliverable someone already asked for.

02

Map the surrounding system

Identify what happens before, during, and after the learning moment: support, workflow, tools, managers, reminders, and real-world constraints.

03

Find the weak links

Look for gaps in reinforcement, transfer, feedback, confidence, environment, incentives, or clarity.

04

Choose the right design response

Decide whether the work needs training, practice, job aids, manager prompts, workflow support, communication, or environmental changes.

Why not just ask AI for a learning plan?

Because the problem is rarely solved by generating more content.

General AI can help draft a plan, outline a course, or summarize best practices. But learning systems work requires a different kind of structure. You need to diagnose what is happening in the workflow, what learners experience after the learning event, what support exists, what managers reinforce, and where transfer breaks down. Systems Mapper is meant to make that thinking visible.

01 Problem before deliverable

Start with the performance issue instead of assuming the answer is a course.

02 System before content

Map workflow, support, environment, managers, reinforcement, and transfer.

03 Design response before output

Choose the intervention that fits the problem instead of generating a generic learning asset.

Future member outputs

The goal is a reusable map of the learning system.

Canvas

Learning System Snapshot

A reusable map of the before, during, and after moments that affect whether learning transfers into real work.

Diagnosis

Weak Link Notes

A structured summary of where the system is breaking down: feedback, support, manager behavior, workflow friction, or environment.

Plan

Design Response Map

A clearer recommendation for whether the work needs training, practice, support, communication, coaching, or system changes.

Export

Stakeholder Brief

An exportable explanation of why the solution should be broader than a single course or content deliverable.

Connected public resources

Start with the public Lab while the member workflow is being built.