How do you make sense of all the information you are bombarded with on a daily basis? We can barely absorb the overwhelming amount of information, let alone determine its meaning. As Drs. Derek and Laura Cabrera illustrate in this course, we process information best with our eyes and our hands, and we can take advantage of this fact by using visual maps. Visual maps can help you corral this information, organize and structure it, and, most importantly, convert it into knowledge you can act upon.

Through hands-on practice, you'll learn to deconstruct your thought processes and create visual maps that reveal hidden patterns and relationships in your thinking. You'll discover how to use specific mental moves and frameworks that can accelerate your analytical capabilities and help you tackle complex problems more efficiently. These techniques aren't just theoretical—they're practical tools you can apply immediately to real-world challenges, whether you're developing business strategies, improving team dynamics, or examining work processes.

The course combines visual mapping with systems thinking to help you organize information, identify structures, and develop solutions to workplace challenges. The methods you learn apply to various professional scenarios, from improving work processes to resolving team conflicts. As you practice these techniques, you'll develop practical approaches for examining complex problems in your daily work.

 

How It Works

Course Length
2 weeks

Effort
3 to 5 hours of study per week

Format
100% online, instructor-led
  • Managers, leaders, decision makers, consultants, and anyone responsible for projects, complex processes, and the budgets and people involved with them. Learners will come from every continent and from a diverse range of organizations, including private sector companies large and small, nonprofits, governments, and NGOs.
  • For people already interested in systems dynamics or soft systems methodologies, the core principles from this program can be applied to any systems-based models.
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