Overview

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Based on the best-selling book, Bulletproof Problem Solving, by Charles Conn and Robert McLean. This course offers a systematic, structured approach to problem-solving, providing learners with tools to address challenges in both personal and professional environments. By using real-world case studies, participants will develop the skills needed to analyze complex problems and take actionable steps toward their resolution. The course emphasizes the importance of logical strategies for decision-making, empowering individuals with techniques to plan for the long term. Throughout the course, learners will engage with practical content, helping them improve their problem-solving abilities across various scenarios. What makes this course unique is its clear, visual framework that combines theory with real-world applications. The structured, seven-step process enables students to break down complex issues, prioritize tasks, and apply problem-solving methods to a variety of situations. Business professionals, managers, and individuals facing decision-making challenges will benefit from this course. While no prior experience is required, some basic understanding of logic and critical thinking will enhance the learning experience. From Bulletproof Problem Solving Copyright © 2018 by Charles Conn and Robert McLean. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Used by arrangement with John Wiley & Sons, Inc.

Syllabus

Learn the Bulletproof Problem Solving Approach

In this section, we apply the Bulletproof seven-step problem-solving cycle, building MECE logic trees to break issues apart, then prioritizing key variables to direct analytics and synthesize actionable recommendations.

Define the Problem

In this section, we convert vague challenges into outcome-focused problem statements, employing SMART criteria, KPIs and explicit scope boundaries to streamline analysis and secure strategic advantage.

Problem Disaggregation and Prioritization

In this section, we build MECE logic trees, compare deductive versus inductive structures, and apply pruning to prioritize high-impact root causes, streamlining analysis and improving strategic decision allocation.

Build a Great Workplan and Team Processes

In this section, we explore critical path workplans, blend chunky and lean planning with one day answers, and adopt agile team norms that reduce bias and spark inventive, data informed problem solving.

Conduct Analyses

In this section, we use heuristics and rules of thumb to size relationships, choose focused analyses that objectively test hypotheses, and coordinate team checks that minimize bias before complex modeling.

Big Guns of Analysis

In this section, we learn when heuristics falter and how to select, resource, and deploy Bayesian statistics, regression, Monte Carlo simulation, randomized controlled trials, machine learning, and game theory for demanding data challenges.

Synthesize Results and Tell a Great Story

In this section, we synthesize multi-source findings into succinct insights, apply pyramid logic to structure data narratives, and refine storytelling techniques to persuade skeptical stakeholders, ensuring analyses directly influence decisions.

Problem Solving with Long Time Frames and High Uncertainty

In this section, we classify uncertainty levels, construct logic trees and scenario analyses, and apply real-option portfolios to design resilient long-term strategies across capital investment, career trajectories and ecosystem conservation.

Wicked Problems

In this section, we map interconnected systems to classify obesity and overfishing as wicked problems, apply the seven-step framework to decompose causes, and prototype ecologically-economic policy solutions.