Problem solving course - The consulting approach

Discover the basic principles of consultant problem solving, including messy structures, root-cause analysis, and a hypothesis-driven, fact-based approach guided by the 80-20 rule.

Discover how structure matters by dividing problems into smaller subproblems and using a tree structure to reach root causes and actionable solutions.

Structure problems by breaking them into subproblems and visualizing them as a tree, ensuring mutually exclusive and collectively exhaustive parts, then apply five requirements: level consistency, materiality, simplicity, and actionability.

Explain level consistency by grouping items into the same logical category so a and b listed together cannot have a as a subset of b, with country examples.

Frame problem structures around simplicity to avoid overlaps and complexity. Show growth in sales through quantities or prices, with existing or new markets.

Focus on materiality to avoid over-segmentation, prioritizing branches that meaningfully affect outcomes, as in avoiding pineapple pizzas as a separate focus when most sales come from other products.

Identify controllable drivers to structure a problem, focusing on action ability and segmentation, and avoid macro factors, illustrated by the pizza case.

Explore segmentation drivers—financials, customer characteristics, value chain geography, product lines, and internal versus external factors—to break down problems effectively. Mix math or standard, and hypothesis- or issue-based approaches.

Explore the merits of mathematical segmentation to structure problems, combining mathematical and non-mathematical breakdowns for quantifiable, logical connections, illustrated by airline revenue and profit decompositions.

Compare issue based and hypothesis based segmentation to structure problems and drive solution oriented thinking, using issue trees and hypothesis trees to analyze revenues, customers, and pricing.

Prepare and draw out your structure, then sense-check and communicate it. Use sequential, mathematical segmentation to identify the main driver and build the first level before deeper breakdown.

Apply four tests to your structure: missile test for distinct branches, level test for proper levels, peanut butter factory test for tailored applicability, and high school student test for clarity.

Communicate your structure top-down with the pyramid principle, starting from the main problem and detailing subproblems and their drivers, using the volume and market-size example.

Apply issue tree and hypothesis based segmentation to boost bank productivity by optimizing customer facing time and back office share, test the structure, and deploy targeted solutions.

Lead the analysis by defining the objective, identifying key issues, and navigating a structured approach to generate actionable solutions for problems like declining airline revenues.

Lead the analysis by identifying key issues through the HDI diagnostic approach, formulating and testing hypotheses, and iterating to prioritize root causes for effective, efficient, and replicable problem solving.

Test your hypothesis by asking tailored questions to prove or disprove it, using differential analysis and benchmarking to uncover root causes and assess its scope and impact.

Analyze new information and adjust your structure in real time to keep track of data; synthesize so what insights to form hypotheses.

Lead the analysis by iterating, delving, and switching branches, testing hypotheses with new data, and pivoting when findings disprove them, using airline revenue insights to guide strategic problem solving.

Lead the analysis with a structured, actionable approach to idea generation, avoiding lists. Apply three methods: two-by-two matrices, custom-made structures, and a mathematical approach, with benchmarks and translation for inspiration.

Lead the analysis with a hypothesis-driven focus to avoid inefficiency, maintain the big picture, and test ideas through targeted inquiries to boost airline revenue and occupancy.

Apply the HDI method to identify key issues, generate hypotheses, and test productivity improvements by reallocating back-office time to customer-facing activities in Ecobank.