PART II: Thinking Skills

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"Winning teams don't simply know more frameworks. They think differently."

Frameworks are valuable. Financial models are important. Analytical tools matter, but none of them creates winning recommendations on their own. Every framework depends on the quality of the thinking behind it.

The strongest case-solving competitors develop habits of mind that allow them to ask better questions, challenge assumptions, recognise patterns, connect ideas, and make decisions under uncertainty. Those habits are skills.

Unlike memorising a framework, thinking skills transfer from one competition to the next, from one industry to another, and eventually into your professional career. All forms of thinking can use the Mad Skills Thinking Model but emphasise different stages within each.

Observe → Question → Connect → Decide → Reflect

Observe: What facts and patterns do you notice?
Question: What assumptions should be challenged?
Connect: How do the pieces fit together?
Decide: What is the best course of action, and why?
Reflect: What did you learn, and what would you do differently?

This section introduces the thinking skills that underpin every successful case solution. As you work through each chapter, remember one important principle:

Your recommendation can never be stronger than the thinking that produced it.

Chapter 5: Analytical Thinking

Learning Objectives

By the end of this chapter, you should be able to:

break complex problems into smaller components
identify relevant information
distinguish correlation from causation
use evidence to test hypotheses
interpret quantitative and qualitative information
turn data into meaningful insights

Why This Matters

Case competitions often provide more information than you can use. You may receive:

financial statements;
market data;
customer research;
industry statistics;
operational information;
survey results;
competitor information.

The challenge isn't finding information. The challenge is determining what matters. Analytical Thinking helps you separate signal from noise.

Discover Your Mad Skills Principle

Data doesn’t create insight. Thinking about data creates insight.

A table containing twenty numbers isn't analysis. Analysis happens when you identify a meaningful relationship and explain why it matters.

Deciphering Case Characteristics

The amount and type of analysis you need depends on the case. A financially focused case may require detailed quantitative analysis. A customer experience case may depend more heavily on qualitative evidence. A market entry case may require market sizing and competitive analysis. A complex operational case may require several layers of quantitative and process analysis. Don't analyse simply because data exists. Analyse because the result will help you decide.

Breaking Down the Problem

A useful analytical process is:

Define: What exactly are we trying to understand?
Break Down: What components make up the problem?
Investigate: What evidence can help us evaluate each component?
Compare: What patterns or differences emerge?
Interpret: What does the evidence mean?
Decide: How does the analysis influence our recommendation?

The Difference Between Data and Insight

Consider: "Customer retention declined from 82% to 74%." That is data.

Now consider: "Retention among high-value customers declined from 86% to 68%, accounting for most of the company's profit decline." That is insight.

The second statement is more useful because it connects the data to the decision.

Coach's Lens

I often see teams proudly announce: "We did a lot of analysis." That isn't the objective. Judges aren't rewarding the number of calculations you completed. They are evaluating whether your analysis helped you understand the problem and make a better recommendation. Ask after every analysis: So what? Then ask: Now what? Those two questions turn analysis into action.

Common Mistakes

Analysis Without a Question
Starting with data rather than identifying what you need to know.
Analysis Paralysis
Continuing to analyse after you already have enough information to make the decision.
Correlation Equals Causation
Assuming that because two things move together, one causes the other.
Ignoring Base Rates
Focusing on unusual examples rather than the broader pattern.
Overvaluing Precision
Presenting numbers to the nearest decimal when the underlying assumptions are uncertain.

Competition Example

Suppose sales have increased 12%. That sounds positive. But further analysis reveals:

volume increased 20%;
average price declined 7%;
gross margin declined 15%;
premium customers declined significantly.

The headline says growth. The analysis reveals deterioration. This is why case competitors need to look beyond the obvious number.

Mad Skills Drill

Take a financial or market table from a previous case.

Identify: Three observations.
For each observation, write: So what?
Then write: Now what?

Which observation changes your recommendation?

Reflection Questions

Did your team ever perform analysis that didn't affect the recommendation?
Which analysis created your strongest insight?
How did you decide when you had enough information?

Chapter Summary

Analytical thinking is not about doing more calculations. It is about using evidence to answer important questions. Strong analytical thinking moves from:

Data → Pattern → Meaning → Implication → Decision

Key Takeaways

✓ Start with a question.

✓ Focus on relevant information.

✓ Look for meaningful patterns.

✓ Distinguish observation from interpretation.

✓ Always ask "So what?" and "Now what?"

Looking Ahead

Analytical thinking helps you understand what is happening. But case-solving competitions also require you to imagine what could happen. That requires Creative Thinking.

Chapter 6: Creative Thinking

Learning Objectives

By the end of this chapter, you should be able to:

generate multiple possible solutions
avoid premature judgment
challenge conventional assumptions
use structured creativity techniques
combine ideas in new ways
develop differentiated recommendations

Why This Matters

Once a team understands the problem, it is tempting to jump immediately to the first reasonable solution. That can be dangerous. Your first idea is usually the most obvious. And if your team has the same information as every other team, the obvious idea is probably available to them also.

Creative thinking helps you move beyond "What could we do?" to "What else could we do?" and eventually to "What could we do that others might not consider?"

Discover Your Mad Skills Principle

Don’t confuse creativity with randomness. Great case solutions combine imagination with strategic discipline.

Creativity generates possibilities. Analysis evaluates them. Strategy selects them.

Deciphering Case Characteristics

Creativity becomes particularly valuable when:

the case asks for innovation;
existing solutions are failing;
the organisation operates in a highly competitive market;
customer needs are changing;
traditional approaches have reached their limits.

But creativity is not only for innovation cases. Every case requires some degree of creative problem-solving. The key is determining how much creativity the situation requires.

The Creative Thinking Process

A useful process is:

Define: Clearly understand the problem.
Diverge: Generate many possibilities.
Combine: Look for connections between ideas.
Challenge: Question assumptions.
Converge: Evaluate and prioritise.
Refine: Turn the strongest idea into a practical solution.

The Rule of Divergence

During brainstorming, separate: Idea generation from Idea evaluation. If someone suggests an idea and another team member immediately says: "That won't work," you have stopped creative thinking.

Capture the idea. Evaluate it later.

Creative Thinking Tools

Reverse Brainstorming

Instead of asking: How can we solve this problem? Ask: How could we make this problem even worse? Then reverse the answers.

SCAMPER

Ask whether you can:

Substitute
Combine
Adapt
Modify
Put to another use
Eliminate
Reverse

Constraint Thinking

Ask:

What if we had half the budget?
What if we had to launch in 30 days?
What if we couldn't use our current distribution channel?

Constraints can force new thinking.

Analogical Thinking

Ask: Who else has solved a similar problem? The best idea for one industry may come from another.

Coach's Lens

Creative thinking doesn't mean adding more ideas to a recommendation. In fact, one of the most common mistakes is presenting a collection of creative initiatives as innovation. Five unrelated ideas are not a strategy. The strongest creative solutions usually have a clear connection to the problem. They are:

Relevant
Differentiated
Feasible
Valuable

Common Mistakes

Brainstorming Too Early
If you don't understand the problem, you may generate solutions to the wrong problem.
Killing Ideas Too Quickly
Premature evaluation reduces creativity.
Creativity for Creativity's Sake
An unusual idea isn't automatically a good idea.
Ignoring Feasibility
Creative solutions still need to work in the real world.
Copying Other Industries Without Understanding Context
A successful idea elsewhere may not transfer directly.

Competition Example

A struggling retailer wants to increase customer visits. The obvious solutions include:

discounts;
advertising;
loyalty points.

A creative team might ask: What if the store became a destination rather than simply a place to buy products? That could lead to:

events;
experiential spaces;
partnerships;
community programming;
personalised services.

The idea is not valuable because it is unusual. It is valuable if it addresses the underlying customer problem and creates economic Value.

Mad Skills Drill

Take a straightforward case problem: "Customer traffic has declined."

Generate 20 possible solutions.
Do not evaluate them.
Then group them into themes.
Finally, select the three most promising ideas based on:
- customer value;
- strategic fit;
- feasibility;
- financial impact.

What changed when you separated creativity from evaluation?

Reflection Questions

Does your team tend to jump to the first idea?
Who challenges conventional thinking?
How do you create an environment where team members can suggest unconventional ideas?
How do you prevent creativity from becoming impractical?

Chapter Summary

Creative thinking expands the solution space. But creativity must ultimately connect back to the problem, the organisation, and the decision. The goal isn't to be different. The goal is to discover a better possibility.

Key Takeaways

✓ Understand the problem before generating solutions.

✓ Separate divergence from convergence.

✓ Challenge assumptions.

✓ Use structured creativity tools.

✓ Evaluate creative ideas for strategic and practical Value.

Looking Ahead

Creative thinking helps us ask: "What could we do?" Ethical thinking forces us to ask a different question: "What should we do?"

Chapter 7: Ethical Thinking

Learning Objectives

By the end of this chapter, you should be able to:

identify ethical dimensions of business decisions
recognise competing stakeholder interests
distinguish legal decisions from ethical decisions
identify potential harms and unintended consequences
evaluate decisions using multiple ethical perspectives
incorporate ethical considerations into recommendations

Why This Matters

A recommendation can be:

profitable;
legal;
feasible;
strategically sound;

and still be ethically questionable. Business decisions affect people.

Employees.
Customers.
Suppliers.
Communities.
Shareholders.
Future generations.
The environment.

Ethical thinking asks us to consider those consequences.

Discover Your Mad Skills Principle

The fact that we can do something doesn’t mean we should do it.

Ethical thinking expands the definition of a successful recommendation. The question is no longer simply: "Will this work?" It becomes: "Will this create value without creating unacceptable harm?"

Deciphering Case Characteristics

Ethical thinking becomes especially important when cases involve:

employee treatment;
customer data;
artificial intelligence;
environmental impact;
healthcare;
vulnerable populations;
government decisions;
discrimination;
supply chains;
social enterprises.

But ethics should not be treated as an "ESG section." Ethical considerations can exist in almost any business decision.

Legal vs Ethical

Something can be legal and still be ethically questionable. For example:

A company may legally collect customer information. But should it collect information customers don't reasonably expect to be used?
A company may legally outsource production. But should it do so if working conditions are unacceptable?
A company may legally automate jobs. But what responsibility does it have to affected employees?

These are ethical questions.

The Stakeholder Lens

Identify:

Who benefits?
Who bears the cost?
Who has power?
Who has little voice?
Who could be harmed?
Who has responsibility?

These questions can reveal ethical issues hidden inside seemingly straightforward business decisions.

Ethical Decision-Making Framework

When facing an ethical dilemma, ask:

What happened? Establish the facts.
Who is affected? Identify stakeholders.
What values conflict? Identify the competing principles.
What options exist? Don't assume there are only two.
What are the consequences? Consider short- and long-term effects.
What decision can we defend? Would you be comfortable defending the decision publicly?

Coach's Lens

Ethics should not be something teams add to the final slide because they think judges expect it. It should influence the recommendation. If you say: "We recommend automating 30% of the workforce," the ethical question isn't simply whether the plan saves money. You should consider:

who loses their jobs;
whether retraining is possible;
how the organisation communicates the change;
whether the productivity gains justify the disruption;
what responsibilities the organisation has to employees.

The best recommendations recognise these tensions rather than pretending they don't exist.

Common Mistakes

Treating Ethics as a Checkbox
Adding "ethical considerations" at the end of the presentation.
Assuming Profit and Ethics Are Opposites
Sometimes ethical decisions create long-term economic Value.
Ignoring Stakeholders
Focusing exclusively on shareholders.
Confusing Legal With Ethical
Legality establishes a minimum standard, not necessarily the best decision.
Moralising
Ethical analysis should be thoughtful rather than judgmental.

Competition Example

A company can reduce costs by moving production to a lower-cost supplier. Financial analysis shows a significant benefit. Further research reveals the supplier has questionable labour practices. The team now has a strategic choice. Options might include:

continue using the supplier;
reject the supplier;
require compliance standards;
establish an audit process;
develop alternative suppliers.

The ethical analysis doesn't eliminate the business decision. It makes the decision better informed.

Mad Skills Drill

Take a recommendation from a previous case. Identify:

three groups that benefit;
three groups that could be negatively affected;
one ethical concern;
one mitigation strategy.

Then ask, "Would you still recommend the strategy?" If not, what would you change?

Reflection Questions

Have you ever ignored an ethical issue because it made the recommendation more complicated?
Which stakeholder did your team focus on most?
Which stakeholder received the least attention?
Would you be comfortable defending your recommendation publicly?

Chapter Summary

Ethical thinking asks us to look beyond what is profitable or feasible. It asks: What is responsible? Strong case-solving competitors recognise that sustainable business decisions must consider both performance and consequences.

Key Takeaways

✓ Legal does not always mean ethical.

✓ Identify who benefits and who bears the cost.

✓ Consider stakeholders beyond shareholders.

✓ Look for unintended consequences.

✓ Build ethical considerations into the recommendation rather than adding them at the end.

Looking Ahead

Ethical thinking helps us evaluate what we should do. But many case decisions involve uncertainty. You may not have enough information to know which option will produce the best Outcome. That brings us to another essential competitive skill: Decision-Making Under Uncertainty.

Chapter 8: Decision Making Under Uncertainty

Learning Objectives

By the end of this chapter, you should be able to:

distinguish risk from uncertainty
identify assumptions that affect a decision
evaluate multiple possible outcomes
make decisions when information is incomplete
use scenarios and sensitivity analysis
build recommendations that remain resilient when assumptions change

Why This Matters

Case competitions rarely give you perfect information. You may not know:

exactly how customers will respond;
how competitors will react;
whether a market will grow;
whether implementation will proceed as planned;
whether your financial assumptions will hold.

Yet you still have to make a recommendation. That is the nature of business. Leaders rarely make decisions with complete information. The goal isn't to eliminate uncertainty. It is to make a good decision despite uncertainty.

Discover Your Mad Skills Principle

You don’t need certainty to make a decision. You need a defensible decision and a plan for managing uncertainty.

This is one of the most important lessons in case competitions. Students often try to make their recommendation sound certain. Experienced decision makers recognise uncertainty and manage it.

Deciphering Case Characteristics

The importance of uncertainty depends on the case. A decision involving a proven technology may have relatively low uncertainty. A new product entering an emerging market may have tremendous uncertainty. A startup case may involve uncertainty around almost every major assumption. A market-entry case may involve uncertainty around:

demand;
competition;
regulation;
pricing;
customer adoption.

Recognising the level of uncertainty should influence both your analysis and your recommendation.

Risk vs Uncertainty

A useful distinction is:

Risk: You can identify possible outcomes and estimate their probabilities.
Uncertainty: You cannot confidently estimate the probability of outcomes.

For example:

If historical data suggests a 20% chance of a particular outcome, you may be dealing with risk.
If the company is entering a completely new market with no reliable historical data, you may be dealing with uncertainty.

Both require judgment.

The Assumption Test

Every recommendation contains assumptions. Identify the three to five assumptions that matter most. For each, ask: What happens if this assumption is wrong? This simple question can reveal the vulnerabilities in your recommendation.

Scenario Analysis

Instead of creating one forecast, consider several.

Base Case: What happens if things develop as expected?
Upside Case: What happens if conditions are better than expected?
Downside Case: What happens if important assumptions fail?

The purpose isn't to predict the future. It is to understand how resilient the recommendation is.

Sensitivity Analysis

Sensitivity analysis asks: Which assumptions matter most to our decision?

For example, if project success depends heavily on customer adoption, test different adoption rates. If the recommendation remains attractive across reasonable scenarios, confidence increases. If a small change makes the project unattractive, that assumption deserves attention.

Decision Trees

Video: Decision Trees Visually Show Your Strategic Choices and Why You Chose Them

Decision trees can help when:

decisions happen in stages;
different outcomes lead to different next steps;
probabilities can be estimated;
the Value of future choices matters.

They help visualise:

Decision → Outcome → Decision → Outcome

Expected Value

When probabilities are available, expected Value can help compare uncertain alternatives.

A simplified version is: Expected Value = Probability × Outcome
For multiple outcomes: Expected Value = Σ (Probability × Outcome)

The calculation doesn't decide for you. It provides another piece of evidence.

Real Options Thinking

Sometimes the best decision isn't to make a large commitment immediately.

You may be able to:

run a pilot;
test the market;
launch in one region;
conduct customer research;
create a minimum viable product.

These actions generate information. That information has Value. A staged investment can therefore be a strategic response to uncertainty.

Coach's Lens

One of the strongest phrases a team can use in a competition is: "Our recommendation depends on three critical assumptions." That statement shows awareness.

Even better: "We have designed the implementation to test those assumptions before making the full investment." Now you are not simply acknowledging uncertainty. You are managing it. That is what business leaders do.

Common Mistakes

Pretending Uncertainty Doesn't Exist
Every forecast contains assumptions.
Using Fake Precision
A projection of "$4,283,721" may imply more certainty than the analysis supports.
Building Only One Scenario
One forecast is not a strategy for uncertainty.
Overanalysing Every Possibility
You cannot model every possible future.
Focus on uncertainties that could materially change the decision.
Failing to Build Flexibility into Implementation
A good strategy can adapt as new information becomes available.

Competition Example

A company is considering entering a new international market. Your model predicts:

$10 million revenue;
15% margin;
three-year payback.

The team could present these numbers. A stronger team asks:

What if adoption is 20% lower?
What if customer acquisition costs are 30% higher?
What if the competitor responds aggressively?
What if regulatory approval takes six months longer?

The analysis might reveal that the strategy is attractive under most conditions but fails under a particular scenario. That insight changes the recommendation. Perhaps the team now recommends:

A phased market entry beginning with a pilot in one region, with expansion contingent on predefined customer adoption and profitability thresholds.

The uncertainty hasn't disappeared. But it has been managed.

Mad Skills Drill

Take one recommendation from a previous case. Identify:

Three Critical Assumptions: What must be true for your recommendation to succeed?
Three Risks: What could go wrong?
Three Scenarios: What happens if conditions are better, expected, or worse?
One Trigger: What evidence would cause you to change your strategy?

Reflection Questions

Which assumption in your last recommendation was most uncertain?
Did your team test it?
What would happen if it were wrong?
Could your implementation have been designed to learn more before committing significant resources?

Chapter Summary

Business leaders rarely have perfect information. Neither do case-solving competitors.

The objective is not to eliminate uncertainty. It is to:

Identify it.
Measure it where possible.
Understand its impact.
Manage it.
Build flexibility into the decision.

A strong recommendation doesn't say: "We know exactly what will happen."

It says: "Based on what we know, this is the best decision—and here is how we will manage what we don't know."

Key Takeaways

✓ Separate risk from uncertainty.

✓ Identify the assumptions that matter most.

✓ Test critical assumptions.

✓ Use scenarios and sensitivity analysis.

✓ Consider staged decisions when uncertainty is high.

✓ Build trigger points into implementation.

✓ Don't confuse precision with certainty.

PART II CLOSING: Five Thinking Skills. One Strategic Mindset.

The five skills in this section are different, but they work together.

Critical Thinking asks: Is our reasoning sound?
Strategic Thinking asks: Where should we go?
Systems Thinking asks: How are the pieces connected?
Analytical Thinking asks: What does the evidence tell us?
Creative Thinking asks: What else is possible?
Ethical Thinking asks: What should we do?
Decision Making Under Uncertainty asks: How do we make the best choice when we don't know everything?

These are not separate skills; you use one at a time. They interact throughout the case-solving process.

You may use analytical thinking to understand the problem.
Systems thinking to understand its causes.
Creative thinking to generate alternatives.
Critical thinking to challenge them.
Ethical Thinking to understand their consequences.
Strategic Thinking to determine which direction creates the most Value.
Decision-making under uncertainty to choose a path forward despite incomplete information.

That is what expert case-solving looks like. It's not simply knowing more; it's thinking better.

The Mad Skills Thinking Cycle

Throughout your case-solving career, return to this cycle:

OBSERVE (What is happening?) à QUESTION (What should we challenge?) à CONNECT (How do the pieces interact?) à EXPLORE (What possibilities exist?) à EVALUATE (What does the evidence tell us?) à DECIDE (What should we do?) à ADAPT (What will we do if our assumptions change?)

ü The framework is never the goal.

ü The insight is never the end.

ü The decision is what matters.

And the better you become at thinking, the better your decisions become. That is the foundation of your Discover Your Mad Skills toolkit.