
By the end of this lesson, learners will be able to:
Explain the core idea behind Einstein’s quote about spending “55 minutes defining the problem and 5 minutes solving it.”
Differentiate between a fake problem (vague story) and a real problem (observable, testable gap).
Identify at least three common “problem language crimes”: globalizing, mind-reading, and abstract blob language.
Recognize the three main costs of fake problems: attention cost, action cost, and relational cost.
Apply a simple first-pass tagging system (F? / R? / R!) to their own “problem dump.”
Use ChatGPT as a basic “mirror” to highlight which problem statements are vague judgments and which are concrete and testable.
By the end of this lesson, learners will be able to:
Differentiate between a symptom and a true business problem by using the “gap between as-is and should-be” definition.
Classify business problems into Run, Improve, and Transform categories and explain how each affects time horizon and urgency.
Distinguish between Passive problems (reality hits us) and Active problems (created by goals) and describe why both matter in business.
Recognize which Cynefin domain a problem belongs to at a high level (Clear, Complicated, Complex, or Chaotic) and why each needs a different type of response.
Evaluate whether a problem is worth solving using the Impact, Frequency, Reach, and Leverage (IFRL) value test.
Describe what a problem portfolio is and explain why businesses must balance Exploit (Run/Improve) and Explore (Transform) problems instead of chasing a single “one big problem.
By the end of this lesson, learners will be able to:
Explain what a problem portfolio is at the company level and how it differs from a simple to-do list.
Describe the three archetypes of company problem portfolios: operational excellence, innovation-driven tech, and customer-obsessed.
Identify how different archetypes weight Run, Improve, and Transform problems in their portfolios.
Explain the idea of ambidexterity and the balance between Exploit (Run/Improve) and Explore (Transform) in top companies.
Recognize common mistakes when companies try to be “everything at once” without a conscious strategic choice.
Evaluate whether a company’s current work looks more like a deliberate problem portfolio or a chaotic to-do list.
By the end of this lesson, learners will be able to:
Define what makes a problem “Customer-Obsessed” rather than an internal-only issue.
Describe the three customer pillars: Customer Insight, Customer Experience, and Relationship & Value.
Differentiate between Run, Improve, and Transform problems in a Customer-Obsessed context.
Classify example problems into the appropriate pillar and horizon (Run / Improve / Transform).
Evaluate whether a list of current business problems is aligned with a Customer-Obsessed strategy.
By the end of this lesson, learners will be able to:
Define what makes a problem “Operational Excellence–relevant” in terms of work, reliability, flow, and cost.
Describe the three core pillars of Operational Excellence: Process Reliability & Quality, Flow & Speed, and Cost & Asset Productivity.
Classify operational problems into the three time horizons: Run (protect today), Improve (sharpen the engine), and Transform (rebuild the engine).
Differentiate between passive operations problems (reacting to breakdowns) and active operations problems (raising the standard).
Map real-world operational issues into the 3×3 portfolio (pillars × Run/Improve/Transform) to see gaps and imbalances.
Evaluate whether their current “top problem list” is consistent with an Operational Excellence strategy or reveals misalignment.
To show learners that if a company chooses Innovation-Driven as its strategy, then it must carry a specific portfolio of problems about
how it discovers opportunities,
how it experiments and develops solutions,
and how it commercializes and scales them
across Run / Improve / Transform horizons.
By the end of this lesson, learners will be able to:
Explain the difference between a company’s public strategy story and its power story.
Identify which strategy archetype (Customer-Obsessed, Operational Excellence, Innovation-Driven) best describes their company’s real behaviour.
Describe their team’s “mini-game” inside the larger company strategy in one clear sentence.
Write a job-to-be-done sentence for their own role using the pattern “My job is to ___ for ___ so that ___.”
Judge whether a problem is on-strategy or off-strategy by checking alignment with company game, team job, and personal role.
By the end of this lesson, learners will be able to:
Identify which problems in their recent workweek are Run, Improve, or Transform problems.
Explain the different goals and strategies for handling Run, Improve, and Transform problems.
Choose one Run problem and define a simple “firebreak” action to prevent recurring crises.
Select one Improve problem and design a small, practical upgrade to reduce friction.
Select one Transform problem and frame it as a small, low-risk experiment to try in the next 7 days.
By the end of this lesson, learners will be able to:
Distinguish Busy Problems from Leverage Problems using the two axes: alignment with company strategy and level of leverage/impact.
Identify off-strategy problems in their own work and recognise why they are Busy even if they are real and concrete.
Apply a simple 5-question test (frequency, blast radius, upstream/downstream, metric link, repeat payoff) to classify problems as Busy or Leverage.
Re-evaluate their 7-day Run / Improve / Transform plan to ensure at least one chosen problem is on-strategy and high-leverage.
Consciously de-prioritise some Busy Problems and commit to giving more focus to a small set of Leverage Problems.
By the end of this lesson, learners will be able to:
Define the difference between Passive and Active problems in their daily work.
Identify which problems in their current list are Passive (imposed by reality) and which are candidates for Active (chosen by raising standards).
Explain why not all leverage problems should automatically become their personal Active problems.
Select 1–2 Active, aligned, leverage problems that are realistic for their role and worth investing extra effort into.
Describe a healthy strategy for managing Passive problems (triage, containment, escalation) without over-owning them.
By the end of this lesson, learners will be able to:
Identify whether a given work problem fits best in the Simple, Complicated, Complex, or Chaotic domain using key cues.
Describe the default response strategy for each domain (Simple → standardise, Complicated → analyse, Complex → experiment, Chaotic → stabilise).
Classify their own high-priority problems into Cynefin Lite domains using a short set of diagnostic questions.
Match common workplace situations to an appropriate problem-solving posture (checklist, analysis, experiments, or crisis response).
(Optional AI link) Choose an appropriate way to use ChatGPT as a thinking partner based on the domain of the problem.
By the end of this lesson, learners will be able to:
Explain why the phrase “Don’t bring problems, bring solutions” is misleading and how it is often misinterpreted by employees.
Describe how leaders typically perceive different types of “problem bringers” (complainer, firefighter, solver-in-a-cave, architect).
Identify the key elements that make a problem “leader-ready” (clarity, context, scope, nature, possible directions).
Distinguish between a vague complaint and a structured, leader-ready problem statement.
Draft a short, leader-ready version of a work problem that is clear, on-strategy, leverage, and includes possible next steps.
“This course contains the use of artificial intelligence.”
Most people are told to “be more innovative”.
Very few are told where to point that innovation.
The result? Teams chase random ideas, patch symptoms, and stay busy… but not necessarily useful. Slides talk about “digital transformation”, “AI”, and “innovation”. Your calendar shows firefighting, conflicting priorities, and vague “strategic projects” that never quite land.
This course exists to fix that gap.
Finding Problems Worth Solving is a practical, AI-powered guide to the one skill that sits underneath real innovation and better decisions:
Choosing good business problems – and committing to them.
Instead of giving you yet another list of creativity techniques, this course teaches you how to see your work as a portfolio of problems, and how to use ChatGPT as a structured thinking partner to:
Spot problems that actually matter.
Test whether they’re real, leverage, and solvable.
Decide which ones deserve your time, energy, and political capital.
Think of it as learning to be the portfolio manager of your attention in an AI era.
Why “Problem-First” beats “Idea-First”
In many organisations, “innovation” quietly means:
“Please bring more ideas to the next workshop.”
But great innovators, product managers, and leaders don’t start with ideas.
They start with problems worth solving:
Problems that connect to real customers and real business metrics.
Problems that, if solved, remove a whole family of headaches.
Problems that invite experiments, not endless debate.
This course walks you through a clear, repeatable way to go from:
“Everything feels messy and urgent.”
to
“Here are the 3–5 problems that are genuinely worth our energy – and here’s why.”
You’ll learn to distinguish between:
Fake problems vs real problems.
Busy problems vs leverage problems.
Passive problems (reality hitting you) vs active problems (standards you choose).
And you’ll learn to weave these distinctions into how you talk about work, so you start to sound less like “someone who complains” and more like someone who thinks clearly about what matters.
Run / Improve / Transform – from your perspective
One of the core lenses in the course is a simple but powerful three-part view of work:
Run – problems that stop you from doing the basics (things break, customers get angry, numbers go red).
Improve – problems that, if fixed, make your current system faster, smoother, or less painful.
Transform – problems that, if tackled, change your system: how your team works, what you offer, or how customers experience you.
You’ll learn to see your own day, week, and month through Run / Improve / Transform, and then use ChatGPT to:
Make your problem list explicit instead of fuzzy.
Sort it into the right bucket.
Choose a healthy mix: enough Run to stay credible, enough Improve to create visible value, and a few Transform bets that express real innovation.
This alone changes how you interpret “be more innovative”.
Innovation stops meaning “do crazy new things” and starts meaning:
“Be deliberate about which Run/Improve/Transform problems you choose to carry.”
Problem Physics: Cynefin and the right “treatment”
Not every problem behaves the same way.
Some are like flat-pack furniture: follow the instructions and you’re done.
Others are more like gardening: you experiment, observe, and adjust over time.
In the course, you’ll get a friendly, practical introduction to Cynefin – a framework for thinking about different kinds of problems:
Simple – known cause-and-effect; best solved with checklists and standard processes.
Complicated – knowable with analysis and expertise; best solved with investigation and design.
Complex – messy, adaptive situations; best approached through small experiments, learning, and iteration.
Chaotic – fire situations; first stabilise, then move the problem into another domain.
You’ll learn how to use ChatGPT to:
Rephrase your problem in a way that reveals its domain.
Explore different “treatments” (checklist, analysis, experiment, or stabilisation action).
Avoid the classic mistakes: writing a giant plan for a Complex problem, or over-analysing a Simple one.
This “problem physics” layer means you’re not just choosing problems; you’re matching them to the right way of working.
ChatGPT as your problem-thinking co-pilot
This is not a generic “how to prompt ChatGPT” course.
Instead, you’ll see ChatGPT being used in a very specific way:
As a thinking co-pilot for your problem portfolio.
You’ll use it to:
Turn vague frustrations into concrete, observable problem statements.
Generate candidate problems from customer feedback, team complaints, or messy notes.
Classify problems by Run / Improve / Transform and by domain (Simple / Complicated / Complex / Chaotic).
Explore possible ways to test or de-risk a problem before you commit to it.
Practice how you might talk about a problem with your manager or team – with better framing and clearer logic.
You stay in control.
ChatGPT accelerates the thinking, but you decide:
Which problems make it onto your list.
Which ones get promoted to “worth solving”.
Which ones become active problems you choose to champion.
From task-doer to “problem architect” in your team
Underneath all the tools, the course is about a subtle identity shift:
From “I do tasks and react to whatever hits my inbox.”
To “I am deliberate about which problems I hold and how I frame them.”
By the end, you’ll have:
A written personal problem portfolio – your 3–7 problems worth solving next.
A simple “Problem Canvas” to keep those visible and updated.
A more confident way to speak about problems with managers and colleagues – not as complaints, but as thought-through opportunities for impact.
You won’t magically control what your company does.
But you will control where your mind, energy, and innovation time go.
And in a world where AI can generate a thousand ideas in a minute, the advantage shifts to the person who can say:
“Out of all of this, these are the problems that matter. Let’s start here.”