A phone giant that had built its own replacement in its labs. A shopping village asking why a visit that looks successful still disappoints. Two ways of asking “why?”, and what each one found.
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Ten items. Say your answer out loud before you reveal it.
Read the sentence, guess the meaning of the word in bold, then reveal.
Three terms: a red herring · a contributing factor · a blind spot. Say the right one, then reveal.
One missing word fits every phrase in the group. Say it, then reveal.
Read each part. After it, answer the quick check from memory, then discuss one question. The figures are rounded, and the facts are as the cases were reported.
You may have met this case in The Giant That Saw It Coming. This time, look at it through the lens.
In 2007 Nokia was not merely the market leader in mobile phones; it practically was the market. Roughly four in every ten handsets sold on earth carried its name. It was Europe’s most valuable technology company and Finland’s national champion, and it had reached that position by out-engineering everyone: better logistics, better manufacturing, phones that survived being dropped and lasted a week on one charge.
And it had seen the future. That is the detail that makes the case worth studying. Nokia had built internet-connected touchscreen prototypes years before anyone else shipped one, and its research teams had experimented with app stores and mobile internet services while competitors were still selling keypad phones. In January 2007 Apple, a computer maker with no experience of phones, announced the iPhone. The first reaction inside the industry was widely dismissive, and not entirely without reason: by every metric the incumbent used, it was a worse phone. By a metric nobody was yet using, it was a computer that happened to make calls. The App Store followed in 2008, and Android, free to every other manufacturer, within months.
Nokia responded on paper. Touchscreen devices were commissioned and its operating system, Symbian, was revised again and again. But Symbian had been designed for an earlier age, and adapting it for modern touchscreens was slow and demoralising. Software deadlines slipped by quarters, then years, while the hardware teams waited for code that kept not arriving.
1. Why does the case say that foresight was not Nokia’s problem?
2. Why was the iPhone first dismissed inside the industry?
3. What was the practical problem with Symbian?
1. Because Nokia had already built internet-connected touchscreen prototypes and experimented with app stores years before; the future had arrived in its own laboratories first.
2. By every metric the industry used it was a worse phone: more expensive, fragile, poor at calls and tied to one network. Nobody was yet measuring it as a computer.
3. It was designed for an earlier age; adapting it for modern touchscreens was slow, so software deadlines slipped by quarters and then by years.
You may have met this case in The Giant That Saw It Coming. This time, look at it through the lens.
Later academic research, built on interviews with dozens of Nokia insiders, found a more uncomfortable explanation: fear. Middle managers, the studies reported, were afraid to tell their superiors how bad the software situation really was, afraid for their budgets, their standing and their careers. Reports were softened at each level they passed through. Senior leaders, shown filtered information, set targets the engineers privately knew to be impossible, and the engineers, being asked for the impossible, reported progress that did not exist. Nobody lied, exactly. The organisation as a whole lied, one reasonable-sounding meeting at a time.
The numbers held up for a remarkably long time: smartphone share stayed high on paper well after 2007, which itself became an argument for calm. In February 2011 the new chief executive, Stephen Elop, recruited from Microsoft, circulated a memo that leaked within days. He compared the company to a man standing on a burning oil platform in the North Sea: staying meant certain death, so he had to jump into freezing, uncertain water. Nokia, he wrote, would abandon its own software and bet its future on Microsoft’s untested Windows Phone.
So why did Nokia lose? The honest answer has several parts: software that was too slow to change, a fast-moving rival with an ecosystem, and a culture that filtered bad news. None alone explains the fall, and each made the others worse. It is an example of a problem where the search for one root cause is itself a mistake.
1. What did the research on insiders find?
2. What did Stephen Elop’s memo say, and what did he decide to do?
3. Why does the case argue against a single root cause?
1. That fear led middle managers to soften bad news at each level, so leaders set impossible targets, and engineers reported progress that did not exist. A system lied, though no single person did.
2. He compared Nokia to a man on a burning oil platform who must jump into cold water; the plan was to abandon its own software and bet on Microsoft’s Windows Phone.
3. Because several causes (slow software, a strong rival, a culture that filtered bad news) interacted and made each other worse; none alone explains it.
You may have met this case in The Village That Sold a Day Out. This time, look at it through the lens.
A different kind of ‘why’ appears at Bicester Village, a shopping centre outside London which opened in 1995. The location was not a natural high street, so customers had to choose to travel there, and the company decided that the place itself had to be worth the journey. It treated shops as ‘boutiques’, shoppers as ‘guests’ and the centre as a ‘village’, with open-air streets, restaurants, multilingual service, personal shopping, hotel links and transport links. By 2019 a company-commissioned statement reported 7.3 million visits, about 2.3 million of them international.
Yet success did not close the question. In 2026 a customer-experience partner described a new programme for the company built on four principles: Effortless, Hospitable, Personalised, Fabulous. Its analysis of the visitor’s journey reportedly found inconsistent arrival and welcome, weak visibility of services, congestion, and a gap between luxury expectations and delivery. The proposed answer was not one campaign. It was to connect planning, arrival, navigation, hospitality and departure as one system.
Use the lens. What exactly happened? At Nokia: share and software deadlines slipping. At Bicester: a visit that does not always match the promise. What could explain it? Nokia: technology, a rival, culture. Bicester: arrival, signs, crowds, service. What evidence separates the causes? Nokia: prototypes showed the idea existed, delays pointed to software, insiders pointed to fear. Bicester: a journey analysis, step by step. How sure are we? At Nokia, sure that there were several causes and not which mattered most. At Bicester, the difficult question is not how do we get more visitors? It is which part of the visit system is failing, and what result would prove we repaired it?
1. What did Bicester do to make the place worth the journey?
2. What did the 2026 analysis of the visitor journey reportedly find?
3. What is the management question the case ends on?
1. It treated shops as boutiques, shoppers as guests and the centre as a village, with open-air streets, restaurants, multilingual service, personal shopping, hotel links and transport links.
2. Inconsistent arrival and welcome, weak visibility of services, congestion, and a gap between luxury expectations and delivery.
3. Which part of the visit system is failing, and what result would prove that it has been repaired?
A “Why…?” question asks you to explain what went wrong, and the danger is to answer it with a person to blame or the first explanation that comes to mind. The lens makes you state the facts exactly, list possible causes, find the evidence that separates them, and say how sure you are. It is a thinking aid, and it often ends in more than one cause.
Each situation describes a problem and what is known. What can the lens say? Choose, then check.
1. A leading cause — the timing and the content of the complaints point to one cause, and the main alternative (price) did not change.
2. Not enough data — there is no evidence yet either way; the next step is to say which data is needed.
3. Two rivals — two causes fit the facts equally well; name the one check that would tell them apart.
4. A leading cause — the change and the fix coincide exactly, which is strong evidence for the handover.
5. Two rivals — both causes fit; a comparison of leavers under different managers on the same pay would separate them.
6. Not enough data — the figures describe the problem but give no evidence of its cause; asking patients is the cheapest next step.
7. A leading cause — the timing and the fix point clearly to the supplier’s change.
There may be no single root cause. When causes interact, as at Nokia, another ‘why’ does not get you closer. Say so: Several things combined, and here is how.
Blame ends the search. Once a person is blamed, the system that allowed the problem stops being examined. Ask what the system made easy.
The cheapest check may be the wrong one. It is a place to start, not a conclusion. Be ready to say what you would do if it showed nothing.
A diagnosis uses language that says what caused what, how strong the evidence is, and what you conclude about the past. This language keeps you precise and fair.
Use each word from the box once: stems · attributable · gave · accounts.
1. The delay from one missing signature at the start of the process.
2. Most of the increase is to the arrival of a new competitor.
3. The software problems rise to a chain of late product launches.
4. That one product for half of the complaints.
1. stems — stems from
2. attributable — attributable to
3. gave — gave rise to
4. accounts — accounts for
Write the verb in brackets in the correct form, with the modal. Use the whole phrase.
1. The managers (must / know) about the delay; their own reports mention it.
2. It (can’t / be) the software; the problem began before it was installed.
3. The price rise (may well / contribute) to the fall, but we cannot be sure.
4. The staff (might / not / understand) the new process; nobody explained it.
1. must have known — very sure, from evidence
2. can’t have been — very sure it did not happen
3. may well have contributed — probable, not certain
4. might not have understood — possible
Now explain one problem you know in four sentences: state what happened, offer two possible causes, say which the evidence favours using must have / may well have / can’t have, and say how sure you are.
Say what happened, offer the possible causes, and say how sure you are. Choose a task, start the timer, and talk.
Choose one: Why did the best team in a company suddenly lose its edge? Why do some good ideas never get delivered? Why do customers leave a business they say they like? Say the facts, offer two or three causes, name the evidence that would separate them, and give your confidence.
Describe a problem where the first explanation was wrong. Say what the symptom was, what you first thought, and what you found.
Someone says: “It is obviously Sam’s fault.” Respond without defending Sam or attacking the speaker. Ask what the system allowed, and say what you would check first.