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Culture Matters. Just Not in the Way We Think.

6/4/2026

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Part 4: How Strong Is the Culture–Performance Link, Really?

We rarely question the line “culture drives performance” – it feels intuitively true.
This series asks how strongly that claim is supported by evidence. It is for leaders, HR, and OD practitioners who are making decisions about where to invest scarce time, money, and leadership attention. In this part, the aim is to help you calibrate just how powerful culture appears to be compared with other predictors of performance – and what that means for your priorities.

Introduction
We rarely question the statement, 'culture drives performance'.
It is repeated in boardrooms, strategy documents, and leadership offsites. It feels intuitively correct.
But intuition is not evidence. If culture is one of the most powerful drivers of organisational success, we should expect to see a strong and consistent empirical relationship between culture and performance. So what does the research actually show?

The Science
The CIPD rapid evidence assessment reviewed meta-analyses and controlled studies examining the link between organisational culture and performance.

The findings are clear:
  • The overall association between culture and performance is moderate to low.
  • Across 60 studies, the average correlation is small, approximately 0.16.
  • When objective performance measures (such as profitability or revenue growth) are used, the correlation drops further.
  • The evidence is inconsistent across different culture types and performance outcomes.
A correlation of 0.16 is not zero, but it is modest. For context, some meta-analyses have found that general mental ability predicts job performance with correlations around 0.50 or higher. In other words, individual cognitive ability shows a stronger and more consistent link to performance than organisational culture does.
That comparison is uncomfortable, because it challenges where we place our attention.

Key Findings
The evidence suggests several important conclusions:
  1. Culture correlates with performance, but modestly.
    The relationship exists, but it is not large. Imagine performance differences are represented by a whole pie. Culture explains only one small slice of that pie, about 2–3%. The rest of the pie is made up of many other ingredients.
  2. The link weakens with harder measures.
    When performance is assessed with more objective indicators, the culture–performance correlation becomes smaller.
  3. Culture is a weaker predictor than some other variables.
    Factors such as general mental ability, aspects of personality, leadership quality, and structural design often show stronger and more consistent relationships with performance. For example, 25% of performance can be statistically explained by cognitive ability
  4. The direction of causality is often unclear.
    In some studies, strong performance appears to influence how people describe their culture, rather than culture clearly driving performance.
This does not mean culture is irrelevant, it means culture may not be the dominant lever we often assume it is.
It also highlights a methodological issue. Much culture research relies on cross-sectional survey data. That makes it difficult to establish:
  • What comes first.
  • What actually causes what.
  • How much of the effect is really due to other factors such as leadership, incentives, or talent.
There is limited rigorous intervention evidence showing that deliberately changing culture, in isolation, reliably improves performance.

What Does This Mean in Practice?
If culture’s predictive power is modest, several possibilities emerge for practice. First, culture may be a contextual amplifier rather than a primary engine.  It shapes how other levers – strategy, structure, leadership, talent – play out day to day. Second, culture may interact with other predictors rather than operate independently. For example, good leadership might have more impact in enabling conditions of psychological safety and trust. Third, we may have under-invested in other organisational-level predictors of performance.
The wider research literature suggests paying close attention to:
  • Leadership quality and consistency.
  • Decision-making structures and speed.
  • Incentive and reward alignment.
  • Selection and talent density.
  • Performance management systems.
  • Cognitive diversity.
  • Role clarity.
  • Fairness and justice perceptions.
It is entirely plausible that some of these variables account for more variance in performance outcomes than culture itself, yet we often default to culture as the headline explanation. This is not a call to abandon culture but a call to rebalance our attention. If you are serious about performance, you may need to:
  • Invest more in understanding structural predictors.
  • Examine how culture interacts with systems rather than treating it as a stand-alone fix.
  • Be cautious about bold claims that “culture drives results” without specifying how much and through which pathways.

If You’re a Leader or HR Practitioner, Try This Week
To translate this into action, you can reassess where you focus effort:
  1. List your current “performance levers”.
    Write down the main initiatives currently justified as “improving performance” (for example, culture programmes, leadership development, incentive redesign, role clarity work). Mark which ones are explicitly framed as culture work.
  2. Estimate impact, then challenge your estimate.
    For each initiative, privately rate (on a simple 1–5 scale) how much impact you expect it to have on performance in the next 12–24 months. Then ask: if culture’s direct effect is modest, where might structural or leadership changes deliver more impact for the same effort?
  3. Reframe one culture claim.
    Take a statement like “we need to transform our culture to hit our targets” and rewrite it more precisely, for example: “We need clearer decision rights, better frontline leadership, and aligned incentives to hit our targets; over time, consistently doing this will shift how people experience our culture.”
  4. Run a “what else matters?” exercise with your team.
    In a leadership or HR meeting, pose the question: “If culture is only one of several modest predictors of performance, what other variables in our organisation might deserve equal or greater scrutiny this year?” Capture the list and compare it to your current agenda.
  5. Design one system experiment before a culture campaign.
    Before launching a broad culture initiative, pick one concrete system element (for example, how promotions are decided, or how projects are resourced) and run a small, evidence-informed experiment there. Observe whether performance and people’s experience shift, without labelling it a “culture” project.
These steps do not deny that culture matters. They help you place culture in context and avoid overclaiming what culture work alone can deliver.

A Quote to Reflect On
“The association between organisational culture and performance is moderate to low.”
— Organisational Culture and Performance: An Evidence Review

A Question to Reflect On
If culture is not the strongest predictor of performance:
What other variables in your organisation might deserve equal – or greater – scrutiny?
If you can name them, your next strategic decision may be to rebalance where you invest effort: treating culture as important context, not the only story.

Further Reading
  • Barends, E. & Rousseau, D. (2022). Organisational culture and performance: An evidence review. CIPD
  • Chatman, J. & O’Reilly, C. (2016). Paradigm lost: reinvigorating the study of organisational culture.
  • Schneider, B., Ehrhart, M., & Macey, W. (2013). Organisational climate and culture.
 


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Culture Matters. Just Not in the Way We Think.

23/3/2026

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Part 3: Can we measure culture – or are we measuring something else?
At work, we behave as if “culture” is something we can capture in a dashboard. We run surveys, plot index scores, and compare ourselves to benchmarks. This series asks what those numbers are actually telling us. In this part, the aim is to help leaders, HR, and OD practitioners distinguish between measuring “culture” in the abstract and measuring concrete constructs such as fairness, trust, or role clarity that you can genuinely act on.
​
Introduction
If culture matters, we should be able to measure it. That seems reasonable.

Across organisations, we run:
  • Culture diagnostics
  • Engagement surveys
  • Values alignment assessments
  • Competing values frameworks
  • Proprietary culture tools
We generate dashboards, heat maps, and index scores.
But a more uncomfortable question sits beneath all of this:
Are we measuring culture or are we measuring something adjacent to it?

The Science
The CIPD evidence review examined how organisational culture is assessed across the research literature.
Several issues stand out:
  • Over 70 diagnostic instruments exist.
  • There is no consensus on the best method.
  • Some tools show predictive validity.
  • But construct validity remains unclear.
Construct and predictive validity matters. Predictive validity tells us that a measure correlates with an outcome. Construct validity tells us whether we are actually measuring the thing we claim to be measuring.
In some cases, prominent tools such as OCAI and DOCS were originally designed to measure organisational effectiveness. They were later positioned as culture instruments. This creates a circular problem. If a tool measures effectiveness-related variables and then correlates with performance, are we observing:

Culture → Performance
Or simply:
Effectiveness indicators → Performance

The distinction is not academic nit-picking. It goes to the heart of what we believe we are managing. The CIPD review also notes that many studies rely on cross-sectional surveys and self-report data, often completed by senior managers.

That introduces further concerns:
  • Single-source bias
  • Perception distortion
  • Lack of temporal ordering
If we cannot clearly define culture, and we struggle to measure it with construct clarity, then management confidence should be cautious.

Key Findings
From the evidence:
  • There is no agreed method of assessing culture.
  • Scholars remain divided between qualitative deep-dive approaches and quantitative survey-based approaches.
  • Many instruments demonstrate reliability and some predictive validity.
  • However, it remains unclear what exactly they are capturing.
That final point is critical.

It is possible that culture surveys are measuring:
  • Leadership behaviour
  • Fairness perceptions
  • Trust levels
  • Psychological safety
  • Clarity of strategy
  • Incentive alignment
  • Workload stress
  • Management quality
All of which are meaningful. But those are not identical to culture as defined by Schein’s deep assumptions model. We may be aggregating perceptions of management systems and calling the result “culture”.

What Does This Mean in Practice?
This is where it becomes practical. When you run a culture survey, ask:

What constructs are actually being assessed?
If employees respond to items about:
  • Feeling listened to
  • Fair treatment
  • Clear expectations
  • Accountability
  • Recognition
Are you measuring culture? Or are you measuring:
  • Managerial competence
  • Justice perceptions
  • Psychological climate
  • Performance management quality
These distinctions matter because the interventions will differ.

If low scores reflect poor role clarity, the intervention is structural.
If low scores reflect pay inequity, the intervention is economic.
If low scores reflect leadership inconsistency, the intervention is behavioural.

If everything is labelled culture, solutions become vague. Measurement clarity forces intervention precision.
This does not mean stop surveying. It means: be explicit about what your instrument captures and resist the temptation to let the word culture absorb multiple system variables without differentiation.

If You’re a Leader or HR Practitioner, Try This Week
To turn this into action, you can take a more forensic look at your “culture” data:
  1. Deconstruct your latest survey.
    Take your most recent culture or engagement survey and list the main themes it measures (for example, trust, workload, leadership, clarity, recognition). Relabel each theme with the most concrete construct you can: “role clarity”, “perceived fairness”, “manager availability”, “psychological safety”.
  2. Match constructs to interventions.
    For one low-scoring area, ask:
    • If this is really about workload, what structural changes would we consider?
    • If it is really about fairness, what policy or pay decisions are needed?
    • If it is really about leadership behaviour, what support or consequences are required?
      Write one potential intervention for each interpretation. Notice how different they are.
  3. Change the way you present results.
    In your next slide deck or report, replace a generic phrase like “our culture scores are down” with a more precise line such as: “Scores on role clarity and perceived fairness have dropped; these are our current hypotheses about why.”
  4. Ask your vendor harder questions.
    If you use an external tool, ask the provider:
    • Which constructs does this instrument validly measure?
    • Which constructs does it not measure?
    • What evidence do you have that this is about culture rather than, for example, leadership or climate? Use the answers to refine how you talk about the results internally.
  5. Pilot a more targeted measure.
    Before commissioning another broad “culture” survey, consider a small, focused pulse on one construct you care deeply about (for example psychological safety or role clarity). Make the construct explicit from the start, and design your interventions to match it.
These steps will not eliminate all ambiguity but they will reduce the gap between what your numbers claim to measure and what you actually act on.

A Quote to Reflect On
“Although these instruments have often provided good predictive validity… there is no evidence of construct validity, meaning that it is unclear what exactly is being measured.”
Organisational Culture and Performance: An Evidence Review

A Question to Reflect On
When your organisation receives its next culture report:
Do you know which underlying constructs are being measured?
And do your interventions match those constructs?

If the answer is “not really”, your most impactful next step may be to tighten the link between what you measure, what you call it, and what you actually do.

Further Reading
  • Barends, E. & Rousseau, D. (2022). Organisational culture and performance: An evidence review. CIPD
  • Chatman, J. & O’Reilly, C. (2016). Paradigm lost: reinvigorating the study of organisational culture.
  • Schneider, B., Ehrhart, M., & Macey, W. (2013). Organisational climate and culture.
 


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Culture Matters. Just Not in the Way We Think.

9/3/2026

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Part 2: If Culture Improves Performance, How Exactly?

At work, we often say “culture drives performance” as if the pathway is obvious. This series explores what the evidence actually shows about that claim. It is for leaders, HR, and OD practitioners who are under pressure to “use culture” as a performance lever and want more clarity before investing time and money. The aim of this part is to help you move from culture as a slogan to culture as a clearer cause-and-effect story you can scrutinise and, where appropriate, act on.

Introduction

We often hear that culture drives performance.

It is said with confidence:
  • Strong cultures outperform weak ones.
  • Winning companies have distinctive cultures.
  • Culture is a competitive advantage.
But once you ask a simple question, the certainty becomes harder to sustain:
How, exactly, is culture supposed to improve performance?

What is the mechanism?
Not the slogan, the mechanism

The Science

The CIPD evidence review explicitly examined the assumed logic model linking organisational culture to performance. Their conclusion is striking. It is unclear how organisational culture enhances performance.

The claim that culture affects performance rests on three assumptions:
  1. Organisations have an identifiable culture.
  2. Culture is related to performance.
  3. Culture can be changed to improve performance.

But when researchers look for a coherent, unified theory explaining how culture produces performance gains, they do not find one. Instead, what exists is a collection of loosely related hypotheses.

For example:
  • An “adhocracy” culture is said to enhance innovation by encouraging autonomy and risk-taking.
  • A “market” culture is said to improve financial performance by emphasising results and competitiveness.
  • A “clan” culture is associated with collaboration and internal cohesion.

These are plausible stories. But plausibility is not the same as causal clarity. There is no single, integrated model explaining:
  • Through which pathways culture affects behaviour.
  • Under what conditions it matters more or less.
  • Whether it precedes performance or follows it.
In fact, some longitudinal studies suggest the direction of causality may run the other way: performance can shape culture, not just the reverse.

Key Findings

The evidence on culture and performance shows:
  • Correlations are moderate to low (mean around 0.16 across studies).
  • Associations are substantially weaker when objective performance measures are used.
  • Culture is a weaker predictor of performance compared with factors such as general mental ability, personality traits, or structural variables.
Importantly, correlations do not explain mechanism. If culture correlates with innovation in certain contexts, that still leaves open critical questions:
  • Is it culture that drives innovation?
  • Or do innovative firms retrospectively describe themselves in certain ways?
  • Or do both emerge from underlying leadership, incentives, and strategy?
Without a clear cause-and-effect story, culture risks becoming an explanatory shortcut.
When something works, we attribute it to culture. When something fails, we diagnose a culture problem. But that may be post hoc reasoning.

What Does This Mean in Practice?

In HR and leadership conversations, culture is often treated as a performance lever.
The implicit model looks like this:
Define desired values
→ Communicate them clearly
→ Align behaviours
→ Improve performance

But if the mechanism is unclear, the intervention pathway becomes fragile. So before launching a culture initiative, it may be worth asking:
  • What behaviour are we trying to change?
  • What system currently stabilises that behaviour?
  • What incentives reinforce it?
  • What leadership signals normalise it?
  • What consequences make it costly to act differently?
If culture influences performance, it likely does so indirectly:
  • By shaping coordination.
  • By reducing friction.
  • By influencing trust and psychological safety.
  • By stabilising expectations.
In other words, culture may not be the engine, it may be the operating conditions. Operating conditions matter, but they are not the same thing as horsepower. The risk for practitioners is not believing culture matters, the risk is assuming you understand the pathway without interrogating it.

If You’re a Leader or HR Practitioner, Try This Week
To move from slogans to mechanisms, you can run a few focused experiments:
  1. Name the specific outcome, not just “performance”.
    Choose one outcome that matters this year (for example, faster decision-making, fewer safety incidents, better cross-team collaboration). Write it down in a single sentence.
  2. Sketch your current “culture story”.
    For that outcome, write how you currently believe culture helps or hinders it. For example: “Our culture of openness helps us spot risks early” or “Our blame culture slows reporting.” Then ask: what is the actual behaviour in meetings, emails, and decisions that makes this true?
  3. Map system levers behind the story.
    For the same outcome, list:
    • How are decisions really made?
    • Who has authority to say “yes” or “no”?
    • What gets rewarded or penalised (formally and informally)?
    • What happens when someone raises a problem or makes a mistake? This starts to separate “culture” from the concrete levers you can adjust.
  4. Test one assumption about cause and effect.
    Take one belief such as “we need a culture of accountability to improve results” and reframe it as: “We think clearer goals, regular follow-up, and consequences for missed commitments will improve results.” Run a small experiment (for example, weekly progress reviews in one team) and see what changes before you launch a broad “accountability culture” programme.
  5. Be explicit in your language.
    In your next communication or slide deck, replace one phrase like “our culture drives performance” with a more precise statement: “These three practices (X, Y, Z) are how we expect to improve performance; over time, if we repeat them, they will shape what people experience as our culture.”

These steps will not produce a perfect logic model. But they will force you to be clearer about how you believe culture connects to performance - and where you might be relying on story rather than evidence.

A Quote to Reflect On
“The logic model for the culture–performance link is not based on a single coherent theory, but rather a number of separate, loosely related hypotheses.”
— Organisational Culture and Performance: An Evidence Review

A Question to Reflect On
When you say culture drives performance in your organisation:
Can you clearly articulate the mechanism? or are you inferring cause from correlation?

If your answer is closer to the second, your next step may be to pause the next broad “culture” initiative and first map the specific pathways you are actually trying to change.
​
Further Reading
  • Barends, E. & Rousseau, D. (2022). Organisational culture and performance: An evidence review. CIPD
  • Chatman, J. & O’Reilly, C. (2016). Paradigm lost: reinvigorating the study of organisational culture.
  • Schneider, B., Ehrhart, M., & Macey, W. (2013). Organisational climate and culture.

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Culture Matters. Just Not in the Way We Think.

23/2/2026

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Part 1: What Do We Actually Mean by Culture?

At work, we talk about culture as if it is obvious, powerful, and always worth investing in. This series takes a more evidence-based look at those assumptions. It is for leaders, HR, and OD practitioners who are being asked to “fix the culture” or “build a high-performance culture” and want to be more precise. Across the series, the aim is to help you make better decisions about when to work on “culture”, when to work on systems and structures, and how to connect the two in practice.
Introduction

I have written about culture before.
I have facilitated culture conversations.
I have believed culture was a primary lever of organisational success.

But reading the evidence more closely has unsettled me.

We talk about culture as if it is obvious. As if everyone knows what it is. As if it can be strengthened, shifted, or engineered with enough intention.

Yet when you step into the research, certainty fades.

Before we ask whether culture improves performance, perhaps we need to ask a more basic question:

What exactly do we mean by culture?
And if you are a leader, HR, or OD practitioner, an equally practical question follows:

When you say “culture” at work, what specific behaviours and system signals are you actually pointing at?

The Science

The Chartered Institute of Personnel and Development (CIPD) conducted a rapid evidence assessment examining the link between organisational culture and performance.

Their findings are sobering:
  • There is no consensus definition of organisational culture.
  • Multiple competing schools of thought exist.
  • Scholars disagree on whether culture is something an organisation is or something it has.
Two dominant approaches stand out:

1. Schein’s model
Culture is a pattern of shared underlying assumptions, values, and beliefs that guide behaviour. It is deep, embedded, and difficult to change.

2. Traits–strength models
Culture is a profile of measurable characteristics (for example clan, market, hierarchy, adhocracy) assessed via surveys such as Competing Values Framework (OCAI), Denison Organisational Culture Survey (DOCS), Organisational Culture Inventory (OCI) or Organisational Culture Profile (OCP).

The problem is not that these models exist. The problem is that they are conceptually different. If scholars cannot agree what culture is, measurement becomes unstable.

And when measurement is unstable, management becomes uncertain.

Key Findings

The CIPD review highlights several important issues:
  • Over 70 diagnostic instruments exist for assessing culture.
  • Many show predictive validity but lack construct validity.
  • In some cases, tools originally designed to measure effectiveness have been relabelled as culture instruments.
  • Studies often rely on cross-sectional surveys and self-report data.
Put simply: we may be correlating performance with something called culture without being entirely clear what that “something” is.

This does not mean culture is imaginary.
It does mean it is conceptually fragmented.

And that fragmentation matters.

What Does This Mean in Practice?

In HR, we routinely:
  • Commission culture surveys.
  • Diagnose cultural strengths and weaknesses.
  • Design culture change initiatives.
  • Align recruitment and reward with “our culture”.
But if the construct itself lacks clarity, we must pause.

When we say:
“We have a high-performance culture.”

What are we actually referring to?
  • Decision speed?
  • Collaboration norms?
  • Risk tolerance?
  • Leadership behaviour?
  • Incentive design?
  • Psychological safety?

If different leaders are imagining different things, culture becomes a container word.
And container words can obscure more than they clarify.

Perhaps the more useful move is not to abandon culture, but to disaggregate it.

Instead of asking:
“How do we strengthen our culture?”
Ask:
  • Which behaviours are stabilised?
  • Which behaviours are rewarded?
  • Which behaviours are tolerated?
  • Which behaviours are costly?
That shift moves us from abstraction to mechanism.

If You’re a Leader or HR Practitioner, Try This Week

To make this concrete, here are a few small experiments you can run:
  1. Clarify the picture behind the word “culture”.
    In your next leadership or HR meeting, ask each person to write down, in one sentence, what they mean when they say “our culture”. Compare the answers. Notice where they diverge.
  2. Translate slogans into observable behaviour.
    Take one existing culture statement (for example, “We have a high-performance culture” or “We value collaboration”) and rewrite it as concrete behaviour:
    • “We have a high-performance culture” → “We commit to clear goals, review progress weekly, and address underperformance within one month.”
    • “We value collaboration” → “Major cross-team decisions involve A and B before sign-off.”
  3. Name the system signals, not just the vibes.
    For one team or function, list three recent decisions about hiring, promotion, reward, or workload. Ask: “What do these decisions signal is really valued here?”
  4. Audit a phrase you use often.
    If you frequently describe your organisation as “innovative”, “customer-centric”, or “high trust”, write down:
    • What behaviours are consistently rewarded that justify this label?
    • What behaviours are consistently penalised that would contradict it?
These actions do not solve culture.
But they make your use of the word “culture” more precise, and your levers more visible.

A Quote to Reflect On
“There is no consensus of what ‘organisational culture’ entails.”
— Organisational Culture and Performance: An Evidence Review

A Question to Reflect On
When you talk about culture in your organisation, are you describing shared assumptions, measurable traits, or simply patterns of behaviour?

If your honest answer is “I’m not sure”, your next step may not be another culture initiative. It may be a clearer shared definition.

Further Reading
  • Barends, E. & Rousseau, D. (2022). Organisational culture and performance: An evidence review. CIPD
  • Chatman, J. & O’Reilly, C. (2016). Paradigm lost: reinvigorating the study of organisational culture.
  • Schneider, B., Ehrhart, M., & Macey, W. (2013). Organisational climate and culture.

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Work, Mind, and Cognitive Health

9/2/2026

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Part 2: The myth of inevitable decline – and the HR policies that quietly reinforce it
​
One of the most enduring assumptions about cognitive decline is that it is inevitable: ageing equals decline, decline equals limitation, limitation equals withdrawal. Yet both Ellen Langer’s work and the Lancet Commission’s life course model suggest a different story: decline is neither uniform nor fixed, and context matters.

If culture shapes behaviour, policy shapes expectation. Many organisational systems are quietly built on assumptions about fragility and diminishing capability that the science does not support.

The science, briefly recapped
The Lancet Commission highlights that cognitive risk factors accumulate through everyday exposure to stress, inactivity, isolation, and limited learning, many of which are influenced by working conditions. At the same time, risk trajectories remain changeable throughout life, undermining the idea that decline is a one-way path.

Langer’s research adds the psychological dimension: when people are treated as capable, choiceful, and engaged, outcomes improve; when systems signal fragility, limitation, or passivity, outcomes deteriorate. Workplaces operationalise these signals not only through culture, but through HR policy.
So what myths about cognition are embedded in the way work is formalised?

Myth one: cognitive decline is an age issue
This myth appears when development investment drops after a certain career stage, or when mid-career roles become narrower rather than richer. Organisational research shows that training and development investment often peaks early in careers and declines sharply after mid-career, based more on assumptions about return on investment than on evidence of learning capacity.
Policy shifts could include:
  • Setting explicit expectations that development budgets and stretch opportunities are distributed across career stages, not front-loaded.
  • Designing mid- and late-career roles that add complexity and discretion rather than only span and oversight.
Reflective prompt: If you plotted development spend by age band in your organisation, what story would it tell?

Myth two: predictability is always protective
This belief is often embedded in rigid role profiles, static job families, and promotion systems that reward replication over learning. Static roles are easier to design, benchmark, and control, yet job design research shows that when predictability dominates, roles can drift into “passive jobs” (low demand and low control), whereas “active jobs”, which combine structure with discretion, better sustain learning and cognitive health over time.
Policy shifts could include:
  • Building in periodic role refresh cycles that explicitly add problem-solving, experimentation, or mentoring components.
  • Reviewing promotion criteria for signals that prize stability over adaptive learning and reframing them to value judgement, experimentation, and informed risk-taking.
Reflective prompt: Where in your job architecture have roles become easier to administer than to grow in?

Myth three: wellbeing sits outside core people processes
This myth appears when health, workload, and learning are treated as separate from performance, reward, and progression. A substantial body of research shows that organisations frequently incentivise overwork, speed, and constant availability, even while promoting wellbeing rhetorically. When performance ratings and promotion decisions favour those who tolerate unsustainable load, wellbeing becomes performative rather than genuinely protective.
Policy shifts could include:
  • Integrating workload sustainability and recovery practices into performance conversations and leadership expectations.
  • Auditing reward and recognition mechanisms for signals that equate value with visible overextension or constant availability.
Reflective prompt: If people only watched who gets promoted and rewarded, what would they infer about the cognitive cost of success here?

From myth to design choice
If organisations took cognitive health seriously as a long-term outcome, some HR policy choices might look different. For example:
  • Career frameworks that encourage movement, secondments, and skill renewal rather than linear progression alone.
  • Performance systems that value judgement, learning, and adaptation, not just delivery under pressure.
  • Capability models that evolve with roles, designing jobs for tomorrow’s expectations rather than recruiting only for yesterday’s skills.
  • Work environment standards that treat sound, light, and sensory load as cognitive factors, not merely facilities issues.​

None of these require radical reinvention; they require a shift in what organisations see as legitimate people risks and a willingness to see cognition as an organisational outcome, not just an individual trait.

A quote to reflect on
“Much of what we call decline is simply the result of how situations are framed.”
Ellen Langer.

A question to reflect on
What assumptions about capability, ageing, and limitation are embedded in your HR policies, not just your culture?

Further reading
  • Livingston et al. (2024). Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission. The Lancet Commissions.
  • Langer, E. The Mindful Body.
 

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Work, Mind, and Cognitive Health

26/1/2026

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Part 1: How everyday work shapes long-term cognitive health

Lasting cognitive decline does not begin at retirement; it is shaped quietly across decades of working life by the environments, expectations, and practices people inhabit every day. Last year, joining the Dementia Compass Advisory Board has widened curiosity about cognitive health not only in later life, but across the working years.

One of the most striking convergences comes from the 2024 Lancet Commission on dementia prevention, intervention, and care and Ellen Langer’s The Mindful Body. Read together, they challenge three assumptions: that cognitive health is fixed, purely medical, and solely individual.

The science

The 2024 Lancet Commission estimates that nearly 45 percent of dementia cases worldwide could be prevented or delayed by addressing modifiable risk factors across the life course. Many of these are not abstract lifestyle choices but conditions intertwined with work: physical inactivity, social isolation, depression, hypertension, hearing and vision loss, and limited ongoing education.

The Commission argues for a life course approach: risk accumulates across early life, midlife, and later life, yet remains malleable throughout adulthood. Langer’s work adds that expectation, attention, and choice shape both cognitive and physical outcomes, reframing mindfulness as an environmental property: do people have opportunities to notice, distinguish, decide, and engage?

Seen through this lens, cognitive health becomes responsive to context, including workplace context.

Three workplace insights
When this science is viewed through a workplace lens, three insights stand out.
  • Work is a cognitive environment. It shapes how people direct attention, move, interact, and learn on a daily basis, often more than any formal wellbeing intervention.
  • Mid-career years matter. The years of highest workload, responsibility, and pressure are also the years when many cognitive risk factors are actively shaped, for better or worse.
  • Culture alone is not enough. What organisations signal through values can be undermined or reinforced by what they formalise through policy and process.
These insights move the conversation from individual resilience to the structure of work itself.

Policy as a cognitive lever
Culture is often described as “the way we do things around here”, but culture is sustained through policy choices, not intentions. Policies silently encode what an organisation believes about attention, energy, and capability.​

Some examples:
  • Job design and role scope
    Highly fragmented or overly standardised roles may optimise efficiency while reducing cognitive engagement. Policies that allow for role evolution, task variety, and problem-solving discretion support sustained cognitive activation.
    Micro-question: Where in your organisation have roles become more administratively dense than cognitively rich?
  • Learning and development
    When learning is framed narrowly around compliance or mandatory completion, its cognitive benefit is limited. Policies that value lateral learning, mentoring, and stretch assignments support the protective effects of ongoing education highlighted by the Lancet.
    Micro-question: How much of your learning budget goes to renewal versus reinforcement?
  • Hybrid and flexible working
    Flexibility can protect focus and autonomy, but without intentional social design, it can also increase isolation. Policies that address connection, not just location, matter for long-term cognitive health.
    Micro-question: Who is structurally more isolated when your flexible working patterns are mapped?
  • Workload and performance management
    Chronic overload increases depression and hypertension risk, both recognised contributors to cognitive decline. Policies that reward sustainable performance, not just output volume, send a different cognitive signal.​
    Micro-question: What, concretely, do your promotion decisions reward over a three-year horizon?
Seen this way, cognitive health is not an add-on wellbeing topic; it is a long-term outcome of how work is structurally experienced.

A quote to reflect on
“When we are mindful, we are actively making new distinctions. When we are mindless, we rely on old categories.” Ellen Langer.

A question to reflect on
What aspects of your organisation’s work design quietly support cognitive engagement, and which may be eroding it over time?

Further reading
  • Livingston et al. (2024). Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission. The Lancet Commissions.
  • Langer, E. The Mindful Body.



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Changing Behaviour at Work: A Reminder for the Year Ahead

12/1/2026

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PictureImage generated using ChatGPT
Introduction

As a new year begins and organisations reset their priorities, we often focus on what needs to change: new goals, fresh strategies, renewed expectations. But we rarely pause to examine the thing that will ultimately determine whether any of it sticks - behaviour. By behaviour, I mean specific, observable actions people take day to day, what they say, do, and how they interact, not general traits or feelings.

I recently listened to a session on behaviour change in organisations by Prof. Rob Briner (I am a huge fan of his work), and it put language to things I’ve instinctively believed for years. Behaviour is not a “soft” add-on; it is the work. As Daniels and Bailey put it, “All organisational results are the product of human behaviour.”

As organisations reach for new OKRs and bold ambitions, it is worth remembering that without revisiting the people practices and systems that shape everyday behaviour, very little will change. January is a natural reset point. Before we ask people to deliver more, collaborate more, or “be more proactive,” it is worth asking a simpler question: do we even know which behaviours matter, and are our systems designed to support them?

The Science

Psychological research in social learning and behavioural economics shows that environments cue behaviours more reliably than attitudes or motivations alone. From the webinar, I learned the following:
  • Specific, observable, measurable behaviours are what organisations should target, not vague categories like “be proactive,” “be collaborative,” or “show ownership.” These are pseudo-behaviours, you cannot change them because they are not behaviours.
  • Behaviour change in workplaces rarely requires digging into “root causes” like childhood, personality, or motivation. Instead, the evidence shows that changing aspects of the immediate environment is what shifts behaviour.
  • Changing attitudes does not reliably change behaviour. In fact, it’s often the reverse: changing behaviour can shift attitudes over time.
  • The Organisational Behaviour Management (OBM) model shows that behaviour is shaped by antecedents (what happens before), behaviour (what is done), and consequences (what happens after). Tweaking antecedents or consequences is more effective than launching new engagement campaigns.
This is consistent with decades of behavioural science:
  • Lewin’s field theory emphasised that behaviour is a function of the person and their environment.
  • Kahneman and Tversky demonstrated that environments consistently shape decisions more than we like to admit.
  • Duckworth and Gross (2020) highlight that despite numerous behaviour-change models, no single approach works everywhere - context is always king.
The challenge for organisations is twofold:
  1. We often target things that are not behaviour.
  2. We underestimate how much our systems shape what people actually do.

Key Findings
Drawing on the webinar, three insights stood out:

1. Many organisations are trying to change things that aren’t behaviour.
Examples: “be empathetic,” “be resilient,” “be more commercial.” These sound good but are not observable actions. You can’t influence what you can’t define.

2. Behaviour change requires clarity.
If we want better performance, we need to pinpoint the behaviours that drive it. For example, improving customer service in supermarkets wasn’t about “being helpful,” it was about three observable actions:
  • make eye contact,
  • smile,
  • ask customers if they need help.
Simple, specific, measurable.

3. Systems support (or sabotage) behaviour.
Antecedents (e.g., goals, instructions, feedback, resources) and consequences (e.g., praise, recognition, loss of opportunity) determine whether behaviours show up consistently. A beautifully designed strategy rarely stands a chance if the system - metrics, processes, rituals, leadership habits, pulls people elsewhere.
This is behaviour science 101: we get the behaviours we reinforce, not the behaviours we request.

What Does This Mean for Organisations in this Year?
January is a natural moment to start again, but we miss an opportunity if we only rewrite objectives and not the behaviours that will bring them to life.

Here are four practical opportunities for organisations to revisit:
1. Get clear on the behaviours that actually drive your goals.
Take one strategic priority and ask:
  • What behaviours would we see if we were successful?
  • Can we observe them?
  • Can we measure them?
If the answer is no, you’re not ready to implement the strategy.

2. Look at the environment, not the individual, first.
Instead of asking why people aren’t doing something, ask:
  • Do they have clarity?
  • Do they have cues?
  • Do they have the resources?
  • Are there blockers in the environment?
  • Are the consequences aligned with what we want?
Most “performance issues” are system issues in disguise.

Across very different industries, a few examples stand out:
  • Google (Tech): Introducing simple meeting norms such as equal speaking turns measurably improved team performance (Project Aristotle).
  • Heathrow Airport (Public Infrastructure): Etching a small fly into urinals reduced spillage by 80 percent - a micro-cue that transformed hygiene behaviour.
  • Call Centres (Service Industry): Synchronising break schedules increased collaboration and boosted productivity by around 20 percent (MIT Human Dynamics Lab).
  • Hospitals (Healthcare): Installing real-time feedback screens at ward entrances lifted hand hygiene compliance from ~60 percent to over 90 percent and reduced infections.
  • Microsoft Engineering (Technology): Introducing 15-minute daily paired code reviews reduced software defects by more than 60 percent.
Across sectors, the lesson is the same: change the system, and behaviour changes with it.

3. Reinforce progress, not perfection.
The behavioural model emphasises sub-goals and positive reinforcement.
People repeat behaviour that is acknowledged and rewarded, even in small ways.

4. Stop relying on attitudes or culture as the lever for change.
Engagement surveys are useful, but improving attitudes alone will not drive specific behaviours.
Culture, too, is not a cause of behaviour, it’s a description of behaviour. If you want to change culture, change behaviour first.

This aligns with the equity lens many organisations now explore. When people perceive inequity, in workload, recognition, pay, development, or opportunity, their behaviour shifts long before their words do. They withdraw, reduce effort, change their frame of comparison, or leave altogether (Adams, 1963).
Behaviour always tells the truth.

A Quote to Reflect On

“Behaviour change emphasises that it is changes in behaviour that cause changes in attitude rather than vice versa.”

A Question to Reflect On

If your organisation could only change three behaviours next year, which ones would make the biggest difference and what in your environment needs to shift to make them possible?
While focusing on behaviour is key, organisations must also address systemic barriers like workload, incentives, or leadership alignment, that affect people’s ability to act differently. Retention, performance, and culture ultimately come down to what people do every day. Design your systems so those behaviours are clear, supported, and consistently reinforced, and watch your organisation transform.
​
Further Reading
  • Corporate Research Forum. (2025). Behaviour Change in Organisations [Webinar].
    https://www.crforum.co.uk/research-and-resources/video-behaviour-change-in-organisations/
  • Daniels, A. & Bailey, J. (2014). Performance Management: Changing Behaviour That Drives Organizational Performance.
  • Duckworth, A. & Gross, J. (2020). Behaviour Change: An Integrative Review.
  • Kahneman, D. (2011). Thinking, Fast and Slow.
  • Adams, J. (1963). Equity Theory of Motivation.
  • Michie et al. (2015). The Behaviour Change Technique Taxonomy.
 

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A quiet closing for the year

29/12/2025

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Picture
As the year draws to a close, I have been reflecting on what has stayed with me from this year’s writing. Not the output, or even the topics themselves, but the ideas that seemed to resonate most deeply with readers, and with me.

Looking back across the 2025 posts on HR Unplugged, a clear thread runs through them: a growing curiosity about what is really happening beneath workplace behaviour. Less interest in surface explanations, more attention to the underlying mechanics.

Much of this year’s writing returned, in different ways, to the neuroscience of better workplaces. How people perceive fairness. How judgement is formed under pressure. How attention, threat, uncertainty, and cognitive load quietly shape decision-making long before policies or values have a chance to intervene. These posts struck a chord because they named something many people recognise but struggle to articulate: that work is experienced in the body and brain, not just on organisation charts.

A few reflections stand out.

Fairness is processed emotionally before it is processed rationally.
Several posts explored how quickly people register fairness or unfairness, often before they can explain why. The brain is constantly scanning for cues: am I safe, am I valued, does this effort make sense? When those cues are inconsistent, people adapt. Sometimes by disengaging, sometimes by conserving energy, sometimes by withdrawing trust. Rarely is this a conscious protest; more often it is a neurological response to perceived imbalance.

Judgement deteriorates when cognitive load is ignored.
Across the year, there was a recurring focus on how decision quality drops in environments that overload attention, rush choices, or reward speed over sense-making. Under sustained pressure, people default to shortcuts, habits, and assumptions. This is not a moral failure. It is how the brain copes. Organisations that ignore this reality often misdiagnose poor judgement as a capability issue, rather than a context issue.

Silence is a signal, not an absence.
Several posts examined moments where nothing was said, no challenge was raised, no resistance appeared. Neuroscience helps explain why. When speaking up feels risky, costly, or futile, the brain’s threat system does its job. People stay quiet to preserve energy and safety. Over time, those accumulated moments of silence shape culture far more powerfully than any single incident.

Work is shaped by accumulated moments of experience.
Not grand interventions, but repeated signals. The meeting where dissent is brushed past. The decision explained late, or not at all. The stretch expectation added without removing anything else. Each moment may seem small. Together, they train the brain on what to expect here, and how to survive.
What I take from this year is a renewed respect for how subtle workplace design really is. Behaviour does not change because we ask it to. It changes because the environment teaches the brain what is rewarded, what is risky, and what is pointless.

As the year closes, before turning to new ideas in January, this feels like a useful pause. A moment to reflect not on how hard people are trying, but on what their environments are repeatedly asking their brains to do.
And in HRunplugged style:

A Quote to Reflect On
“Every system is perfectly designed to get the results it gets.” - W. Edwards Deming

A Question to Reflect On
If nothing about your system changed next year, what behaviours would you confidently expect to see more of?
​
My wish for 2026 is a more thoughtful conversation about work. One that takes human limits seriously. One that designs for judgement, attention, and fairness, rather than assuming endless capacity.
Thank you for reading, reflecting, and staying curious with me this year. Wishing you a gentle close to the year, and a purposeful, well-designed 2026.
 


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The Practices That Strengthen Team Emotional Intelligence (Part 2)

15/12/2025

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Picture
Introduction

In part one, I explored the conditions that make team emotional intelligence possible: rhythm, fairness, purpose and psychological safety. These conditions create the emotional climate – the shared backdrop against which behaviour plays out. But climate alone is not enough. Without repeated practices, even psychologically safe teams slide back into old habits under pressure. Once the environment supports it, teams need practices that build the muscles of emotional intelligence in action.

This second part looks at the deeper practices that help teams read one another more accurately, regulate collective emotions and make better decisions under pressure. It builds on the Squiggly Careers episode, but extends it using insights from organisational psychology, neuroscience and collective intelligence research.
Team emotional intelligence is not a soft skill. It is a performance system. Druskat and Wolff describe team emotional intelligence as the set of norms that shape how a team becomes aware of, understands, and responds to emotions within the team and in its environment. Crucially, it is emergent: something the team does together, not the sum of individual traits.

The Science
Research on team emotional intelligence shows that high performing teams do three things exceptionally well:
  1. They manage emotions inside the team
  2. They manage emotions between the team and stakeholders
  3. They use emotional information to improve thinking, not avoid it

This builds on the work of Vanessa Druskat and Steven Wolff, whose studies show that team EI is not the sum of individual EI. It emerges from shared norms that guide how people express emotion, confront tension, repair breakdowns and stay connected.

Other strands of research support this:

Emotion Regulation (Gross)
Teams that know how to reduce unhelpful emotional spirals do better under stress. Naming emotions, reframing challenges and slowing the pace of discussion improve accuracy and reduce conflict. Gross’s process model of emotion regulation shows that reappraisal and response modulation change how emotions are experienced and expressed; at team level, shared re-framing and pacing serve the same function under pressure.

Collective Intelligence (Woolley et al.)
Teams with higher collective intelligence tend to have higher levels of turn-taking, social sensitivity and equitable voice distribution. In other words, emotional intelligence improves the team’s ability to think as a group.

Team Effectiveness (Hackman)
Hackman found that successful teams use norms to protect time, attention and relationships. Emotional intelligence supports these norms by reducing unnecessary interpersonal friction.

Social Identity Theory (Tajfel and Turner)
Teams that cultivate a strong shared identity interpret ambiguity as a collective challenge rather than a personal threat. This strengthens resilience and reduces blame. Social identity work suggests that when people experience a strong, valued in-group identity, ambiguity and setbacks are interpreted as ‘our challenge’ rather than personal threat, which buffers stress and blame spirals.
Together, these insights show that team emotional intelligence is a set of practices that support stability, clarity and joint problem-solving.

Key Findings
1. Teams become emotionally intelligent when they learn to regulate emotions together
Emotion regulation is often discussed at an individual level, but teams can regulate emotion too. Effective teams slow down when tension rises. They acknowledge discomfort rather than suppress it. They name what feels difficult so it can be worked with rather than worked around.
This shared regulation keeps thinking clear and reduces defensiveness. It also mirrors what happened in the Chilean rescue, where open acknowledgement of fear helped teams stay grounded under extreme pressure.

2. Social sensing improves performance
Research on collective intelligence shows that social sensitivity predicts team performance more than individual IQ. Emotionally intelligent teams consciously practise tuning in to one another. They pay attention to who has not spoken. They ask clarifying questions. They track group energy. These small acts reduce misinterpretations and help people feel seen.

3. Teams build emotional intelligence by strengthening repair, not avoiding rupture
High trust does not mean the absence of conflict. It means teams repair quickly and respectfully. Repair includes acknowledging hurt, clarifying assumptions and resetting expectations.
Repair was a core part of the miners’ underground resilience. It is also central to Edmondson’s work on teaming. Teams that repair well recover faster, collaborate better and show higher long-term performance.

4. Shared identity amplifies resilience
A team identity gives people emotional anchors when work becomes difficult. Druskat’s research shows that rituals and shared stories increase belonging and help teams regulate stress. The miners called themselves the 33 Musketeers. That story held them together. In workplaces, team identity can reduce siloed thinking and reinforce collective responsibility.

5. Teams need boundaries that protect attention and relationships
Hackman noted that team performance improves when teams protect their time and avoid unnecessary task switching. Emotionally intelligent teams are disciplined about what they say yes to. They protect their attention so they can protect the quality of their interactions. This is not emotional softness. It is emotional strategy.

What This Means

Leaders often ask how to build emotional intelligence in teams. The answer is found in repeated practice, not personality traits.
In practice, emotionally intelligent teams do the following:
  • Regulate tension together by naming emotions early, especially when pressure rises. e.g. ‘It feels like we’re getting tense – let’s pause for a minute and check what people are worried about.’
  • Increase social sensitivity by protecting equal voice and pacing discussions
  • Repair ruptures quickly instead of avoiding difficult conversations. e.g. a 10-minute follow-up where someone says, ‘That meeting felt off – did I miss something or step on a toe?
  • Strengthen shared identity through rituals, stories and consistent ways of working
  • Protect attention by setting boundaries that reduce noise and preserve connection

These practices help teams sustain clarity, compassion and cohesion. They move teams from individual performance to collective effectiveness. These practices do not remove all conflict or stress, nor do they replace structural fixes where workloads or incentives are misaligned. They do, however, give teams a way to stay connected and think clearly while those systemic issues are being addressed.
Emotional intelligence becomes something teams do together, not something individuals are expected to carry alone.

A Quote to Reflect On
“Teams do not become emotionally intelligent by accident. They do so by shaping norms that help them notice, interpret and respond to emotion in ways that strengthen performance.” Druskat and Wolff

A Question to Reflect On
Which shared practice would make the biggest difference to your team: regulating tension, strengthening repair, increasing social sensitivity or reinforcing team identity? What is one small experiment you can run in your next meeting to strengthen that practice?

​Further Reading
Druskat, V. and Wolff, S. Building the Emotionally Intelligent Team
Woolley, A.W. et al. Evidence for a Collective Intelligence Factor in the Performance of Human Groups
Edmondson, A. Teaming
Hackman, J. Leading Teams
Gross, J. Emotion Regulation Theory


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The Conditions That Make Team Emotional Intelligence Possible (Part 1)

1/12/2025

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Picture
Introduction

Listening to the Squiggly Careers episode on team emotional intelligence made me pause. Before any team can practise emotional intelligence, something more fundamental needs to be in place. The episode reminded me of the Harvard case study and article on the 2010 Chilean mining rescue. Thirty-three miners underground, hundreds of experts above ground, and a global audience watching. What looked like a miracle was actually a masterclass in how to create an environment where people can think, feel and act together.
​
It made me wonder: what kind of environment is needed before team emotional intelligence can exist at all?
This first part explores the conditions that make emotionally intelligent teamwork possible. Part two will look at the practical habits that build and strengthen it.

The Science

As this post was inspired by the Squiggly Careers podcast, we will use the definition shared in the podcast. Team emotional intelligence is defined in the Squiggly podsheet as the habits, routines, and norms that help a team work well together. However, those habits only stick when the environment supports them.

Several strands of research point to this:

Neuroscience
Predictable rhythms lower threat responses by reducing uncertainty, which calms activity in threat-related networks of the brain such as the amygdala and anterior cingulate cortex. In the Chilean rescue, twice-daily updates and shared briefings kept people calm and coordinated in a situation where uncertainty was constant.

Group resilience
Teams regulate through shared routines and fairness. The miners’ underground routine and collective decision-making preserved belonging and reduced panic. Although the Chilean rescue is a single case, not a controlled experiment, but it vividly illustrates principles found across resilience and team effectiveness research: routines, fairness, and shared purpose buffer stress and sustain coordination.

Collective intelligence
Studies on collective intelligence show that equal turn-taking and social sensitivity predict team performance more strongly than average IQ, reinforcing that voice and safety are cognitive assets, not ‘soft’ extras. Amy Edmondson calls this real-time learning, a form of teaming that depends on psychological safety.

Purpose and sensemaking
Shared purpose synchronises attention and mood. In the rescue case, every group had one goal. Purpose aligned their emotional tone and reduced unnecessary friction.

Together, the science shows that emotional intelligence is a social climate as much as an individual skill.

Key Findings

1. Rhythm creates emotional steadiness
Teams regulate better when communication has a consistent heartbeat. The Chilean rescue team relied on structured briefings to calm anxiety and focus attention.

2. Fairness builds trust
Equity signals safety. Whether underground rationing or workplace workload distribution, fairness strengthens connection.

3. Purpose reduces emotional noise
Shared purpose quietens conflict. When teams know why they are working together, irritations lose power.
​
4. Psychological safety fuels collective intelligence
Teams become more adaptable when it is safe to share doubts, ask questions and express emotion without judgement.

What This Means

Before encouraging emotionally intelligent behaviours, leaders need to shape the environment. In practice this means:

Create predictable rhythms. Regular check-ins, reflections and update cycles keep teams grounded. For example: a short, same-time weekly ‘state of the team’ check-in that always covers wins, worries, and priorities.

Be transparent and fair. Explain decisions, recognise effort and manage workloads openly.

Normalise emotion as information. Encourage naming frustrations or hopes without labelling them as weakness. For instance: ‘It sounds like there’s some frustration here – can we name what that’s about so we can problem-solve it.

Anchor the team in purpose. Remind people why the work matters, especially when pressures rise.

Model humility. Curiosity from leaders invites openness from teams.

Emotional intelligence grows when the environment makes it safe and possible.

A Quote to Reflect On
“There was no super-leader who had all the answers. We were playing with our cards open on the table.”
André Sougarret

A Question to Reflect On
What conditions in your current team help people connect and think together, and what is quietly working against it? What is one small rhythm or fairness change you could pilot in the next month?

Further Reading
Edmondson, A. Teaming.
Leonard, H., Edmondson, A., Rashid, F. The 2010 Chilean Mining Rescue (A).
Goleman, D. Emotional Intelligence.
Druskat, V. and Wolff, S. Building the Emotionally Intelligent Team.


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