Human Systems Stewardship: Insights & Navigation

*If you haven’t yet, I encourage you to read the first piece in this series, titled “The End of Human Resources,” as it lays the groundwork for what’s to come over the next few months. [Parts 2, 3 & 4 of the series are available now]

Have you ever worked for one of those organizations that win a “Best Employer” award and thought, “How is that possible? This is the most toxic place I’ve ever worked! Have they met my manager, the devil incarnate??”

On paper, the organization appears to be thriving. Employee engagement scores are strong, the eNPS score has improved, and targets are being met. In short, the dashboard is green.

Meanwhile, no one speaks honestly in meetings, the same concerns keep coming up in exit interviews, and employees are bad-mouthing leadership every chance they get. In short, people are miserable.

So which signal should we trust?

This question sits at the heart of why I’ve always struggled to fully embrace the employee engagement survey.

Organizations are gathering more information about working life than at any other point in history. We measure engagement, satisfaction, retention, productivity, well-being, burnout, culture, belonging, trust, and everything in between. Every organization I’ve worked for either conducts an engagement survey, wants to conduct one, or believes the answer to their current challenges can be found in one.

My response has almost always been some variation of, “Okay, but it probably won’t give you the answers you’re looking for.”

It’s not that I dislike data, employee voice, or measurement itself. Human systems are extraordinarily complex, and understanding them requires information. What’s always made me uncomfortable, however, is the confidence with which organizations interpret these results, as though a single survey, administered once or twice a year, could accurately capture something as dynamic and complex as human experience.

Survey results feel incomplete and, to a certain extent, dishonest. They seem almost disconnected from the reality people experience every day.

One of the most useful concepts to articulate this disconnect was recently introduced to me by Des Kennedy, who likens corporate culture to meteorology. (Watch this space → Applied Creativity Substack for more to come on this topic.)

Meteorology is the scientific study of weather. It measures temperature, pressure, precipitation, humidity, and wind in order to understand what’s happening in the atmosphere at a particular moment. Climatology studies something quite different. Climate is not what we experience when we step outside on any given day; it’s the long-term pattern that emerges over time from thousands of observations, interactions, and changing conditions.

Weather is immediate. Climate is cumulative. You feel the weather. You infer the climate.

In a corporate environment?

A difficult meeting is weather. A resignation is weather. A conflict between colleagues is weather. An engagement score is weather. It represents a single reading taken at a particular moment in time: one number, one dimension, one observation. It tells us something about the formal system on that day, but very little about the conditions that produced it.

Culture, trust, psychological safety, leadership credibility? Climate. The unspoken rules, political dynamics, assumptions people carry, and the accumulated experiences that shape behaviour make up organizational climate.

Meteorologists don’t rely on a single temperature reading to understand the atmosphere, and organizations shouldn’t rely on a single survey score to understand culture. Pulse surveys, stay interviews, exit interviews, and engagement surveys all contribute valuable observations. None of them, on their own, explains the climate producing what they measure.

The problem isn’t measurement; it’s our tendency to mistake measurement for understanding.

Insight & Navigation

Insight & Navigation is the fourth system within Human Systems Stewardship because organizations can’t adapt to realities they can’t perceive.

Every strategic decision, cultural issue, leadership challenge, market disruption, technological change, or emerging risk depends on an organization’s ability to understand what’s actually happening both inside and outside its boundaries. The future will inevitably present conditions the organization has not previously encountered, and its ability to respond depends less on the amount of information it has and more on its ability to interpret what that information means.

Trust & Governance explored power.

Care & Belonging explored humanity.

Growth & Evolution explored capability.

Insight & Navigation explores reality.

More specifically, it explores how organizations perceive reality, construct meaning, distinguish signal from noise, and ultimately decide what they believe to be true.

The Insight & Navigation System

Every insight is only as sound as the picture of reality it’s based on. Think of this as the system responsible for how organizations make sense of reality and ultimately determine what they believe to be true.

Insight & Navigation determines:

• whether data creates discernment or false certainty

• whether weak signals are noticed or ignored

• whether difficult truths can be safely expressed

• whether multiple forms of evidence are considered

• whether stories and narratives are examined or repeated

• whether assumptions are challenged or protected

• whether emerging risks become visible early enough to matter

• whether decisions remain connected to reality

At its core, this system asks:

How does this organization know what is true?

Truth inside organizations rarely exists within a single metric. It emerges through patterns, contradictions, stories, relationships, observations, quantitative and qualitative information, and lived experience. Usually, it first appears as a weak signal…maybe it’s a recurring pattern, or a discrepancy between what people say and what they do.

The capability this system develops is discernment.

Discernment is the ability to distinguish signal from noise, symptoms from causes, weather from climate, and information from insight. It’s the ability to recognize emerging patterns, integrate competing information, challenge assumptions, and remain curious when confidence is the easier option.

Today’s organizations hold extraordinary amounts of information at a scale unimaginable even a decade ago. Yet they continue to be surprised by turnover, declining trust, resistance to change, burnout, leadership failures, and emerging risks. This suggests that information alone doesn’t necessarily produce understanding.

In other words, organizations are highly informed but poorly oriented.

Data creates an illusion of certainty, and dashboards create an illusion of understanding. Metrics become substitutes for curiosity. Numbers carry greater legitimacy than lived experience. Leaders aren’t investigating the conditions that produce outcomes; they’re just managing the indicators themselves. The result is an organization that believes it fully understands itself while increasingly losing contact with reality.

And, just like with the previous human systems, this is where AI enters the chat. AI is remarkably effective at identifying patterns across large quantities of qualitative and quantitative information. It can surface themes, identify anomalies, detect emerging issues, and connect information that would be difficult for humans to process at scale. AI creates capacity; it expands our ability to observe.

But while AI may dramatically improve our ability to observe the weather, understanding the climate is still fundamentally a human responsibility. The interpretation still belongs to people.

When Insight & Navigation functions well, organizations become better at noticing what others miss. Weak signals become visible. Contradictions become useful. Difficult truths become discussable. Data doesn’t replace judgment; it informs it. Emerging risks become easier to identify, and decisions become more grounded in reality. Organizations become less certain, but considerably more accurate.

This is ultimately why organizations need both meteorology and climatology. We need ways to observe what’s happening today, but we also need the ability to understand the longer-term patterns that produce those observations. Surveys, dashboards, exit interviews, customer complaints, AI analytics, and financial reports all tell us something about today’s weather. Insight & Navigation is the system that explores what kind of climate those observations describe.

In Practice

When Insight & Navigation functions well, it shows up structurally as:

• narrative sensemaking sessions

• organizational listening practices

• multiple forms of evidence

• qualitative and quantitative analysis

• truth-telling mechanisms

• climate assessments, not isolated measurements

• organizational retrospectives

• scenario planning and foresight work

• ethical uses of analytics and AI

• cross-functional interpretation of information

• regular examination of assumptions and dominant narratives

These practices determine whether information remains fragmented or develops into discernment, whether organizations repeatedly encounter the same problems or develop the ability to recognize patterns before they become crises.

Many organizations currently rely on annual surveys, quarterly dashboards, and periodic assessments to understand themselves, yet human systems rarely operate on those timelines. Meaning evolves through countless interactions that occur between measurements.

The weather changes every day. Climate is inferred over time.

Engagement surveys, pulse surveys, stay interviews, exit interviews, culture assessments, and people analytics all provide valuable signals in this system, but they’re only one source of information in a much broader process of organizational sensemaking.

The Literacies Required to Steward This System

As with the previous posts in this series, I've intentionally resisted relying on the same handful of management thinkers that appear on most leadership reading lists. Understanding human systems requires multiple ways of knowing, diverse lived experiences, and perspectives that too often get left out of organizational conversations.

Human systems produce quantitative information, qualitative information, stories, emotions, relationships, assumptions, patterns, contradictions, and weak signals. No single discipline captures all of that.

Stewarding this system requires literacy in:

• Systems thinking

• Narrative intelligence

• futures literacy

• Information Ecology

• human-centered analytics

• AI ethics

• design justice

• qualitative inquiry

(Please note that some recommendations are repeated. Human systems are interconnected, and many of these thinkers contribute to multiple systems.)

1. Systems Thinking

Systems thinking is the ability to understand that organizational outcomes rarely result from isolated events. They emerge from relationships, feedback loops, incentives, structures, and patterns interacting over time.

Recommended Reading:

Donella Meadows: Thinking in Systems ← click here

A practical introduction to systems thinking that helps readers move beyond events and begin recognizing the underlying structures producing organizational behaviour.

• Key Takeaways From This Work:

  • Events are usually symptoms, not causes.

  • Feedback loops shape behaviour over time

  • Lasting change comes from understanding system structure, not isolated problems

2. Narrative Intelligence

Narrative intelligence is the ability to recognize that organizations make decisions not only through data, but through stories. Every organization carries narratives about success, leadership, culture, risk, and identity that influence what people notice, ignore, and believe.

Recommended Reading:

Douglas Rushkoff: Team Human ← click here

A thoughtful exploration of how stories, technology, media, and power influence the way humans make sense of the world. Particularly useful for recognizing how organizational narratives shape decision-making.

• Key Takeaways From This Work:

  • Stories influence behaviour as much as data

  • Technology should strengthen human judgment rather than replace it

  • Relationships remain central to good decision-making

3. Human-Centred Analytics

Analytics should help organizations become more curious, not more certain. Human-centred analytics recognizes that data represents people, relationships, and lived experience rather than abstract numbers.

Recommended Reading:

Ruha Benjamin: Race After Technology ← click here

A critical examination of how data, algorithms, and technology can reinforce existing inequities while appearing objective. Especially valuable for questioning what organizational data measures and what it misses.

• Key Takeaways From This Work:

  • Data is never completely neutral

  • Technology often reflects existing power structures

  • Objectivity should always be questioned, not assumed.

4. Design Justice

The way information is collected, interpreted, and acted upon is never neutral. Design justice asks who benefits from existing systems, who is excluded, and whose experiences become visible.

Recommended Reading:

Sasha Costanza-Chock: Design Justice ← click here

A compelling exploration of how systems, technologies, and decision-making processes can unintentionally reinforce exclusion, and how more participatory approaches create better outcomes.

• Key Takeaways From This Work:

  • Design decisions reflect values.

  • Those closest to the problem should help shape solutions

  • Inclusion improves the quality of organizational insight

5. Futures Literacy

Organizations rarely fail because they lack information about the present. More often, they struggle because they continue interpreting the future through assumptions that no longer fit reality.

Recommended Reading:

Jamais Cascio: Facing the Age of Chaos ← click here

Essential reading that digs into uncertainty, foresight, and how organizations can develop greater adaptability in rapidly changing environments.

• Key Takeaways From This Work:

  • The future can’t be predicted, but it can be explored

  • weak signals often matter before obvious trends

  • Better questions produce better strategic decisions

6. Information Ecology

Information doesn’t exist in isolation. It’s shaped by context, relationships, incentives, power, and interpretation. Information ecology is the study of how organizational knowledge is created, shared, filtered, and ultimately used.

Recommended Reading:

Neil Postman: Technopoly ← click here

A valuable examination of how cultures can become dominated by information and technology while losing sight of wisdom, judgment, and human values.

• Key Takeaways From This Work:

  • More information does not automatically produce better decisions

  • Technology changes how people think, not just how they work

  • Wisdom requires interpretation, not simply accumulation

7. Algorithmic Literacy

Algorithmic literacy is the ability to recognize that data, algorithms, and artificial intelligence are not neutral. Every system reflects the assumptions, values, priorities, and biases of the people who designed it.

Recommended Reading:

Safiya Umoja Noble: Algorithms of Oppression ← click here

An important examination of how search engines, algorithms, and digital technologies shape what we know, what we see, and ultimately what we believe. Especially valuable for understanding why organizational data should always be interpreted critically instead of accepted as objective truth.

• Key Takeaways From This Work:

  • Algorithms reflect human values and biases

  • Data should inform judgment, not replace it

  • Critical thinking becomes more important as AI becomes more capable

What This System Requires of Organizations

Insight & Navigation can’t depend entirely on annual surveys, quarterly dashboards, leadership intuition, or increasingly sophisticated analytics tools.

Organizations must intentionally develop:

• listening capability

• interpretation capability

• narrative capability

• truth-telling capability

• foresight capability

• discernment capability

Organizations are unlikely to eliminate ambiguity, uncertainty, or complexity. The objective is to become better at navigating them.

What would it look like to build organizations that are as committed to understanding reality as they are to controlling it? Start paying attention to which signals get taken seriously, which forms of evidence are dismissed, and who ultimately gets to decide what counts as truth.

The final of the five interconnected systems within Human Systems Stewardship is Guardrails & Integrity, but in many ways, it’s only the beginning.

Once we’ve explored that final system (coming sometime in the next week or so), we get to the part of this series I’ve been both looking forward to and dreading. As I wrote in the first post, The End of Human Resources, if Human Systems Stewardship is going to mean anything at all, it can’t just sound compelling in theory; it has to work in practice. The first five systems establish the foundation, but the next step is to determine whether that foundation can actually support a different way of organizing work.