from "The Purpose Engine: How a Hidden Network of Employees Drives Company Success"

How do you measure what truly makes an employee valuable? Is it the number of sales they close, the lines of code they write, or their annual performance score? For years, we’ve relied on these direct, individual metrics, but in any large organization, we know that’s not the whole story. Some people just make everyone around them better. They are the glue in a team, the bridge between departments, the quiet mentors who elevate the entire system. Their contribution is a ripple effect—what I nerdily call “higher-order productivity”—and it’s a massive driver of success that has remained almost impossible to measure…

…unless you’re a mad scientist.

Back in 2017, I was given an unprecedented opportunity to collaborate with a company of nearly half a million employees on a fascinating question: “What is the single largest driver of productivity inside our organization that we are not currently tracking?”

To answer this, I had to invent a new way of seeing the company. We treated the entire organization, hundreds of thousands of employees, as a single, massive brain. Using three years of anonymized data—email and chat, project assignments, and even bluetooth-measured contract tracing from thousands of volunteers—we mapped the company's “digital functional connectivity”. With this we could see who was talking to whom, how information flowed, and how collaborative structures formed and dissolved.

With this functional connectivity map, we developed a model inspired by the AI that powers deep learning. We looked at high-level successes—like a project finishing ahead of schedule or a business unit exceeding its targets—and traced the credit for that success backward through the network, identifying how individual employees (network units) contributed to these positive ripples—what’s known as credit assignment by backpropagation in machine learning. By carefully controlling for an individual’s own performance metrics, the model isolates the value they added to the system around them. In short, I could finally measure—messily and imperfectly—an employee’s invisible, systemic impact.

The results were staggering. This untracked, higher-order value was not distributed evenly. In fact, it followed a stark power law: a tiny fraction of the workforce, just 11% of employees, were responsible for over 80% of this hidden value-add. While most employees had a neutral systemic impact, and a sizable group had a slightly negative effect (acting as communication bottlenecks or creating friction), this small group of high-impact individuals was a force multiplier, making everyone they interacted with more effective.

The next step was hunting for the driver of this impact. Standard personality traits like conscientiousness or agreeableness have correlations but were only weakly predictive. Instead, the defining behavior was what I call “small sacrifices.” The big higher-order value-add workers were the ones who would spend extra time helping a colleague on their team but also on other teams and even entirely unrelated groups. They might improve a shared database that no one asked them to or proactively share knowledge that wasn't directly related to their own tasks. They acted as bridges between disconnected groups and were hubs of collaboration.

When we correlated this behavior with extensive psychological data from surveys and even the text of anonymized employee diaries, one factor emerged as the dominant predictor, dwarfing all others: Strength of Purpose (SoP).

Strength of Purpose is a deep, internal commitment to a goal that is bigger than yourself. Crucially, this wasn't about believing in the corporate mission statement. These individuals had their own personal sense of purpose and found ways to connect their work to it. This inner drive fueled the "small sacrifices" that benefited the collective, even without any immediate personal gain. Their actions weren't driven by rational self-interest but by a desire to contribute to something meaningful.

And the economic impact was profound. Our model estimated that this purpose-driven, higher-order productivity accounted for 13% of the company's total productivity.

But here lies the tragic paradox. Because this value was invisible to traditional performance reviews, the company was systematically failing to recognize its most impactful people. Individuals with high systemic value but moderate traditional scores were less likely to be promoted and significantly more likely to leave the company. Companies are losing some of its most valuable talent because of our bias to measure things that are easy to measure.

These findings have urgent implications. As AI automates routine tasks, the uniquely human contributions—collaboration, mentorship, and purpose-driven problem-solving—become the core of human value-add. This work shows that "purpose" isn't a soft, feel-good concept; it is also a hard, quantifiable driver of economic value. It challenges us to rethink how we hire, manage, and reward people, urging us to look beyond the spreadsheet and learn to see the invisible network of purpose that truly powers an organization.

Research Roundup

Higher-Order Productivity II

What makes a great manager? For me, the ultimate measure is higher-order productivity: the best managers lift everyone around them.

New research on “200,000 white-collar workers and 30,000 managers over 10 years in 100 countries” provides concrete numbers on this lift. Estimating the value-add of the top 30% reveals that good managers produce “large and persistent gains in workers' career progression and productivity”.

Seven years after a good manager takes over a team, those “workers earn 30% more and perform better on objective performance measures”. In fact, with a company “doubling the share of good managers would increase output per worker by 61%”.

These findings complement my own research which finds that about 11% of workers drive nearly 80% of higher-order, predominately via simply helping coworkers…even when there is no obvious benefit to themselves. Making others better isn’t just the job of managers.

Trust is a Dish Best Served Luke Warm

Your office thermostat might be sabotaging your team's collective intelligence.

We know smart teams are more than the sum of their parts, but we often forget that collective intelligence’s messy nonlinearity can depend on context.

When “programmers were randomly assigned to work individually or in pairs under warm (29°C/84°F) or control (24°C/75°F) conditions”, heat…

> “had no effect on individual performance”

> “but impaired team performance”.

The heat didn't make people lazy; it made collaboration harder.

The most critical finding was that this “negative impact was strongest in heterogeneous teams” teams. The cognitive load of managing physical discomfort taxed the brain's prefrontal cortex, leaving fewer resources for the demanding work of building trust. The well known "diversity boost" to collective intelligence was effectively cancelled out by the temperature.

This isn't just about heat. It shows how hidden stressors—like physical discomfort, emotional load, or time pressure—silently compete for the mental resources required for great teamwork.

The takeaway: Protecting your team's performance means managing not just the work, but the context in which the work gets done.

The Good & The Cool

What makes someone "cool"? Why would this be different from what makes someone "good"?

You may have seen a new global study in which nearly 6,000 people across a dozen countries were surveyed on “cool” and “good”. The results show that “many of the attributes associated with cool people are also associated with good people”, but there were differences.

https://psycnet.apa.org/record/2026-30402-001

Cool evoked more perceptions of “extroverted, hedonistic, powerful, adventurous, open, and autonomous”, while good evoked more a more “conforming, traditional, secure, warm, agreeable, universalistic, conscientious, and calm” ideal.

These distinctions held steady across a surprising expanse of cultures: “Australia, Chile, China (Mainland and Hong Kong), Germany, India, Mexico, Nigeria, Spain, South Africa, South Korea, Turkey, and the United States”

It’s important to see clearly that this study isn't about objective psychological profiles; it's about our subjective perceptions of others. While our brains passively create these social constructs based on our experiences, we can be active crafters of our beliefs.

It disturbs me that “good” people are perceived as relatively conformist and the cool among us are free to be hedonists but get a pass of conscientiousness. I choose: powerful and calm; adventurous and secure; autonomous and universalistic; open and conscientious. This paradoxical mix—the capacity to lead boldly and build responsibly—is the engine of genuine human potential.

SciFi, Fantasy, & Me

It makes sense that a generation raised on Harry Potter would produce an entire subgenre of Dark Academia. It’s given rise to some wonderful stories (Gideon the Ninth!!) but they all suffer from the very question they explore: why the hell would anyone willingly condemn their kids to these abattoirs? HP started as a children’s fable—it didn’t need to make contact with reality. But later books and the genre as a whole suffers from the unreality not of magic but of cultural norms.

The Incandescent isn’t free of this foundational problem, but its world still feels whole where so many others feel like a parable or skin-deep stageplay. Having an adult teacher as the POV helps give it a grounded feel, even as the demons and spells play out in that increasingly familiar English Private School setting. The Incandescent works without being dark academia wonk and without leaving me constantly wondering, “Why would they do this to themselves?”

Stage & Screen

• August 18, Qatar: What's next: Human-AI Collective Intelligence
• September 18, Oakland: Reactive Conference
• Sep 28-Oct 3, South Africa: Finally I can return. Are you in SA? Book me!
• October 6, UK: More med school education
• October 11, Mexico City: maybe...I hope so!
• October 29, Baltimore: The amazing future of libraries!
• November 4, Mountain View: More fun with Singularity University
• November 21, Warsaw: The Human Tech Summit
• December 8, San Francisco: Fortune Brainstorm AI SF talking about build a foundation model for human development

Vivienne L'Ecuyer Ming