Codex Vitae

Buster Benson‘s

Codex Vitae

Is a fantastic idea and as a bonus, a great rabbit-hole-entrance to his writing in general.

Inspired by Robin Sloan’s Mr Penumbra’s 24-Hour Bookstore, he decided to attempt to write his own Codex Vitae or Book of Life, that represents everything he has learned in his life.

The Codex Vita starts by articulating several classes of beliefs: metabeliefs, perceptions, observations and predictions.

It then covers a set of topic and ideas that drives Buster’s worldview. And then his “personal canon”: articles and books that he was most inspired by, and his key writings.

The idea of creating such artifact as a tool for self exploration, reflection and personal growth strongly resonates with me. So much so that I have “forked” (sort of) Buster’s repo on GitHub and created my own branch here.

At the time of writing this post, it only contains the first pass at the (mathematical) intersection of his beliefs and mine. I hope to add to it in the coming weeks.


Codex Vitae

The “Future of Productivity” Series

Tiago Forte of Forte Labs wrote a wonderful 4-part series about the “Future of Productivity”.

Its title doesn’t do it justice, in my opinion at least, as it’s a much deeper treatise on the essence of human behavior, which has applicability well beyond the limited scope of productivity. Though much of this significance body of work  (~4,000 words each) is oriented around the overall goal of improving productivity, I’d argue that much of can either be used as-is or slightly generalized to be applicable for an even-bigger goal of living up to one’s full potential.

Part 1:  Productivity for Precious Snowflakes – discusses a mindset-driven approach for productive work and mastering it using four core skills: alignment, specialization, workflow and aggregation.

Part 2: Emergent Productivity: A People-Centered Equation for Modern Work – discusses the tensions between an employee and the business under the existing transactional paradigm, and the way they can be resolved under a new paradigm in which rather than viewing work as a common ground between the company and employees, employees are viewed as the common ground between the company and work. This simple switch leads to rather surprising outcomes.

Part 3: The Holy Grail of Self-Improvement – discusses Tiago’s take on habit formation and behavior change. It starts off with a few prominent behavior change framework like “identity-based habits“, but the more interesting part explores the notion of “emergent habits” under the assumption that human behavior is a complex (as opposed to a complicated) system. This leads to some thoughtful insights on the way behavior is shaped and habits can be formed.

Part 4: Meta-Skills, Marco-Laws and the Power of Constraints – discusses the core components of a self-knowledge based productivity improvement framework: meta-skills – skills that allow you to leverage other skills, macro-laws – fundamental axioms about yourself designed to guide the next phase of exploration and learning.

The “Future of Productivity” Series

From Engagement to “Skin in the Game”

Take a breath, this is going to be a long-ish post in the standards of this blog.

In this post, I’d like to explain why I think “employee engagement” and/or “employee satisfaction” are vanity metrics, that are likely to become a distraction from true improvements to organizational health. Don’t worry. It’s not all bad. I also like to propose an alternative path that’s more likely to lead to the end state we’re really optimizing for.

This is a 3-part piece: in the first part, I’ll present the thinking, mostly not my own, that led me to see this disjoint. In the second part, I’ll anchor it in some real world examples. Finally, I’ll propose an approach that I believe can take us closer to the right path.

Part I: What’s wrong with “employee engagement”?

I can’t remember what led me to discover this “ancient” (+20 years old) piece by Chris Argyris,  one of the fathers of the field of “organizational development”:

Good Communications that Blocks Learning

But ever since I did, I come back and re-read it quite regularly. Which is rather rare in my case, and a good indication that it contains some fundamental truth, that unfortunately is still far from being considered self-evident in the People Ops space. It’s a +6,000 words piece, that is well worth a thorough read, but I’ve quoted some of the most relevant parts to the discussion at hand below (emphasis is mine).

Chris makes his case known from the get-go:

Years ago, when corporations still wanted employees who did only what they were told, employee surveys and walk-around management were appropriate and effective tools. They can still produce useful information about routine issues like cafeteria service and parking privileges, and they can still generate valuable quantitative data in support of programs like total quality management. What they do not do is get people to reflect on their work and behavior. They do not encourage individual accountability. And they do not surface the kinds of deep and potentially threatening or embarrassing information that can motivate learning and produce real change.

And explains the false rationale more deeply:

In the name of positive thinking, in other words, managers often censor what everyone needs to say and hear. For the sake of “morale” and “considerateness,” they deprive employees and themselves of the opportunity to take responsibility for their own behavior by learning to understand it. Because double-loop learning depends on questioning one’s own assumptions and behavior, this apparently benevolent strategy is actually antilearning. Admittedly, being considerate and positive can contribute to the solution of single-loop problems like cutting costs. But it will never help people figure out why they lived with problems for years on end, why they covered up those problems, why they covered up the cover-up, why they were so good at pointing to the responsibility of others and so slow to focus on their own.

At the heart of the problem, is a false role design principle:

First, consider the way roles and responsibilities are assigned in manager-employee (or leader-subordinate) conversations, interviews, and surveys. There seem to be two rules. Rule number one is that employees are to be truthful and forthcoming about the world they work in, about norms, procedures, and the strengths and weaknesses of their superiors. All other aspects of their role in the life of the organization—their goals, feelings, failings, and conflicted motives—are taken for granted and remain unexamined. Rule number two is that top-level managers, who play an intensely scrutinized role in the life of the company, are to assume virtually all responsibility for employee well-being and organizational success. Employees must tell the truth as they see it; leaders must modify their own and the company’s behavior. In other words, employees educate, and managers act.

Which manifests itself in tools like employee surveys:

Employee surveys like the one Acme conducted—and like most other forms of leader-subordinate communication—have a fundamentally antimanagement bias whenever they deal with double-loop issues. They encourage employees not to reflect on their own behavior and attitudes. By assigning all the responsibility for fixing problems to management, they encourage managers not to relinquish the top-down, command-and-control mind-set that prevents empowerment.

This “positivity” also highlights more fundamental issues:

But this emphasis on being positive is plainly counterproductive. First, it overlooks the critical role that dissatisfaction, low morale, and negative attitudes can play—often should play—in giving an accurate picture of organizational reality, especially with regard to threatening or sensitive issues. (For example, if employees are helping to eliminate their own jobs, why should we expect or encourage them to display high morale or disguise their mixed feelings?) Second, it condescendingly assumes that employees can only function in a cheerful world, even if the cheer is false. We make no such assumption about senior executives. We expect leaders to stand up and take their punches like adults, and we recognize that their best performance is often linked to shaky morale, job insecurity, high levels of frustration, and a vigilant focus on negatives. But leaders have a tendency to treat everyone below the top, including many of their managers, like members of a more fragile race, who can be productive only if they are contented.

Chugging along with these attitudes in place, is simply not sustainable in today’s competitive reality:

Today, facing competitive pressures an earlier generation could hardly have imagined, managers need employees who think constantly and creatively about the needs of the organization. They need employees with as much intrinsic motivation and as deep a sense of organizational stewardship as any company executive. To bring this about, corporate communications must demand more of everyone involved. Leaders and subordinates alike—those who ask and those who answer—must all begin struggling with a new level of self-awareness, candor, and responsibility.

Bottom line: the focus on positive “employee engagement” / “employee satisfaction” further exacerbates the “employees educate, managers act” dynamics and the sense of learned helplessness of employees in dealing with organizational health issues.

Part II: Real world examples

Let’s explore two prominent trends in the PeopleOps space. Both are getting some serious attention in recent years and experience some notion of forward progress. But evaluated through Argyris’ double-loop learning lens, are we really making progress or still standing in place?

Employee engagement/satisfaction surveys:

Whether you use a tried-and-true tool like the Gallup Q12, decided to give an innovative startup like CultureAmp a try,  or opted to build your own home-brewed, most-likely-Google-Forms-based tool, the fundamental interaction design remains the same: you, the employee, should truthfully tell us what’s going on, and we, management, will solve these issues for you. Allow me to demonstrate with a few Q12 questions (my additions in italics, intentionally extreme/exaggerated to drive the point home):

  • You DO NOT know what is expected of you at work, but never asked your manger to clarify her expectations
  • You DO NOT have the materials and equipment you need to do your work right, but never asked for them
  • At work, your opinions DO NOT seem to count, but you never made an effort to articulate them clearly
  • Your associates or fellow employees ARE NOT committed to doing quality work, but you never referred a candidate to the company, or gave one of your peers honest feedback
  • You DO NOT have a best friend at work, but never made the effort to make one

To be clear, I’m not trying to make the case that these should all be problems for the employee to solve on her own – that would be just as senseless as making them purely the problem of management. I’m trying to show that the employee’s own behavior plays a critical role in both the problem and the solution.

360 Feedback

Again, the tool, be it Workday, Reflektive or your own home-brewed solution, doesn’t change the fundamental interaction design: you, the reviewer, should truthfully tell us/me what’s going on, and we (management)/I (the employee) are/is responsible for addressing it. Even in the more progressive setup, where feedback is shared/solicited directly to/by the employee, the dynamic stays the same: one side calls out the problem, and the other side is responsible for solving it.

Part III: Having “skin in the game”

The good news is that starting to move in the right direction, doesn’t require some dramatic change management effort, or a massive paradigm shift. The glass half-full of “a tool is only as good as the process it enables” is that it’s unlikely that you’ll have to throw your existing tool out the window, and have all those hours upon hours of implementation and adoption go to waste.

A small tweak to the interaction design can be a great first step. I’ve been contemplating how to label this tweak: “dyadic” sounds way too academic, “reciprocal” is not quite there. “Skin in the game” seems to be the closest, but I’m open to better label ideas. The idea is to model the interaction based on the fact that both sides are accountable for solving the problem, and they both have roles to play in the solution, albeit different ones (in most cases).

The pattern looks something like this:

  • The problem, why it’s a problem, and how much of a problem it is.
  • What I will do to make it better
  • What you can do to make it better

Consider the 360 feedback example I covered earlier:

  • “You could really use some work on your communication skills”


  • “You could really use some work on your communication skills. Here’s what I will do to help you work on them: <list of things that I will do> and here’s what you can do to work on them: <list of things that you can do>”

Which feedback is more likely to result in you improving your communication skills, and which one is more likely to end in inaction?

Would this require more from me as someone providing feedback? Absolutely! But to repeat the final words form the Argyris piece:

Leaders and subordinates alike—those who ask and those who answer—must all begin struggling with a new level of self-awareness, candor, and responsibility.

From Engagement to “Skin in the Game”

The two statistical tools that are worth paying more attention to

Data analysis is core to almost any role in the knowledge economy. We either do the analysis ourselves, on data that we collected, or try to learn from analysis done by others.

In both cases we are looking for insights – trying to find meaningful patterns in the data that have some functional use – for example: supporting a business decisions.

Many of us are able to tell apart an average from a mean, and have the similar image in our heads of a semi-shaded bell curve, when someone talks about a standard deviation.

But at least in my own case, it seems that I have left behind any functional understanding of deeper statistical concepts somewhere in my second year of undergrad. That is, until some well-intentioned past colleagues have taught me to know better. I’ve been grateful for them ever since.

Of a slightly more extensive list of tools and concepts, I’ve picked two that I view as absolutely critical to master, if we want to have any real chance of success in our quest to discern signal from noise:

Confidence Interval – measurement is an imperfect process. Focusing solely on point estimates coming out of a measurement exercise (average, mean, etc.) typically creates a false sense of certainty in the accuracy of those estimates. Confidence intervals show the reliability of point estimates, by specifying a range within which the parameter is estimated to lie,  given a required confidence level (typically 90%, 95%, 99%).

Two-sample t-test – behind the scary name lies a critical ideal. Comparative analysis is an essential part of almost every form of data analysis. Often times we care less about an absolute computed value in isolation, and more about understanding its significance in the context of other values. Be it measurement of the same parameter in a different time, in a different population or a different parameter altogether. The two-sample t-test enables us to determine, under a given required confidence level, whether two parameters are indeed different from one another.

Let’s connect these tools with more real world examples:

Suppose, that for whatever reason we’ve decided to run an “employee engagement survey” to regularly measure our employee engagement scores (why that’s a bad idea is a topic for a different time). It’s an overly-simplified survey where we simply ask employees to rate their engagement on a scale between 1 and 7.

We’ve decided that if, on average, we score less than 5 – it means we have an engagement problem and further action must be taken. The survey results came back and the average was 4.8. Should we drop whatever we’re doing right now and start figuring out ways to solve our engagement problem? Well, that depends. Depends on what? Depends on the reliability of that point estimate. How might we go about assessing that? Confidence Interval!

We also decided to slice the data by department. While the average score for the marketing department was 5.8, the average score for the engineering department was 5.3. Wow! This seems like a serious problem. Should we drop whatever we’re doing right now and start figuring out what’s going on in engineering that their engagement score is so much lower than marketing’s? Well, that depends. Depends on what? Depends on whether those two averages are indeed different. How might we go about assessing that? A two-sample t-test!




The two statistical tools that are worth paying more attention to

Solving Societal Problems 2.0

Through the joys of going down knowledge rabbit holes, I’ve discovered this recent gem by Yochai Benkler:

Yochai Benkler – Closing Remarks at OuiShare 2016

There are several thought provoking ideas in this short, 17 mins talk. I’d like to focus this post on a few key ones.

Yochai argues that the two core societal problems of our time are:

  1. Climate change the environmental degradation more broadly
  2. Increase in inequality and specifically the negative pressure that it creates on our democracies capacity for peace

Several of the most acclaimed solutions to these problems today are based on some core distributed technology. Be it: Uber, AirBnb, block-chain based applications or distributed energy generation.

In Yochai’s opinion, the use of distributed technology creates a false sense that the solutions are fully aligned with the long term solutions that they are attempting to address. While in fact, they are often time prone to one (or more) of three reactive forces that move them away from solving the problem that they’ve set out to solve in the long run:

  • The power of hierarchy, and specifically the threat of controlling positional power in the way that these organizations are structured
  • The power of property, acting as organizational force for oligarchy and the recreation of power around who owns it
  • The tyranny of the margin – the need to continuously compete and survive in the market, which end up postponing the ethical commitment (that the organization set out to address in the first place)

Yochai summs it up by saying:

“It is not enough to build a decentralized technology if you’re not making it resilient to reconcentration [of power] in the institutional, organizational or cultural level.
You have to integrate for all of them.”

Digging deeper into the structures and processes that can support such organization seems like a worthwhile endeavor. I definitely plan to keep an eye out for more evolved and flushed out articulations of such organizations.

Solving Societal Problems 2.0

PeopleOps – A Primer – Part 1: First Principles

This is the first part of what may (or may not) turn into a series of posts about some of the key ideas in the broad domain of People Operations.

It’s impossible to start with anything but first principles. When I first took an official PeopleOps role it was very clear to me that in order to make a meaningful impact, I would have to question some of the key assumptions behind the domain’s “best practices”. And questioning I have. The content below is the more academic version of the initial outcome coming out of this exploration process.

PeopleOps = Organizational Fitness

Patrick Lencioni coined the term Organizational Health by comparing it to a more well known attribute of an organization:

  • “Organizational Smarts”  – having expertise in strategy, pedagogy, technology, finance, marketing, etc. Intellectual horsepower of the organization.
  • “Organizational Health” – creating an environment with minimal politics, minimal confusion, high morale, high productivity, low turnover, etc.

It is the job of PeopleOps to drive organizational health, but that bar is too low. What PeopleOps is really responsible for is driving “Organizational Fitness” which means creating an environment that best enables the company to deliver on its mission. While the characteristics of organizational health are consistent across companies, the characteristics of organizational fitness vary according to the company’s mission.

Rather than spending a lot of work and time in explaining what is not working in the existing paradigm, I’d like to start with a different basic statement and work my way from there.

That basic statement is:

“organizations are selective, humanistic systems”

To understand it in full, we need to unpack each part of that statement.

Organizations as Systems

I’m using Ackoff’s definition of a system as a collection of at least two interdependent parts that serves a function. The parts can change their own behavior/properties, but the way each change impact the behavior of the whole, depends on the behavior of the other parts.

Ackoff’s also classified systems into 4 types based on whether the whole, and its parts, can display choice and purposeful behavior:

  1. Deterministic systems: neither the parts nor the whole can display choice. Example: a Clock – both parts and whole are completely mechanistic.
  2. Ecological systems: the parts can display choice but the whole cannot. Example: Nature – some parts of it (the animate parts – like people) can display choice. We can affect our environment, but the way the environment reacts to our actions is determined (though not always fully understood).
  3. Animate systems: the parts cannot display choice, but the whole can. Example: a Person – we can make choices, but our organs cannot – their behavior is determined in a similar way to the behavior of an engine in a car. They do not make choices.
  4. Social systems: both the parts and the whole can display choice. Example: Organization – but the parts (people) and the whole (organization) make choices.

This gives us the terms need to describe why more traditional approaches to PeopleOps failed: you cannot drive organizational fitness if you misclassify an organization into the wrong system type. And in a sense, in many cases, organizations were classified as animate systems at best and deterministic systems at worse, thinking about their employees more like machines than like human beings driven by choice and purposeful behavior.

Humanistic Systems and the Fundamental Organizational Challenge

Since we have a system consisting of humans (not machines) we need to figure out what what sets it apart.

First and foremost, we have self-interest – we get very little done with inertia, we need to be motivated to take action. Our behavior is also heavily influenced by our three major “bounds” (h/t Richard Thaler):

  • Bounded Rationality – our cognitive abilities are not infinite
  • Bounded Willpower – we sometimes take actions that conflict with our long term best interests
  • Bounded economic self-interest – we are not solely motivated by our economic self-interest. We also care about things like pride, fairness, and the greater good

These bounds sometime cause us to behave “irrationally” or make mistakes.

This notion of having self-interest leads us to the fundamental organizational challenge:

Maintaining organizational fitness requires continuous management of the tension between the needs (self-interest) of the organization and the needs (self-interest) of the individual

What motivates us?

The key to managing this friction requires looking at is from a humanistic perspective – through the eyes of the employee rather than through the eyes of the organization.

To do that need to start by understanding what is driving our self-interest? What motivates us?

We first need to take into account that the nature of work is changing.

For simplicity sake, we can divide work into two distinct types:

  • Deep (heuristic) Work: Cognitively demanding tasks that require you to focus without distraction and apply hard to replicate skills. Such tasks typically require open-ended problem solving, experimentation and novelty.
  • Shallow (algorithmic) Work: Logistical style tasks that do not require intense focus or the application of hard to replicate skills. Such tasks can often be completed by following a checklist.

As more and more shallow work is being automated, outsourced or offshored, work is shifting to become more heavily weighted towards the deep type. In this type of work, intrinsic motivation is the only type of effective motivation.

Dan Pink’s framework is a good starting point. Dan argues that we are motivated by:

  • Purpose – work that supports a cause greater than yourself
  • Autonomy – acting with choice (different from independence)
  • Mastery – becoming better at something that matters

PeopleOps Strategy

Our strategy is then derived out of these drivers:

  • Purpose through Intellectual Alignment – on-going clarity on the strategic direction of the company and how it ties to the day-to-day activities that each employee owns
  • Autonomy through Behavioral Cohesion – a shared set of core principles that we all adhere to (reinforced through key levers) creates the trust necessary to enable autonomy
  • Mastery through Professional Development – make professional growth a top priority in everything we do


Now we can turn to the last (first) part of our basic statement (“organizations are selective, humanistic systems”).

The greatest advantage an organization has over a country is its ability to select its members.

People naturally like to form ‘tribes’ where they experience a sense of belonging. The concept of being inside or outside the group is probably a byproduct of living in small communities for millions of years, where strangers were likely to be trouble and should be avoided.

While certain kinds of diversity (gender, background, experience, education, etc.) tend to produce interesting and productive work environment, other kinds of diversity (beliefs, life priorities, etc.) tend to produce a lot of ugly strife.

This derives the fourth component of our PeopleOps strategy – Disciplined Selectivity.

Our individual ability to influence who gets to be part of of the organization (sourcing, screening/interviewing and letting go) is one of the most important responsibilities that we have as employees, and necessitates an approach that is methodical, data-driven and bias-free.

Levers of Proactivity

Organizational Fitness doesn’t happen on its own as both time (social entropy) and size (Dunbar’s number) work against it.

This is where the more well-known tools come into play:


  • Org structure
  • Incentives – primarily as they pertain to the notion of fairness, and the few edge cases where extrinsic incentives were found to be effective (more on that in Part
  • Processes & Programs
  • Knowledge management – both pull (repositories) and push (communications)


In Sum

It is PeopleOps mission to drive organizations fitness,  

Knowing that organizations are selective, humanistic systems,

We promote purpose, autonomy, mastery and belonging.

Through intellectual alignment, behavioral cohesion, professional development and disciplined selectivity,

Using org structure, incentives, process & programs and knowledge management.


PeopleOps – A Primer – Part 1: First Principles

Phyles and Neo-Medievalism

The August newsletter contained this contemporary gem this weekend:

End of Nations: Is there an alternative to countries?  by Deborah MacKenzie

Which immediately connected in my mind with Jon Evans‘ latest piece:


[in searching to it, I also came across another piece of his, touching the same theme, published just a couple of months before the MacKenzie piece]

The oddity of nation states is one of my earliest original intellectual thoughts that I seem to remember. There are very few events in my life that I remember so vividly: standing in the indoor porch of my grandmother’s house, sometime in my early teens, expressing my first contrarian thought on a topic as abstract and unprompted as “whether nation states make sense”.

It’s recently been on my mind a lot, after a colleague gave me Neal Stephenson‘s The Diamond Age (which Evans references in both his posts) as a going away gift before stating my new job.

While Stephenson’s phyles seemed like an interesting idea, trying to address some of the structural, systemic deficiencies of nation-states, it still felt outlandish, and as science-fiction-y as a novel idea can be.

Which made MacKenzie’s piece a joy to read, as she takes a much more pragmatic approach to solving the same problem, anchored in both history and and modern scientific discoveries. She is able to chart a path towards a post-nation-state reality which seems more possible and achievable.

If you bore with to this point, you may ask yourself: what does all of this has to do with organizations and org design? (the key themes of this blog.)

The answer is: a lot.

In many progressive, future-of-work pieces, the way traditional organizations are managed and led is often compared to monarchies and dictatorships with the CEO as the (hopefully benevolent) dictator or ruler at the top. An argument is then often made to use the more modern governance approaches, currently used by democratic nation-states, as blueprints for re-imagining the way organizations should run.

Reflecting on this topic in recent months made me wonder whether we may be setting the bar too low. Rather than trying to catch up with nation-states in the way we run our organizations, perhaps we should try to leap-frog them instead?

If we are already trying to lead a governance revolution, perhaps MacKenzie’s Neo-Medievalism is a better role model to aspire to than the modern nation state?






Phyles and Neo-Medievalism