NoDW #3: Developing the DAO Health Survey
The Newsletter of Decentralized Work: Data-driven insights on the world of decentralized work
In this edition:
Our feature article: Developing the DAO Health Survey
From the talentDAO community
Elsewhere in Web3
Developing the DAO Health Survey
An open-source tool for web3 organizational effectiveness
One of the key challenges facing DAOs involves running an effective operation using decentralized structures and procedures. The DAO model of organizing makes them attractive opportunities for skilled contributors, but when organizations fail to operate effectively, they become sick. Symptoms manifest in organizational attitudes, behavior, and culture that influence the organization’s ability to realize its potential. If not managed, these symptoms create negative feedback loops between worsening efficiency and worsening contributor experiences. This will eventually kill the DAO.
To diagnose and mitigate poor organizational health, psychologists developed empirically-driven psychometric surveys to measure the psychological factors that contribute to a healthy organization.
In the traditional scientific literature on predictors of healthy organizations, these same factors have been shown to predict outcomes such as turnover, staffing needs, productivity, performance, client satisfaction, and profit.  Predictors include positive organizational attitudes, engaged workers, supportive cultures, aligned values, and clear communication, among others. After reviewing the literature, we concluded that DAO Health can be sufficiently measured using similar psychometrics.
In partnership with the Ocean protocol, talentDAO is introducing our comprehensive DAO Health Survey – an empirically-driven psychometric tool to gain insights into the health of a DAO.
In this post, we provide details about how this tool was developed, how it should be used and understood, and what is next for talentDAO on our DAO Health initiative.
This write-up is organized as follows:
Operationalizing DAO Health: how we defined DAOs and DAO Health in order to measure them effectively.
Literature Review: a quick summary of how we conducted our review of the scientific literature to decide what to measure and how to design the survey.
Survey Design: a brief introduction to the survey, what it is measuring, how to use it, and a few other good things to know.
The Future of the DAO Health initiative: what is next for this initiative at talentDAO.
The DAO Health Survey is open-source and can be found on Github. Over time, talentDAO will conduct several studies to improve this measurement tool and new versions will be released.
Operationalizing DAO Health
When we talk about DAO Health, what we are really talking about is organizational health.
As researchers at McKinsey put it, organizational health is “...more than just culture or employee engagement. It’s the organization’s ability to align around a common vision, execute against that vision effectively, and renew itself through innovation and creative thinking. Put another way, health is how the ship is run, no matter who is at the helm and what waves rock the vessel.” 
It’s an elegant definition, and we would get away using it in any other context, but in order to come up with a way to properly measure DAO Health, we need a properly operationalized definition of a DAO.
After reviewing a wide range of literature on topics related to organizational health, organizational effectiveness, shared leadership, virtual teams, and worker well-being, we landed at the following operational definition: a DAO is a network of contributors coordinating in dynamic virtual teams toward a shared purpose by decentralizing authority and ownership.
With this as our framework, we arrived at the following operational definition of DAO Health:
The DAO's ability to coordinate teams toward a shared vision and objectives as a function of the contributor socio-psychological factors that drive collective productivity, performance, leadership, and individual experience and well-being.
Arriving at these definitions required consideration of the full range of organizational, behavioral, environmental, and structural factors present in DAOs.
Because DAOs come in many different shapes and sizes, some sharing many similar features with traditional organizations and others sharing few, they can be difficult to characterize. The technical conception of a DAO, based on the definition proposed by Ethereum co-founder, Vitalik Buterin , can be summarized as “automation at the center, humans at the edges”. Here, the only human tasks are the tasks that automation cannot do.
By Vitalik’s definition, many DAOs today would actually be DOs – ‘decentralized organizations’. But for today’s builders, DOs may not entirely reflect their ideals. The common denominator is the leveraging of blockchain technology. That is, the use of a custom-built protocol to function as the infrastructure for new technological systems. It may simply be that the range of human input needed to run all possible protocols was underestimated in Vitalik’s view. Alternatively, it was not at all anticipated that such strong connections would form within these networks, realizing in communities of active contributors eager to do more than just get rich off the next meme coin. Therefore, we retain the term ‘DAO’ in our definition as we feel it best reflects the current public interpretation regardless if it is a DAO or DO, by Vitalik’s technical definition.
Although they all vary in degrees of decentralization and autonomy, as human organizations, many DAOs operate within similar constraints. For example, the use of Discord as the dominant communication medium for DAOs, despite its criticisms, is largely recognized as standard practice. Similarly, the DAO ideology has created a culture of shared leadership, distributed functions, and high autonomy working environments sometimes dubbed 'permissionless' work.
With this in mind, we defined DAOs under the assumptions of human organizations.
Organizational Design theorist Richard Daft defines organizations as "social entities that are goal-directed, are designed as deliberately structured and coordinated activity systems and are linked to the external environment." 
Our view is that this definition of organizations holds for DAOs, albeit with different management models, cultural norms, and technical capabilities.
The activity and goal-directed behavior Daft is describing is the work – or ‘contributions’ in a DAO. These are the activities and behaviors performed to advance the organization's goals.
Our survey focuses on contributors, those doing the work and actively participating in the DAO’s goal-oriented activities. This includes paid and unpaid contributions as well as contributions from those with different membership statuses. However, this definition excludes people with DAO membership by way of financial backing or holding governance tokens solely, as well as presence alone in an open communication platform like Discord.
Unlike voting behavior or event attendance, the state of the contributor experience is not something that can be captured on-chain. If we aim to measure the health of a DAO, we must supplement on-chain activity metrics with off-chain “contributor metrics”.
We refer to contributor experience as an overarching term that encompasses a breadth of varying factors, each with its own moderating effects and various outcomes at each level in the organization.
Contributors provide talent, the collective human capabilities that add value to the organization and make up the working groups of the DAO, also referred to as 'guilds' or more generally, 'teams.'
From this perspective, there are three organizational levels our tool focuses on: individual, team, and organizational. We discuss the relevance of this classification further in the section on Survey Design.
Continue reading this article on Mirror.xyz
From the talentDAO community
As DAOs become a more dominant form of organization and collaboration, exploring how multiple DAOs can effectively collaborate becomes a worthy pursuit. talentDAO contributor George Gillette lays out the foundation for a system that aims to do just that using an HourDAO token and six different types of collaborators: Project Owners, Members, Investors, Judges, Leaders, and Agents.
Bounties play a critical component in DAO operations by enabling casual contributors of the DAO to complete valuable tasks without taking on a formal perpetual role. As a result, they also create a vector through which DAO operations can be disrupted either maliciously or by incompetence. talentDAO contributor Erik Van Winkle proposes a staking-based system as a way to thoughtfully manage that risk.
Crypto protocols coined the term learn-to-earn and popularized the concept. Yet most of its applications in the Web3 space are rather rudimentary. talentDAO contributor ItamarGo makes the case for why one of the bastions of Web2 thinking, corporate L&D programs, is ripe for learn-to-earn disruption.
Elsewhere in Web3
Simon Cicero offers a comprehensive playbook for founders on how to use web3, tokenomics, and the adoption of blockchain technology to take their ideas all the way from inception to exit-to-community.
There is a growing overlap in the idea spaces that DAOs and platform co-ops inhabit. Both forms seek to expand collective ownership and governance of digital infrastructure. Both have a culture that prioritizes collective control and the creation of shared goods. Austin Robey connects the dots on what each form of organizing can learn from the other.
The best DAOs actively nurture community well beyond the period of initial excitement towards a long-term sustainable culture. However, DAOs are encountering a number of issues on this path, with limited solutions at the moment. Zvi Band reviews the patterns behind this challenge and what leading DAOs are doing to build cohesion and culture today.
Co-creation of potentially patentable knowledge is a legal and relational minefield. In this Twitter thread, the MoleculeDAO team explains how IP-NFTs can help.
Is Flat for Everyone? Evidence from a Field Experiment of Structural Decentralization / Michael Lee & Paul Green
This paper has been causing heated debate in the web3 and future-of-work communities at large. Michael Yee & Paul Green’s field experiment led them to conclude that decentralization had no average effect on employee work experience (job satisfaction, engagement, and turnover intention) but improved the work experience of employees with high job-related ability and employees with strong a priori preferences for working in a decentralized structure. Conversely, they show that decentralization negatively impacted the experience of employees with low ability and weak preferences for decentralization.
If you’ve read this far, you’ve earned this beautiful visualization of the Web3 space from an evolutionary perspective, courtesy of Owocki