This is another great piece by Manuel Küblböck, author of “How we make decentralized decisions” which I covered here:

How we align our goals

The post outlines the way a shared map of enabling constraints, at different abstraction levels, can be used for balancing maintaining alignment and enabling autonomy at the same time. 

It covers a lot of ground, and addresses a few subtle issues towards the end of the post that I’m deliberately omitting from this summary. It’s a fairly visual piece and I’m going to play a bit with the way that I’m presenting the content to make it even more so. 

 Goals, used in this context to mean “what I/we want to achieve”, can be defined at various levels of abstraction. By asking ourselves “why?” we move to a goal at a higher level of abstraction. By asking ourselves “how?” we move to a goal at a lower level of abstraction. 

Attaining a higher abstraction goal requires either a longer timeframe or a bigger scope to complete it, or both. A standardized set of units of time, and a standardized set of units of scope create a calibrated canvas to which goals can be anchored. Different organizations may choose different units of time and scope for their alignment efforts. 

Each goal we define constraints goals further down and to the left. The constraint enables autonomy at the level below by providing clarity on the boundary between what we’re doing and not doing. Boundaries don’t have to be precise, just clear enough so everyone has a sufficient understanding of where they are. 

Alignment efforts, therefore, focus on the diagonal area in the middle of the canvas. The area at the top left is too detailed, and the area at the bottom right is too vague to merit defining and aligning on. 

Goal types fall on a spectrum between the aspirational and the practical, and differ in the mechanisms that are used to formulate them: 

• Intentions describe what we aspire to achieve. Typically formulated as a vision (what is the future we are trying to create) and a mission (what we do and for whom). 
• Outcomes describe what we effect through what we do. Typically formulated as objectives in OKRs, or more fine-grained user stories in a product backlog. 
• Outputs describe what we are going to produce. Typically formulated using specifications. 
• Inputs describe how much time and effort we want to invest. Typically formulated using timeboxes like 2-week iterations or the number of hours that’ll be spent investigating a bug.

More practical goal categories can be used to describe goals at lower levels of abstraction. The different level of abstraction also create natural boundaries for assigning ownership: 

• Foundation: The reason we are all here and contribute our efforts. The founders of an organization usually define this.
• Direction: This is the top-level direction from the most senior leaders. It is solely bounded by the foundation and not by any higher-level desired outcomes.
• Coordination: This is where desired outcomes across organizational scopes are coordinated.
• Autonomy: The part fully left to the teams who execute it. Teams break down desired outcomes into outputs and inputs.

The heart of the alignment effort takes place in the coordination zone. Perfect alignment on a desired outcome requires clarity not only on the outcome itself but also on: 

• How progress will be measured? 
• What will be produced to make progress? (outputs) 
• What will be needed to make progress? (conditions) 

A healthy process strives to maximize outcome and progress while keeping outputs and conditions flexible.

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After the initial inception, where the map of goals inside the zone of alignment is defined, on-going alignment takes place at the edges of the relevant time-boxes.

At the end of a time-box, the map is consulted to review what goals were achieved, as well as what progress was made towards the goals at a higher level. If the map doesn’t match reality, opt for adjusting the scope and keeping timeboxes fixed. A goal may be discontinued altogether if it is no longer desirable. 

At the beginning of a time-box, the goals for the time-box are defined (planned). This is another place to check for the relevancy of the goals one abstraction level above, to make sure that progress is made towards a goal that still matters. 

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The rest of the post adds some additional color around the choice of time-frames and units of scope, how efficiency and effectiveness can be described using these building blocks, at which level of accuracy to maintain the map, the order of describing output ingredients, leadership and accountability, expectations and happiness and the timing of committing to a goal (or deferring commitment). 

While examination and reflection are, sadly, not common staples of most operating rhythms in most organizations, there is a fairly wide consensus around the importance of continuously evolving the way we work together to the long-term success of the business, and its ability to continue to attract and keep its talent. Efforts on this front are usually labeled as managing “employee engagement” (or one of its derivatives) though I like the simpler label of “Working on Work” (WoW) to describe the efforts undertaken to improve the way we work, as opposed to efforts that are doing the work itself.

The traditional approach tends to follow a semi or annual cycle of running a survey, compiling the results and defining initiatives to address the gaps/opportunities identified. My goal in this piece is to highlight four big opportunities to make this approach significantly more effective. 

One aspect that I’m intentionally leaving out of my analysis is the frequency of the cycle. I believe that shorter, more frequent reflections should be integrated into the operating rhythm in places where they don’t exist today, but I don’t think that they are a full replacement for this cycle. Some patterns take longer to be observed and some changes take longer times to be affected. Therefore, there is value in this form of macro reflection on this cadence, plus or minus a quarter. So with this short disclaimer, let’s jump in. 

Approach: From “one and done” to “continuous improvement”

WoW is a never-ending, “continuous improvement” effort. And yet, it is often approached as if it is a problem that can and should be solved with a one-time effort. There is an absolute benchmark for what “good enough” looks like, often on a 5-point scale, and a view of “success” as showing an improvement in scores from one period to the next. As if when we’ll score all 5s we’ll be done and can fire half of our HR staff…

A continuous improvement approach starts at a different point: accepting the perpetual nature of the effort, it will define a distribution of our overall capacity to do work between “doing work” and “working on work” that can be refined or adjusted from one period to the next. The systems for managing work and managing WoW will be integrated, where at the moment the latter seem to mostly fall outside the capacity and direction efforts used for the work itself (OKRs, budgets, etc.). The sensing/reflecting piece of the cycle will be oriented more towards setting the right direction for the efforts rather than measuring progress. More on that shortly.

Sensing: From ”false precision” to “focus and patterns”

Current sensing efforts collect evaluations using a 5-point Likert scale, and analysis consists of comparing the scores either across demographics or time periods. The absolute numerical score opens the door for false precision and misinterpretations of the scores. Many organizations tend to walk through that door. 

On a more tactical level, it shows up as over-reaction to changes in the scores that are not statistically significant. On a more strategic level, it shows up as inferring causality between intervention and outcome where only correlation exists. Did our new employee recognition program led to the increase in scores from the last time? Or was it the changes in personality dynamics in our employee base due to all the new hires? Or perhaps, the announcement we made yesterday about winning that big multi-million dollar contract? Unless we have a way to control for everything else that’s changed or happened at the same time period, it’s unlikely we’ll be able to determine causality with any degree of certainty.

Sensing oriented towards “focus and patterns” avoids the absolutes and reduces the risk of misinterpretation. It looks to order the different potential areas of focus from “the one we should focus on the most” to “the one we should focus on the least” since the goal is now limited to figuring out what we should do next. It also places more weight on a different attribute of the data: looking at its variability both quantitatively and qualitatively to inform how to target a potential change/intervention. Low variability in the top area of focus suggests an organization-wide opportunity that should be matched with an organization-wide change. High variability suggests that things are working well in some areas but not others, requiring a more local change and pointing to good places where potential answers might be found.

Implementation: From “initiatives and projects” to “systems and mindsets”

Reactions to insights surfaced in the sensing phase tend to take the shape of initiatives and projects, often as part of the HR team roadmap, in the best cases in collaborations with the executive team and managers. But those tend to ignore the power of existing organizational systems in shaping existing behaviors and perceptions. Efforts to improve collaboration will likely fail as long as individual performance bonuses are in place. Efforts to improve quality will likely fail as long as targets/goals only measure throughput and cost. The more tangible will always trump the less tangible. Furthermore, efforts tend to focus on the external environment, ignoring the powerful impact that mindsets and internal beliefs have on driving change. Yes, my manager has a part to play in me “knowing what’s expected of me in my role” (a common engagement question). But so do I. Have I sought out clarity if the expectations were unclear to me? If I haven’t, why? What underlying beliefs led to my inaction? How can I test them out and weaken their hold on me?

More effective courses of action will focus on long-lasting changes to both systems and mindsets over temporary initiatives or the addition of yet-another-program.

Ownership: From “not my job” to “everyone’s job”

We like to say that culture, a fuzzy label for the thing we change when we’re WoW is “everyone’s job”. Yet that is hardly reflected in the way traditional cycles are run, perpetuating the dichotomy observed by Chris Argyris’ 25 years ago: “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”. If only HR has capacity allocated towards WoW — real change is unlikely to happen.

An alternative will posit that everyone has “skin in the game” in both things being the way they are right now, and in changing them. That means that everyone must have an opportunity to both recognize their part in causing the current tension and playing an active part in addressing it. That does not mean that everyone should be involved in WoW in the same amount or in the same way. Specialization is the secret sauce of effective collaboration, but it needs to be bounded. When pushed to the extreme, rigid boundary, it becomes detrimental. Working on work should never be an extracurricular activity, bolted on top of an already full plate of the work itself, for any role in the organization.

As readers of this blog already know, I’m constantly on the lookout for innovative compensation approaches. “How to redistribute the value generated by the organization to the people who created it?” is one of the most profound organizational questions. And financial compensation is one of the most tangible indicators of our values and beliefs systems. Any attempt to shift to a new operating paradigm without taking these two issues into account is bound to fail.

Over the last several years, Nicolas di Tada and the team at Manas Tech, a 30-person Buenos Aires-based dev shop, have carefully evolved their process for allocating pay raises. Not only did they document and share their process in:

Salary compensation without intermediation

But Nicolas was also kind enough to hop on a call with me a few weeks back and clarify some of the points that were not clear to me at first read.

In a traditional compensation review process, an autocratic decision-maker (manager), uses quantitative inputs from a performance review to set a new salary according to a predefined salary ladder. The team at Manas sees challenges, bias and limitations in all three key “design elements” mentioned above, so they set out to design a compensation review process without them. The key design principle underlying their system posits that the “wisdom of the team” would lead to a superior outcome than a process using the three elements outlined above.

Their process currently works as follows:

• Every 4 months, the team will review its automated financial model to determine the portion of profit that should be allocated as salary increases. If confidence in future billable hours is lower than desired, the same amount will be allocated as one-time bonuses rather than permanent salary increases.
• The process runs in 3 to 5 rounds (exact number determined at the beginning of the cycle).
• In each round, each team member sees the base salaries of all other team members, and the total pool of salary increases that can be allocated. They can then allocate it across team members in any way they see fit. Team members cannot give themselves a raise.
• At the end of each round, the average increase that each team member received gets permanently allocated to them and subtracted from the overall pool.
• The next round follows the same steps with team members also being able to see the cumulative salary increases that were already permanently allocated to each team member, and the updated (lower) total salary increase pool still remaining to incrementally allocate.

An interesting challenge from a technical/algorithmic perspective has been dealing with the “fuzzy” relationship between an individual team member’s input/recommendation for a salary increase and the resulting increase, since the recommendations of all other team members have to be factored in as well. It creates an incentive to provide an input that’s different than the outcome that you think is appropriate, in an attempt to account for the impact of the other inputs.

In order to get as close as possible to the desired outcome, the solution that the Manas team landed on after multiple iterations is to only permanently allocate the average recommended increase and run several rounds of the process.

While the process does offer a unique solution to some of the greatest challenges of the more conventional approaches, it does pose its own set of challenges. The two that immediately come to mind are scalability and market dynamics.

The solution works well now for Manas at ~30 people where most people know most people well enough. But what happens where there are 200 people in the org? Simply averaging the increase recommendations in each round will require a lot more rounds since a smaller portion of teammates will have a non-0 recommendation for each individual teammate. Potential solutions can be either finding a more permissive “discounting function” that’ll require fewer rounds, or potentially following a tiered process where execs allocate the overall pool across departments, managers allocate the departmental pool across teams, and individuals allocate the team pools across individuals. Each of these comes with its own set of advantages and disadvantages.

The market dynamics tension is a bit more challenging to resolve and the Manas team hasn’t found a one-time systemic solution to it. If we evaluate the Manas approach through a “compensation polarity” lens, their approach falls very close to the “internal fairness” pole. Since compensation market data and market seniority definitions (levels) don’t play a part in the process, it’s not unlikely for salaries to drift overtime from their market comparables and have someone in a role where they are being paid either significantly above or below what they would get paid for doing a similar role in a different company.

In sum, I’m grateful for Nicolas and the folks at Manas for taking a pretty big leap, redesigning a compensation system from scratch breaking many of the challenging assumptions in a more conventional system. It is not perfect and not without its shortcomings, but neither is the existing system, making it a viable alternative offering a plausible trade-off.

This one was a tough one to parse through but contained some sold gold nuggets that made it worth it. This post is a synthesis of two posts by Joost Minnaar, one of the two founders of Corporate Rebels:

How To Organize A Large Company Without Middle Management

4 Future-Proof Organizational Models Beyond Hierarchy And Bureaucracy

To the best of my understanding, they are the product of Joost’s Phd thesis where he’s exploring the way progressive organizations are choosing to organize in a way that minimizes hierarchy and bureaucracy, which he dubs as “middle managerless organizations” or MMLOs for short. While I wish the research methodology was more rigorous than case studies, Joost did aim to extend the robustness of the sample of organizations studied, from the mid-sized US-based core to include also large-sized and international organizations. 

The label “middle managerless” still seem rather hyperbolic to me, but both the problem framing, and the patterns/archetypes he identifies in the applied solutions are rather interesting. 

The organizing problem 

Building on his academic literature review, Joost defines “organizing” as solving three intertwined problems: 

1. Strategy — the problem of organizing the strategic direction of the company and related objectives. This was traditionally done by a top-management team defining short-term (monetary) goals, and now while the structure is unchanged, the management teams tend to be smaller and focus more on defining long term objectives and curating the organizational culture as a means for steering strategy. 
2. Division of Labor — organizing “vertically” in the company. This is broken down into Organizational Structure — the problem of decomposing the objectives set by top management into tasks and roles, traditionally done by the introduction of hierarchy (functional departments, etc.); and Task Allocation — the problem of assigning these tasks and role to employees, traditionally the responsibility of middle management. 
3. Integration of Effort —  organizing “horizontally” across the company This is broken down into Coordination — the problem of providing employees with the information they need in order to coordinate their actions with peers, traditionally done by middle management by introducing a set of rules and procedures (“bureaucracy”); and Motivation — the problem of monitoring the performance of employees and distributing rewards for the tasks they have performed, traditionally done by middle management which assess performance and allocates rewards. 

I like this construct a lot. The one thing that doesn’t fully sit with me is grouping “motivation” under “integration of effort”, but it may just be the behavioristic language that’s used to describe it. When I use simpler, more succinct language it seems to fit better: 

Solution patterns

Since the focus of the research is on the role that middle managers play in organizing and its alternatives, the solutions focus on the “vertically” and “horizontally” aspects of organizing where middle managers play a key role.

In addressing the “vertical” organization problem Joost identified two key approaches that differ in the way they think about the smallest organizational building block. The first views individuals as the basic building block, who then form ad-hoc teams who emerge and dissolve organically. Individuals can be part of one or more of those teams at the same time. Most Holacratic/Sociocratic systems that champion the separation of “role and sole” adopt this approach. Whereas the second views teams as the basic building block, where people self-organize into permanent teams and individuals can only be part of a single stable team at a time. 

In addressing the “horizontal” organization Joost also identified two key approaches that differ in the way the “rules of the game” for coordination between building blocks are defined. The first adopts a more collaborative approach emphasizing a sense of community, belonging and a shared mission. The second adopts a more competitive approach by introducing an internal market system for coordination, oftentimes placing a financial value on transactions and services rendered by one building block to the other. 

The combination of the “vertical” and “horizontal” organization approaches creates 4 organizational model archetypes: 

• European Model — Permanent teams, collaborative dynamics. Companies like NER Group, FAVI, and Buurtzorg as the primary examples. Though it’s also easy to see how Spotify fits that model. 
• Asian Model — Permanent teams, competitive dynamics. Haier being the leading example.  
• American Model — Ad-hoc teams, competitive dynamics. Companies like W.L Gore, Morningstar and Valve. 
• Digital Model — Ad-hoc teams, collaborative dynamics. Mostly common in open-source projects where the collaborative motivation is non-financial like: Wikipedia, Linux and (former) GitHub. 

Just like any 2×2, the real world is more complex, with multiple “hybrid” companies that fall in various places on the spectrum between these extremes. Companies may also move along on the spectrum over time, Zappos being one interesting example moving from the “American Model” to the “Asian Model” and breaking the naming convention in the process 🙂 Nonetheless, this seems like a super useful taxonomy for codifying different organizational patterns.