The Elements of Value

Neat framework by Eric Almquist and the team at Bain:

The Elements of Value

Eric and team decomposed the fuzzy term “value” (to a customer) into a set of 30 “elements of value” organized in a Maslow-inspired pyramid consisting of 4 main categories: functional, emotional, life-changing and social-impact.

the elements of value

To test whether elements of value can be tied to company performance, specifically customer advocacy (as measured by NPS) and revenue growth rate, they’ve asked 10,000 survey respondents to give 50 US companies a 1-10 rating on each value element.

According to the Bain team, companies that received an 8+ rating on 4 or more value elements by at least 50% of the respondents, had an NPS score that’s 4 times higher, and a revenue growth rate that’s 3 times higher than the ones who received an 8+ rating on a single value element.

The team was also able to show that some value elements matter more than others. Specifically that quality trumps all other value elements, and that the other most important elements change from industry to industry.

Given the lack of details on the research methodology, I’m hesitant to derive any conclusive insights from the study itself. The most valuable thing the Bain team produced, in my opinion, is the taxonomy itself, which can be used as an effective scaffolding to drive clarity in conversations around new product development, marketing, consumer insights, etc.


The Elements of Value

PeopleOps: A Primer – Part 3: Fair Monetary Compensation

This is the 3rd part of my PeopleOps series. Part 1 can be found here.

Start with Why

Monetary compensation for work has been a key component of any people system for quite some time now, ever since the vast majority of people realized that slavery is not the best of ideas…

It had gradually evolved in structure and purpose: from a purely mechanistic structure using time-based components (hourly wages) to incorporating more humanistic components such as loyalty (tenure) and individual contributions (pay-for-performance); and from a pure enabler of sustenance, to an enabler of more refined drivers of motivation aimed at accomplishing higher needs in Maslow’s hierarchy. Monetary compensation is a powerful tool in an organization’s toolbox for improving the organization’s ability to make progress on its mission. In this piece I’d like to make the case for why many so-called progressive compensation systems end up missing that mark, and propose an alternative approach for designing more effective compensation systems.

Meet “incentive pay”- “pay for performance”’s evil twin

There are very good intentions behind the “pay for performance” idea: since individual performance in a given role can vary significantly, this variation should also be reflected in the compensation system. However, in many progressive compensation systems, this idea has devolved into a more simplistic notion called “incentive pay” – a “sticks and carrots”-based approach for improving motivation by offering a monetary reward in return for completing a (short-term) objective such as closing a deal, finishing a project, hitting some KPI or more broadly “crushing it” in a certain role. Unfortunately, research has a few things to teach us about “incentive pay”’s ineffectiveness (at best):

  • Ineffective motivator:

    “The failure of any given incentive program is due less to a glitch in that program than to the inadequacy of the psychological assumptions that ground all such plans. […] Do rewards work? The answer depends on what we mean by “work.” Research suggests that, by and large, rewards succeed at securing one thing only: temporary compliance. When it comes to producing lasting change in attitudes and behavior, however, rewards, like punishment, are strikingly ineffective”  — Why Incentive Systems Cannot Work, Alfie Kohn 

    External incentives were found to be ineffective in driving long-term behavior change. In some cases they were even found to diminish productivity. They tend to crowd-out intrinsic motivation, crush creativity, foster short-term thinking, and become addictive. If true behavior change is what we seek – external incentives are not the answer.

  • Increases tolerance of low performance:

    “In a firm which makes extensive use of individual performance rewards, it is often the case that the firm’s reaction to a mediocre or average performer is to say “That’s ok, you can stay — we’ll just pay you less.” This is hardly a recipe for excellence! […]Firms with individual performance-based reward systems often end up tolerating wide varieties of performance” – True Professionalism, David Maister

  • Improving the part doesn’t improve the whole:

    “If you give a manager a numerical target, he’ll make it even if he has to destroy the company in the process.” -W. Edwards Deming.

    A system purely based on individual performance leads to attempts to game the system, take shortcuts, and more troubling unethical behavior. It erodes relationships and reduces collaboration. People will sometimes throw their peers under the bus (only figuratively, let’s hope) just to meet their personal objectives.

  • Fosters a critical attribution error: “no man is an island” cannot be truer in our modern work environment. If you’re a door-to-door salesman, selling cleaning supplies out of a catalog, perhaps you can argue that your contribution to the business can be fully isolated and separated from the contribution of your peers. Therefore, some incentive scheme based on your contribution can be considered as “fair”. But can you make the same argument if you’re selling software to enterprise clients? When each deal is unique and the sales process typically involves more than a handful of people directly and dozens indirectly? Can a successful sale truly be attributed to one person and not the rest? Would the contribution of each of them be identical in each of the deals they contributed to?

Fairness is the name of the game

Hopefully by now we are in agreement that pay-for-performance, as implemented in most progressive compensation systems has a significant, undesirable adverse effect. So how can we take a step forward without having to take two steps back in designing an alternative system?

We first need to take into account that, yes, individual performance varies, and the compensation  system should reflect that. But we also need to take into account that, as discussed in part 1, the work shifts from shallow (algorithmic) to deep (heuristic), intrinsic motivation is the only effective motivation, so external incentives and “sticks and carrots” approaches are simply ineffective motivators.

We cannot ignore the fact that compensation will have some impact on motivation.

But in order to ensure that is has the desired effect, we need to stop thinking about compensation as a direct driver of motivation, and start thinking about it as an indirect driver of intrinsic motivation, through the values that are reflected in the compensation system itself. To use the framework we introduced in part 1, compensation should be thought of as a lever for driving Behavioral Cohesion rather than a lever for driving Intellectual Alignment. First among those is fairness. When we feel that we are compensated unfairly, our motivation takes a big hit. Let’s unpack what this means.

A better compensation system

Fairness is a relative term, as it is a determination coming out of a comparison of two or more things. In the context of a compensation system, we can think about fairness across 4 different dimensions / areas of comparison:

1. Market

Organizations are open systems and people have the freedom to choose to leave one organization and join the other. There is a market for talent, through a rather inefficient one, so prices get distorted. This is not just a problem of asymmetric information. Even if we had a perfect data set of everyone’s compensation information, making a fair comparison will be challenging since neither people nor companies are commodities, so it’ll never be an apples-to-apples comparison, both literally and figuratively. And we haven’t even talked about compensation components whose value cannot be determined with certainty like stock options…

All of this is not to say that market prices should be ignored. The absolute prices should be viewed as important but very loose guardrails. Whichever proxy was chosen for the market price, it’ll be hard to argue that even a ±25% variation is unfair since the measurement error is probably greater than that.

Market prices play a more critical role in the fairness realm when it comes trends. If market prices are changing year-over-year for a certain role, the compensation system should reflect that trend as well.

2. Personal needs and preferences 

Different people have different needs and different personal preferences.The extent to which those are reflected in the compensation system is another dimension of fairness, though a very subjective, cultural-dependent one. This is not as an outlandish an idea as it may sound, even in a capitalistic society: our tax code provides incentives for marriage and childbearing; extended paid family leave is becoming mandatory in more and more states; more companies given their employees some control over their base/upside compensation mix to reflect their personal risk preferences; cost-of-living adjustments are becoming a more fairness-driven debate as companies become more global.

3. Contribution/value to the company – This is the dimension with the most lowest hanging fruits w/r/t fairness, if we can replace “incentive pay” with a better solution. The key attributes of such solution are as following:

  1. Focus on the contribution to the long term success of the company. This goes beyond the short term performance of the individual to also include other supporting behaviors such as driving behavioral cohesion (values fit) or helping others improve their performance. Loyalty, which is often implicitly manifested in the compensation system (paid time off is a good example) should we be evaluated through this lens and either be reflect proactively or left out.
  2. Quantify the contribution through a set of levels, manifested through a set of ladders for each material function or group of roles. Ladders are likely to differ from one another on the attributes that define performance, due to the varying natures of different roles, but should share the same attributes on the other dimensions of contribution.
  3. Loosely couple levels with role (some degree of movement up the ladder is possible without a movement in the organogram), and fully decouple levels from management (management = different ladder). This breaks the unhealthy tight coupling between an increase in compensation and movement up the org.
  4. Consistent “above level” contribution merits a promotion to the next level and an increase in compensation.      

4. Success

This is the flip side of contribution/value to the company. When the company is doing well / succeeds – employees compensation should increase.

When should comp change?

Finally, looking at a compensation system as a driver of fairness, not only gives us good guidance on how compensation should be set, it also, and perhaps more importantly, gives us guidance on dynamics of compensation.

Compensation should change, if and only if:

  1. Market prices change (or:)
  2. Individual needs change (or:)
  3. Career ladders or levels change (or:)
  4. Company performance changes


I’m going to add here answers to some relevant questions I’ve been asked on this topic.

What about “salary bands”? How do they fit in? 

The short answer is: they don’t. Let’s keep in mind how “salary bands” came to be. They were a pressure valve in a world in which base compensation:

  • Was not responsive to changes in the labor market
  • Was tightly coupled to role

In a world where this is no longer the case, and compensation changes due to the 4 drivers listed above, it’s unclear that they still have a role to play.

Furthermore, often times they were used as a tool to implicitly reward loyalty/tenure: “this person has been in this role for a while and have been doing a good job, so I can give them a bump as long as they are “within band””. But if you value loyalty/tenure — why not make it an explicit component of your compensation formula rather than have it be a part of an opaque, subjective “band”?

This candidate that we want to close demands a significant higher comp than the one we can offer her at this level. What do we do? 

The short answer is: we don’t hire her. The more nuanced answer is we should ask ourselves two important questions first:

  1. Is there reason to believe that there was a significant surge in the market and we should adjust all of our salaries upwards to match it? If the answer is no, then we shouldn’t hire her.
  2. Are we leveling her correctly? Can we make a strong case for why we have good reason to expect that she will be able to contribute more to the business and therefore we should higher her into a higher level with a resulting higher comp? If the answer is no, then we shouldn’t hire her.

If we reflect back on the 4 drivers that our compensation system consists of, it’s easy to see how different companies would value (and therefore compensate) the same person differently. A company that’s already in the “printing money” stage should offer high comp (equity included). That doesn’t mean that you should match it.

PeopleOps: A Primer – Part 3: Fair Monetary Compensation

Participatory Organizations: An Overview & Taxonomy

Christopher Allen put together a wonderful collection called:

Participatory Organizations, Patterns, Processes & Tools — An Overview & Taxonomy

There seems to be an interesting uptick in using GitHub as a system of record for some of these great resources, which is probably a topic for a different blog post.

But in any case, not a lot of color to add to this piece. To some extent, it can be thought of as an extension of the “Solving Societal Problems 2.0” piece from a few weeks back, as it offers a trove of additional resources to those of you interested in taking a deeper dive into the world of participatory org.

At a more meta level, the focus on patterns rather than practices is really interesting. Perhaps this is a better way of getting at what I was trying to highlight with Heuristics vs. Best Practices and being able to separate true/deep understanding of the system/environment and a “theater of practices” that exist only on the surface.


Participatory Organizations: An Overview & Taxonomy

Time Management > Task Management

I recently had an interesting insight, that upon reflection, may actually be a real-world example of a Minimum Valuable Problem issue.

A few months ago, a CEO of an early-stage company was asking me for feedback on the idea of adding “task management” features into their MVP product. My feedback was: “Don’t. It’s a super-crowded space, and nobody is close to getting it right. You’ll just create confusing overlap with existing tools that your users already use”.

The “nobody is close to getting it right” was based mostly on intuition, driven by more than a decade of experience with various tools. But at the time, I could not articulate what is it exactly that everybody is “doing wrong” or what “getting it right” may look like. I believe I can now.

Serendipitously, as I was getting ready to write this piece, I came across this one-sentence post by Jeff Weiner:

Jeff W

What most tools often miss is that what we really need help with is managing our time. Successfully managing our tasks is a byproduct of successfully managing our time. We cannot successfully manage our tasks if we’re not successfully managing our time, because, guess what, if we don’t have time to do the work, we cannot get the task done.

I think the folks at Plan, which I’ll get to in a moment, got it 100% right, arguing  that a big part of the problem is the direct replication of physical tools into digital tools:

“We’ve taken the solutions that worked in the 60s and 70s — paper to-do lists, desk calendars, notebooks — and replicated them online and on our phones. If you want to try to “get organized” today, it takes a ton of manual effort, discipline, and, most importantly, time to do it regularly.”

And I’d argue that the same applies to more professional tools such as the Gantt Chart (invented circa 1910) and the Kanban Board (developed as part of the Toyota Production System between 1948-1975).

As we break away from the “production line” type of tasks, and tackle more open-ended problems that require experimentation and creative problem solving, our time becomes our scarcest resource and the hardest one to manage.

Fortunately, there are some promising signs that this schedule-based, rather than task-based, approach is starting to gain traction through some early innovators in the space.

Plan gets at it from the task end. Giving you a side-by-side view of task lists and your calendar, allowing you to actually schedule time to do the work needed.


Worklife gets at it from another non-trivial use of our professional time – meetings. Again, giving you a side-by-side view of your calendar and scaffolded meeting notes view, which makes it easier to track agenda item, assigned tasks and decisions, especially across recurring meetings.


Now if only they could be mashed together into a single tool for managing both tasks and meetings… then we would have a solution to a truly valuable problem.



Time Management > Task Management

Minimum Valuable Problem

Product Management digital newsletters are usually a good resource for more general management and leadership content. Since after all, regardless of our title, we are all product managers: we are tasked with solving a portfolio of problems to a diverse group of stakeholders, using our unique skill sets, through a set of services that we provide.

This summer, all the ones that I’m following on a regular basis seem to have experienced a disappointing drought, which has finally come to an end with this piece referenced in Pivot Product Hits by Scott Sehlhorst:

Minimum Valuable Problem

Minimum Viable Product (MVP) is a commonly used term in lean product development, which refers to “the least you can do” before shipping your product to market. Since the most critical learning, from a business perspective, happens when your product meets the market – aim to get to that milestone sooner rather than later.

MVP is typically discussed through a functionality lens – the minimum amount of features that we need to build in order to have a viable product.

Scott thoughtfully calls out a big challenge with this approach: since it’s an inside-out approach, it doesn’t give us any guidance as to “what is enough?”, increasing the risk of building too little or too much.

Instead, he proposes an outside-in approach: rather than asking what is the minimum viable product that we should build, we should be asking what is the minimum valuable problem that we should solve.

Asking that question from an outside-in, customer-centric perspective, increases our chances of building something that is of value to the customer, as measured by the problem that it is solving for the customer. If it’s only solving half the problem, it’s not that valuable.

In Scott’s words:

The minimum valuable problem is one you completely solve.
You may only solve it in a very narrow context or scope.
You may only solve it for a small group of users or a subset of your ultimate market.
You may only solve it adequately, without creating a truly competitive solution.
But for that one customer, in that one situation, you have completely solved it.


Minimum Valuable Problem

N Squared

Azeem Azhar’s “The Exponential View” is one of my favorite weekend reads. A few weeks ago it contained a link to Amna Silim’s “What is New Economic Thinking?“. Buried in its reference section, I’ve found this gem by Paul Ormerod:

N Squared

N squared stands for Nudging * Networks.

The first part focuses on “Nudging” – the kind of gentle behavior change interventions based on behavior science (rather than standard neo-classical economics) popularized in books such as Thaler and Sunstein’s Nudge.

The meat of the paper focuses on “Networks” and in particular, human networks. It explored the implications of a very interesting assumption:

“Many of the decisions we make are based not so much on the independent, rational calculation of the costs and benefits of different actions – the mode of behavior posited in economic theory – but on observing and copying others”

Ormerod provides a very easy-to-understand explanation of the behavior in a random structure network using the model developed by Duncan Watts.

The outcome of the model is best summarized by the following quote (and graph):

“Systems of interconnected agents whose behavior influences each other are both robust and fragile. These are key words. Most of the time, the system is robust to small disturbances and these do not spread very far. But occasionally, the system is fragile, vulnerable to exactly the same size of shock that usually it is able to contain…

…  The common sense causal link between the size of an event and its eventual impact is broken. “


One of the immediate implications of that outcome is that:

“networked systems bring problems when it comes to measuring impact. What worked and what did not work? And why? A great deal of policy evaluation is carried out paying little or no attention to the potential impact of network effects. But if these effects are significant, studies that ignore them can generate misleading results. A successful outcome may arise not because of a nudge factor, but because of imitation across the network. The risk is that success can be mistakenly attributed and policymakers left puzzled when a similar policy leads to failure in a different context.”

As a final note, Ormerod introduces two additional network structure archetypes, “Scale-free” networks and “Small-world” networks, to show how an intervention strategy that works in one, may not work in another.

Good papers leave you with questions that you’ve never even considered before, that this was definitely the case for me here:

  1. What type of network archetype best describes companies?
  2. Does the archetype change as the company scales and the dynamics of the connection changes?
  3. What does 1+2 mean for corporate governance and more specifically, driving change inside companies?
  4. Given that many employees are tasked with enacting change in networks, how should the now common “accountability to impact/outcomes” mindset change?
N Squared

The OS Canvas

The fantastic piece of thoughtwork by the folks at The Ready:

The OS Canvas

OS v2.0

As Aaron defines it, it is his 2nd attempt to describe complex organizations through simple frameworks in the most comprehensive way possible (the first being the manifesto).

Visually, it’s inspired by Alexander Osterwalder’s Business Model Canvas

From a content perspective, while drawing from the works of dozens of people, the strong influences of Frederic Laloux’s list of structures, practices, and processes in Reinventing Organizations is clearly noticeable.

The framework decomposes the organizational operating system into 9 components:

  1. Structure & Space
  2. Authority & Decisions
  3. Information & Communications
  4. Policy & Governance
  5. Purpose & Values
  6. Meetings, Rhythm & Coordination
  7. Strategy & Innovation
  8. Resource Allocation, Targets & Forecasts
  9. People Development & Motivation


Towards OS V3.0

I view this framework as a huge step forward from v1.0 in three major fronts:

  1. Visual representation – the canvas leverages the spatial arrangement of the content to make it easier to see both the system and its parts at the same time
  2. Content – this iteration seems a lot more comprehensive and captures many organizational elements that were missing in the original manifesto
  3. No-judgement– leaving each of the boxes (components) blank, leaves room to study any potential permutation, without judgement, seeing how small changes may affect the interactions between the different pieces and the whole.

While this framework is a huge step forward, its structure also clarifies the value that it is yet to unlock.

The simple 3×3 layout implicitly suggests that “all parts of the organizational OS were created equal”. I strongly believe that this is not the case, and there’s some directional/sequential relationship between the different component. For example, the organization’s purpose and its beliefs about human motivations seem to be deriving / constraining some of the other components, while the inverse seems to make less sense.

The canvas idea gives us the opportunity to capture not only what the different parts are, but also, to some extent, the way they interact, which a critical attribute of the organizational system.

Lastly, I suspect that if we follow the intent to capture interaction as part of the canvas to its conclusion, we’ll discover that some of the initial “pairings” (all boxes are currently in “X & Y”  or “X, Y & Z” format) don’t make sense anymore, and need to be reshuffled in order to make the interactions more apparent.

Looking forward to v3.0 from Aaron and team, so I can compare it to my own.


The OS Canvas