High Reliability Organizations (HROs) – Podcast with Brian “Ponch” Rivera

In this podcast we are discussing how High Reliability Organizations (HROs) manage information flows, risks, team dynamics and more. Here’s the podcast recording:

To reach out to Brian:

LI: https://www.linkedin.com/in/briandrivera/

References to books mentioned in the podcast:

Managing the Unexpected: Resilient Performance in an Age of Uncertainty
By Karl Weick and Kathleen Sutcliffe
Link: http://a.co/c7XEmp2

Black Box Thinking: Why Most People Never Learn from Their Mistakes–But Some Do
by Matthew Syed
Link: http://a.co/hpvGTi4

Beyond the Checklist: What Else Health Care Can Learn from Aviation Teamwork and Safety (The Culture and Politics of Health Care Work)
by Suzanne Gordon et al.
Link: http://a.co/0K75uNE

Antifragile: Things That Gain from Disorder (Incerto)
by Nassim Nicholas Taleb
Link: http://a.co/78d9wmA

Blink: The Power of Thinking Without Thinking
by Malcolm Gladwell
Link: http://a.co/9irTGE6

Highest Duty: My Search for What Really Matters
by Chesley B. Sullenberger et al.
Link: http://a.co/cnuLjA7

Safety at the Sharp End: A Guide to Non-Technical Skills
by Rhona Flin et al.
Link: http://a.co/40chYlZ


By Alex Yakyma, Org Mindset.

Org Mindset is a Platinum Sponsor of Mile High Agile 2018!

Hello folks! Some exciting news… We are sponsoring Mile High Agile this year that will take place in Denver, Colorado, May 21 & 22.

We will be happy to see you there. We’re gonna have a premium booth with plenty of interesting things, useful give-aways and, most importantly, we will be glad to chat with you, address your questions, participate in discussions on various topics.

We are really excited about this!


By Alex Yakyma, Org Mindset.

Feedback Loop Markers. A Panel Discussion During Our Class.

Last week we had a wonderful OMEC (Org Mindset Enterprise Coach) class. During the lunch break on day two of this three-day training we made a brief panel discussion with our attendees on one important topic: Feedback Loop Markers. It’s one of the many topics in the course. Hope you enjoy the video:

Our next class will be also in Boulder in April. You can find more information on the class schedule and the course description.

Addressing the “Certainty Bias”: Core Principles to the Rescue


Certainty bias?

Indeed. Certainty bias is the term we use in reference to organizations’ tendency to demonstrate overconfidence in desirable outcomes while in fact operating in an environment of uncertainty. A lot of organizations are exposed to this phenomenon. Yours too, most certainty… no pun intended. The problem has some typical symptoms:

  • Assumptions are perceived as facts
  • Organizational behavior is predefined and over-constrained
  • The gap between reality and plan is never properly understood

As a result, we get a whole bunch of “funny” things happening in the enterprise; and those are not exactly “ha-ha”-funny. We see product management that obsesses with scope while there’s no evidence of its value whatsoever. We see long-term, fairly detailed organizational plans that span unimaginable amount of time and cannot be delivered in principle the way it was intended. We see budgets that are tied to detailed scope and we see capacity expectations which never work out. But despite all that, what’s much worse is that the organization continues to live under the impression that it’s actually all working out just fine. The organization de facto loses its ability to learn. The gravity of a fine-elaborated plan with scope and budgets attached to it takes huge toll: people at different levels tend to acquire political skills much rather than the ability to problem-solve and as a result, often chose not to raise systemic issues even if they happen to stumble upon them. Everyone becomes a hostage of the system, which is a result of the flawed thought process.

Okay, but what’s the right thought process then?

I will try to briefly summarize it as a set of principles, a vector in the direction that provides a better toolset for dealing with systems of uncertainty. Here they are:

  1. Aim at business outcomes
  2. Minimize unmanaged assumptions
  3. Align individual motivation with value delivery
  4. Provide room for emergent behavior
  5. Exploit cross-level learning


1. Aim at business outcomes. Hmm… Of course everyone aims at business outcomes, what else should they aim at?

Well, while it really sounds simple and obvious, it doesn’t mean that it actually takes place. What do you think a product manager is aiming at when they demand “all these features” from the team, having no idea whether any of it will produce business value? Or a team that is obsessed with cycle time. Deliver more! Deliver faster! …Does it produce more loyal customers or more revenue or significant long-term competitive advantage? Are those questions even being asked when making scope, quality, schedule or cost decisions?

2. Minimize unmanaged assumptions. Assumptions inevitably arise when we are operating in the environment of uncertainty: we don’t posses full knowledge over organizational behaviors and outcomes. Therefore we assume. The problem comes when we assume this and assume that every step of the way, while pretending that those are not assumptions but rather firm facts. Why do we think this scope will have the anticipated business impact? Will the other team provide the functionality that our team needs? Will this data connector work? Will this funding be sufficient for the initiative? Assumptions are everywhere: in business and technology strategy, in requirements, in implementation approach, in team and skill-set structure, in funding, in interpretation of the company’s bottom-line and more.

On the one hand, the problem is in that we don’t acknowledge assumptions and don’t manage them as such. On the other hand, due to ineffective process and structure, we tend to spawn assumptions in large quantities where they could be avoided in the first place. So, for instance, a rigid structure of teams that have significant dependencies on each other creates unnecessary assumptions that could have been avoided should the teams be more flexible and organized to better contain the dependencies rather than have them scattered across the organization. Similarly, rather than having requirements trickle down the long organizational hierarchy, which ironically enough, bypasses customer every time and generates more and more bold assumptions (of both what to build and how to interpret the requests from above), it would be a lot more productive to provide each team or a small group of teams with a stakeholder with the sufficient requirements decision-making authority who directly interacts with the customer and a few key internal stakeholders.

3. Align individual motivation with value delivery. The type of motivation that dominates across the industry, is usually only loosely connected with value delivery. Organizational leaders should be the ones to take care of this problem, but they are themselves subjected to the same blind spots as everybody else and, as interesting as it sounds, can hardly be blamed for anything. To best illustrate the detail behind this principle, we need to ask ourselves, what organizational behaviors and qualities are we after when we talk about value delivery. Well, we are looking for collaboration along the pathways of critical dependencies, we’re looking for flexibility to be able to respond to new facts, we are looking for openness and transparency for communicating and eliminating impediments. But is that what we usually see? Managers that are overly possessive of “their” people, even though another team or program badly needs help with high-priority work, are hardly a good example of a collaborative spirit. Similarly, who would be motivated to respond to change when the top leadership creates an immense pressure to deliver according to a master plan and measures everyone’s “productivity” based upon that? Finally, what manager would like to be known as the barer of the bad news, given that mostly the “yes-men” and the “happy land” folks get promoted in their organization; no wonder that systemic impediments remain forever unaddressed. The right motivation model has to found human motivation upon adequate thinking and seek to enable the organizational qualities, some of which we mentioned above.

4. Provide room for emergent behavior. One of the deadly sins that stem from the certainty bias is the idea of preprogramming the enterprise. We aim at preprogramming the organization because we lack the right model for thinking about organizational behavior; something that would show us how flawed is that idea in the first place. We tend to believe we can preprogram market conditions, customer needs, scope, team behavior in implementing it, etc. It’s the “clock mechanism” model. Instead, it’s better to think of your organization’s ecosystem as of a city or a garden. You can never direct a specific way in which a city or a garden evolve. You can influence them, of course, by affecting various enablers but never to expect the exactly predefined behavior. A city may decide to sell some land to a hotel chain to attract more small business to the area, but which business will end up there and what other enablement will they require – there’s no way to know upfront. You may decide where to locate different plants in your garden but you can’t expect them to grow precisely like you want. You will know more as you go, but to respond to new facts, you need to preserve flexibility for behaviors you don’t yet know. So, how exactly is an enterprise supposed to provide flexibility for emergent behavior? Well, how about creating plans that explicitly contain the unknowns, multiple possible solution options and experimentation required? How about the funding being detached from exact scope expectations? How about team and department boundaries being a bit more flexible for people to be able to swarm around the problem, when needed?

5. Exploit cross-level learning. It is impossible to establish any of the above, if this aspect of the organization’s life is not in place. See, it’s very easy to believe in long-term fixed scope commitment or in scope-based funding or in the detailed upfront architecture or in the flawlessness of your team structure, when there’s no information flows in place that would demonstrate the gap between those beliefs and reality. Every organizational layer lives with their own sweet, comfortable version of the truth. The idea behind the principle is very simple, there needs to be a mechanism that, in a sense, “collapses the pyramid”. This does not necessarily imply that organizational levels should be abolished, but they have to start to operate differently, overlapping a lot more across multiple levels at a time and immersing themselves into the rich context of experimentation, execution and validation, rather than staring in their dashboards filled with vanity metrics.

This may be enough for the initial discussion on the topic, enough for you to start thinking about it in the context of your organization. Start by asking yourself how your current organizational reality support the principles above.


By Alex Yakyma, Org Mindset.

Lean Portfolio Management Conversation

Recently I had a great conversation with Marshall Guillory (http://blogagility.com) on Lean Portfolio Management. We talked about quite a few topics: the general idea of Lean-Agile Portfolio, common systemic impediments in implementing it, the connection to strategy and structure, organizational learning and more. You can find the video on Marshall’s blog (click on the picture to go to his original post):

By Alex Yakyma, Org Mindset.

Org Mindset Podcast: Key Constructs In Organizational Agility

We took a liberty to go a little bit beyond regular time box as the conversation evolved toward some interesting aspects of organizational agility. We talked about constructs that support responsiveness and flow (as well as anti-patterns to be avoided). We finished by touching on organizational learning and what’s needed to enable it in your enterprise.

Michael mentions two books in this podcast. Here they are with the corresponding links:

Extreme Agility: https://leanpub.com/extremeagility

Spirit of Scrum: https://leanpub.com/spiritofscrum

Bundle: https://leanpub.com/b/non-conformistagile

Enjoy the podcast and the books!


By Alex Yakyma, Org Mindset.

A Misconception of Workload in Complex Systems

Most organizational leaders are concerned with how work is done in their organization. This is indeed a very important concern but despite all the attention, it is most often addressed incorrectly. Today we will dig into this topic a bit deeper.

The Army of Walking Capacity Buckets

Organizations usually rely on the concept of “capacity” to plan and execute work. The idea is very simple at its core, which in part explains its widespread adoption. If you have 120 people, for example, you get 120*X capacity within a time box of size X. You can now plan new initiatives by matching their size against this number.

Here’s a big problem with this logic. Assume we have two teams: A and B, 5 people in each. Team A generally gets backlog items that create a pretty even load distribution across the team members. Team B, on the opposite, has a person (who we will name Olga) with a unique skill set. In this time box most of the backlog items involve Olga and she’s quickly becoming a bottleneck. So, in case of Team A, the throughout is high and can be well predicted by the overall team capacity. In case of Team B, however, the capacity of the team is absolutely useless. The throughput basically depends on Olga’s individual capacity, making the rest of the team run idle for the most part. In fact, it’s usually a lot worse than that as they, instead of going idle, keep creating more “stuff” that will pile up for Olga. So, in one case you have 5 people that move at the speed of 5 and in the other, five people that move at the speed of one person. If by any chance you think that Team B’s case is some sort of exotic mishap, I would encourage you to think again.

This logic scales further up by considering teams instead of individuals and so forth. The main takeaway is this: capacity is a very poor predictor of throughput. It’s not just inaccurate, it’s dangerous as it leads to unreasonably optimistic estimates for the delivery capability and, as a result, leads to substantially overloading the people. It’s counterproductive to view an organizational unit (a team, a team-of-teams, etc.) as a collection of “capacity buckets” that one could uniformly use to deliver value. Instead the structure of dependencies, knowledge pathways and skill sets are primarily responsible for the outcomes.

But Wait, There’s More: Variability

Business demand doesn’t stand still over time. The new backlog items at some point begin to require a different skill ratio and induce different dependency structure within the group. Team A in our example above, despite their prior stable record in terms of individual workload, may suddenly start to experience quite a turbulence with the new scope. Suddenly, there are significant bottlenecks and constraints that couldn’t have been predicted based on prior periods. The problem, therefore, is farther complicated: the internal structure of the workload (which primarily determines the outcomes) turns out to be a moving target.

Wow… Just when we thought we approached the solution…

You Have To Stop Fighting the Physics… It’s Not Helpful

The workload, by it’s nature, is heterogenous and variable. This makes it practically impossible to effectively plan and execute work based upon a “wholesale” capacity approach. It’s not that you will be “a little off”. Your calculations, depending on circumstances, will be way off the target. This is the way things are and it’s up to us whether we want to accept the reality and exploit the underlying forces to produce better economic results or we keep fighting the reality and continue to pretend that workloads are homogenous and predictably stable. The latter means that the organization is losing an opportunity to improve its performance. But what’s even worse, the organization fails to arrive at the right mental model of reality and continues to “optimize”, driving itself into even more trouble.

We have to think carefully what do we like better: the illusion of predictability and uniformity of workload or the actual business outcomes, because these are completely different things.

The Solution Is Not an Improved Mousetrap

This problem solves at the fundamental level. First and foremost, the obsession with capacity and utilization has very clear roots. It’s in the flawed assumption that once you’ve defined a boatload of scope, the success of the initiative equals to properly implementing that scope. This is not how product development works. This is a misapplication of manufacturing principles. We just take the ideas that guide the process of creating repetitive value and apply it to product development where we continually produce unique type of output. That “manufacturing” mentality has to go first, otherwise no method will ever produce good results.

Ok, so if that’s the wrong mentality, what is the right one? It’s actually very simple: in product development, learning and adjusting are the primary success factors. It’s not about the plan, it’s about your ability to quickly understand and properly interpret new facts and then adjust the course of action based on that. It is very easy to say whether an organization understands the nature of product development or follows the illusion of predictability. Simply look into the consequences of deviating from the plan or initiating change. If the organization welcomes change as a vital component of success, if the policies and rules (as well as the actual leadership attitude), make it easy to adjust scope and effort allocation then the organization obviously knows what it’s doing. If, on the opposite, changes are frowned upon, they are very hard to get approvals for and people prefer to rather go in a knowingly sub-optimal direction to avoid the hassle around implementing change, then you are dealing with an organization that treats product development as manufacturing.

So, This Is How It Works

Learning and adjustment. L-e-a-r-n-i-n-g and a-d-j-u-s-t-m-e-n-t…

This doesn’t preclude longer-term planning, but it definitely implies a fundamentally different treatment of planning and execution:

  1. The emphasis is on outcomes rather than outputs. This means more rapid, cross-cutting feedback loops and “value” rather than “scope”-oriented metrics.
  2. Planning and forecasting are informed by empirical evidence of delivery capability rather than capacity thinking, i.e. it should reflect the prior knowledge of constraints and bottlenecks within the system.
  3. It’s okay to plan but plans should not over-constrain the outcomes. Your organization wants to know how much (money, time, etc.) approximately it is going to require to build this and that? It’s totally fine to want to know that, as long as the following rule applies: the organization treats the plan as a collection of assumptions, some of which will play out as expected and others – not at all. This means that the organization will welcome new information and will be looking to adjust the course of action correspondingly. Re-scoping and highly incremental implementation of large initiatives is rather a norm: scope is an important variable, by changing which we can optimize the value delivered.
  4. To be able to quickly learn and adjust, self-organization is vital. Indeed, given the heterogeneity and variability of workload there’s no chance to apply top-down approach to most of the tactical decisions. This shifts the role of the leadership quite a bit and gears them up for addressing the impediments to self-orgnizaiton, collaboration and fast learning.

Wait a Second, But We Are Special…

Who isn’t? I can tell you though that there are two types of “special”:

  1. Certain planning and workload management requirements are externally imposed. That’s, for example, when you are a contractor whose contract agreement uses scope as a key “currency”. Let me be clear about something here. For starters, just because you are operating under such constraints, doesn’t mean that those constraints are helpful to either of the parties. This topic deserves it’s own big article (or articles, rather). I hope I’m not creating an impression that we are dealing with some ideal scenarios here. I happen to have a very good understanding of what contract work is like as that’s the environment where I started my career and worked in multiple different capacities, on both sides of the business: as a contractor and also as a customer, at different times. So, I don’t underestimate the case. At the same time, while it’s the customer who originally imposes the constraints, it’s the contractor who fails to make the leap towards a better collaboration model by demonstrating an alternative approach in action and gradually taking the customer on this journey that will benefit both parties.
  2. The constraints are self-imposed. Well, no excuse then. You are doing it at your own expense. Time to pivot and start treating workload in product development the way it should be treated.

Lastly, the usually superficial adoption of Agile and Lean practices unfortunately does not prevent from capacity thinking as a primary workload management tool. You need to address the root causes of the problem, some of which we discussed above, for Agile and Lean to actually work in your environment.

So… how is workload managed in your organization?


By Alex Yakyma, Org Mindset.

Anti-Pattern: Anemic Transformation

Driving a successful transformation is a tough task. It takes skill and courage on behalf of the change agents in charge. More often than not, however, the journey leads to a pretty undesirable destination where the organization assumes they have succeeded with the job while in fact they got hopelessly stuck, unable to achieve any significant improvement whatsoever. We call this state an “Anemic Transformation”, a transformation that fails to achieve any tangible result.

A Lot More Companies Are Subjected to Anemic Transformation than You Think

Why? Because for many organizations it is hard to even properly evaluate where they stand. See, whether a transformation is successful or not, usually ends up being a subjective call for an enterprise. Part of the reason for this ambiguity (and therefore enough room for subjectivity) is that the transformation has no shared, viable business goals in the first place (read more about this in the post: Climbing the BS Mountain: Agile for the Sake of Agile). While there’s often no evidence of systemic improvement, there’s always plenty of local parameters that seem to have improved and are often interpreted as evidence of success.

At the same time, things that really needed to change, did not change (find out more on this subject here: This Is Why Your Organization Can’t Be Agile). One common manifestation of this: the engineering teams’ operating model has changed while the mindset and the habits of the organizational leaders remain unaffected.

So, How to Bring It Back to Life?

A couple things are important in bringing your transformation back on track.

First, for a change agent it’s vital to not fall into a status quo trap where all they do is seek the path of the least resistance. That’s a route that certainly leads to transformation anemia. It is critical to refocus on things that constrain the transformation. Typically the problem lies in the mindset of the leaders and in the established practices of enterprise planning, execution and measurement. None of these are easy to change, but for a change agent, continuing to pretend that local advancements will get the organization to desirable outcomes, is highly counterproductive. If you want to really change something to the better, it’s time to start doing what really matters as opposed to what’s easy to do. There’s no easy pill that will magically help you acquire the right attitude, overcome your personal fears and focus on the right thing. But it needs to be done: it’s your transformation and you need to make it work…

Second, prioritize the systemic impediments to your transformation and focus on one or two things at a time. Is it current rigid planning procedure or misguiding metrics or something else that creates the problem? Focus on that specific thing. Think about the plan of attack with specific action involved, be it training and coaching the leaders, involving an external party, exposing the leadership to new empirical evidence, etc.

Lastly, work to make the transformation everyone’s business, don’t hold it exclusive to the original transformation team (or center of excellence or whatever you call it). Nobody likes to be changed by somebody else. People like to be in charge of their own fate, not to mention that the outcomes will likely be much better this way.

The Timeless Value of Time

Now, an important caution. Many transformations start on fire but quickly grind to a halt over time. There’s a powerful force behind this. Real behavioral change involves rewiring one’s brain and that takes time. Different people show different neuroplasticity. Moreover, there’s no definitive way to know “when” the shift happened. Therefore, there’s no easy way of telling whether certain people will not be falling back to their old habits… when nobody’s watching.

Overall, the goal of the transformation is to build new sustainable organizational habits, which requires specific enablement in terms of coaching. It may as well require establishing the “reinforcing” feedback cycles, the purpose of which is to provide continuous evidence that the new behaviors are producing value and so forth. Real change is sustainable change and that’s why the focus should always be on the long-term outcomes.

Finally, let’s close with a quick assessment process…

Is Your Organization Exposed to It Too?

So far we were talking about those… other enterprises, somewhere out there. The real question is: how about the transformation in your enterprise? Is it anemic, too? Here are some typical symptoms to check against. If your answer is “yes” to any one of the following bullets, it’s a strong reason to be cautious. Here they are:

  • Our transformation is not linked to business objectives that would be unambiguously shared across the board
  • People at different levels of the organization have significantly different opinions regarding the transformation success
  • No substantial change happened in ways of working of the organization’s leadership
  • The change is mostly “contained” within the lower levels of the organization
  • Depending on circumstances, people may feel uncomfortable sharing their opinions regarding the transformation results
  • Practices that we thought were adopted, turned out to be abandoned

I hope this quick self-assessment helps. Good luck with the transformation, the toughest task there is!

By Alex Yakyma, Org Mindset.