Getting Personal about Change [Keller & Schaninger]

Photo by Martin Sanchez on Unsplash

Every once in a while, I come across some good content from the folks at McKinsey. Last year it was Untangling Your Organization’s Decision-Making which informed “deciding how to decide”. This year, The Helix Organization almost made the cut, but eventually, I decided that while it refines and extends a typical matrix organization in a few important ways, the contribution is still mostly incremental. 

And then I came across Scott Keller and Bill Schaninger’s 

Getting personal about change

An adaptation from their new book Beyond Performance 2.0: A Proven Approach to Leading Large-Scale Change and a piece that was well worth my time. And hopefully yours.

I’ve been thinking about mindsets a lot in recent weeks, as last week’s post about culture may suggest. In the process, I re-read my Pfeffer piece about changing mental models, which rings true today as it did when I wrote it 2.5 years ago and most likely as when the original was written 14 years ago. 

Pfeffer wraps up with the following quote (emphasis mine): 

In addition to being concerned with the company culture, human resources must be concerned with the mental models and mind-sets of the people in the company, particularly its leaders. Because what we do comes from what and how we think, intervening to uncover and affect mental models may be the most important and high-leverage activity HR can perform.

But Pfeffer left a big question unanswered: how? 

Keller & Schaninger, first make a similar case in their own words: mindset is the root cause which causes smart, hard-working, and well-intentioned employees to continue to behave as before, despite the effort and intention to change their behavior. The only way to drive effective behavior change is by reframing the root cause: changing the underlying mindset. From “hoarding information is the best way to magnify power” to “sharing information is the best way to magnify power”, for example. 

Then, they pick up where Pfeffer left off, offering a 2-part approach: 

Changing mindsets using a U-process offsite

Keller & Schaninger argue that the most effective intervention to get leaders and employees to commit to changing themselves is a 2-day offsite for a small group of 20–30 employees at a time, facilitating a workshop-based learning journey for each of the participants. 

The methodology is based on Scharmer’s U-process consisting of three phases:

Sensing. This typically involves a senior leader who has already been through the workshop and shares the company’s change story, describes her or his own personal change journey, and answers questions from participants.

Presencing. This involves participants exploring their personal “iceberg” of behavior. It includes working through modular, discussion-based content and questions that equip leaders to achieve new levels of self-awareness and self-control. “Where and why do I act out of fear rather than hope? Scarcity rather than abundance? Victimhood rather than mastery? And what would be the result if I made different choices?”

Realizing. In this phase, participants make explicit, public choices about personal mind-sets and behavioral shifts; identify “sustaining practices” that will help them act on their insights; and reflect on how they will engage their personal networks for the challenges and support they will need during the rest of their personal change journey.

The offsite is followed-up by small team gatherings aimed at offering peer accountability and advice. And a facilitated session a few weeks out to take stock changes in behavior and determine next-actions. 

Reshaping the work environment using the “influence model” 

Keller & Schaninger observe a similar phenomenon to the one I outlined last week in which behavior is mutually shaped by both our internal mindsets and the external work environment. They offer McKinsey’s “Influence Model” as a roadmap for reshaping the work environment in a way that’s conducive to the desired behavior change: 

Changes in thinking and behaving will be significant and sustained if leaders and employees see clear communications and rituals (the understanding and conviction lever); if supporting incentives, structures, processes, and systems are in place (the formal-mechanisms lever); if training and development opportunities are combined with sound talent decisions (the confidence and skills lever); and if senior leaders and influence leaders allow others to take their cues from the leaders’ own behavior (the role-modeling lever)

Source: McKinsey

Super cool. And kind of looking forward to trying it out in real-life. 

Getting Personal about Change [Keller & Schaninger]

What is culture?

Photo by Francesco Gallarotti on Unsplash

It is rather surprising that I managed to get away with publishing this blog for more than 5 years now while never providing my own definition of culture. I’ve shared Laloux/Wilber’s definition of culture, Horowitz’s, and I’m sure I’ve touched upon it indirectly in countless other posts but never explicitly spelled out mine.  

I’ve formulated, or perhaps more accurately, synthesized, my own definition about three years ago. But only recently, when responding to a different post on this topic, I realized that I haven’t shared it outside of the organization I was part of at the time (AltSchool). 

So here goes. It is influenced mostly by the Laloux definition, and Schein’s (which likely influenced Horowitz’s as well) and consists of three interacting elements: 

“Culture is our shared set of beliefs and mindsets, reflected through our behaviors and supported by our organizational systems (processes, protocols, etc.)”

At the end of the day, culture is epitomized in the way we behave. However, our behavior is shaped by an internal source, our beliefs and mindsets, and an external source, the organizational systems in which we operate. It is important to note that the relationship between these elements is not as one-directional as I make it sound, and there are secondary effects through which organizational systems shape beliefs and mindsets, for example. 

There are no “good cultures” and “bad cultures”. Every culture has its use and may be optimal to a certain group of people aiming to accomplish a certain purpose together. What sets apart strong cultures from weak cultures is the degree to which these elements are honest, clear and in alignment/congruence with one another. 

One of the most common mistakes that organizations make is focusing on defining the first element, beliefs and mindsets, often referred to as values or principles and ignoring the other two. It’s definitely a mistake that I’ve made as well. I’ve written extensively about a process for formulating values or core principles, and I’ll be the first to admit that it muddies the water a bit in distinguishing between the elements, since it was written before I developed this definition. Yet if we look at the 10 core principles that most organizations tend to converge on a subset of, once you peel off the marketing-speak, it becomes a little easier to see why values or principles are not enough. 

Mission-orientation, customer focus, risk-taking/creativity, ownership, transparency, humility/learning, simplicity, excellence, tenacity/grit, and speed are not things that have a clear, descriptive and observable definition. This creates a lot of room for misinterpretation and as a result, misalignment, in both directions: when I’m taking these principles and translate them to the behaviors that I believe reflect them, and when others see my behaviors and translate them to the underlying principles that they believe I may hold. 

In addition, our formal and informal organizational systems, processes such as hiring, firing, promoting, etc. and practices such as the way we run meetings or make decisions, explicitly and implicitly define a set of behaviors that are encouraged/discouraged. Without careful design, those behaviors may or may not be aligned with the behaviors and, in turn, beliefs and mindsets that we want to encourage/discourage. So let’s put in the extra effort to make sure that they do. 

What is culture?

VCoLing: Learning to Learn [Lectica]

Photo by Ben White on Unsplash

Lectica’s overall approach to learning in a complex world deserves its own dedicated post, which I hope to write one day. Today, I want to focus on a smaller piece of their overall thesis — their framework for “how we learn?” because it stands on its own and is more broadly applicable, regardless of the learning goal that you’re applying it towards. 

I am mostly synthesizing content from two sources: 

Virtuous cycles of learning (VCoL) and the +7 skills

Learning in the moment: How to use micro-VCoLs to learn optimally on the fly

Lectica’s framework, called the “Virtuous Cycle of Learning” or VCoL for short consists of 4 key steps: setting a learning goal → gathering information → applying what you’ve learned → reflecting on the outcome. Sparing you my rant on the overall underappreciated importance of reflection in many other approaches to learning, this macro cycle is very similar to other progressive frameworks describing a learning process, with minor variations in the labeling of the different steps. 

When things start to get interesting, and have certainly expanded my knowledge of learning, is in the way Lectica decomposed this cycle further and in the way it is applied to real-world situations. 

The +7 skills

Lectica identified 7 key skills that support the practice of learning. Each, in turn, can be strengthened through a set of specific practices.

Source: Lectica
  1. Awareness of self, others, and the environment: observing and documenting thoughts, feelings, or behavior; self-evaluation; practicing non-judgmental openness to experience; meditation; mindfulness in everyday life; somatic practices, like yoga; coherence practices, like HeartMath
  2. Skills for making connections between ideas, information, emotions, perspectives, and evidence: brainstorming; Minto Pyramid problem solving; polarity thinking (or both / and thinking); mind mapping; causal loop diagramming (or other systems mapping approaches); building relational databases
  3. Skills for seeking and evaluating information, evidence, and perspectives: active listening; deep listening (Kramer); seeking clarification; “library” research; critical thinking; action inquiry (particularly second-person action inquiry); the scientific method
  4. Skills for applying what we know in real-world contexts: action learning; project-based learning; developing action plans or development plans; rehearsing — reducing risk by trying out new knowledge in hypothetical situations; writing or critical discourse — using new knowledge to improve an argument or message
  5. Reflectivity — a cultivated habit of reflecting on outcomes, information, emotions, or events: making sure that learning goals are “just right”; embedding learning in real life, as a part of everyday activities; not punishing learners for making mistakes — helping them see mistakes as a source of useful information; ensuring that every learning cycle, no matter how small, ends with goal setting
  6. Skills for seeking and making use of feedback: openness to feedback; awareness of your own defensiveness; feedback-seeking skills (like helping others feel comfortable providing you with feedback); skills for evaluating and incorporating feedback; second-person action inquiry; participation in focus groups; customer or employee surveys
  7. Awareness of cognitive and behavioral biases and skills for avoiding them: cultivating humility — recognizing the ubiquity of human fallibility; building critical thinking skills; regularly seeking feedback; tackling common cognitive biases, one at a time (e.g., conservation bias, bandwagon effect, stereotyping, or attribution bias)

The 7 skills are also very helpful in better triangulating where the learning cycle is weakest (or breaks down altogether) and then taking focused action to strengthen that particular skill. 


Often times we want to work on a macro skill that’s a bit too lofty, abstract or risky to pursue as a whole. Let’s say we want to improve our “collaborative capacity”, for example. It seems like a worthy goal, but where do we begin? 

We begin by decomposing the macro skill into something more tangible. For example: part of a strong collaborative capacity is having strong facilitation skills. Facilitation skills, in turn, include but are not limited to having strong active listening skills. Active listening skills can be decomposed to: identifying opportunities for listening, giving others opportunities to speak, etc. 

Now we have something in hand that we can more easily run a VCoL around and practice “in the real world” with one additional useful distinction. If we zoom back out to the crude VCoL loop: set, seek, apply, reflect — two stages in the loop, “reflect” and “seek”, are more internal, or done in consultation with a trusted coach or mentor. The other two, “seek” and “apply” is where we engage with the outside environment differently, with the learning goal in mind. And those too can be broken down into micro-VCoLs: an “awareness VCoL”, in which we either increase awareness of opportunities to practice a skill or identify individuals who are proficient in a given skill; and a “practice VCoL”, in which we build virtuosity in the particular learning goal. Examples of the two are shown below.

The next time you set a learning goal for yourself, consider using VCoL as your framework for learning. 

VCoLing: Learning to Learn [Lectica]

How we make decentralized decisions [Küblböck]

Another fantastic piece by Manuel Küblböck whose excellent work I’ve already showcased here. This time, the focus is on how decisions get made at Gini. While the majority of the post covers the mechanics of the various decision-making formats, that was the least interesting part to me, since I’ve already covered most of them, for the most part, in previous posts. What was most interesting, was how the system is structured and the following attributes in particular: 


Source: Manuel Küblböck

I’m not 100% sure where the 7-levels of delegations model originated from, but I first came across it a few years back on the Mgmt3.0 website so I will give them the credit for now. 

This fuller spectrum is being used to anchor the decision-making formats that are actually being used: 

Source: Manuel Küblböck

Again, while the mechanics of “safe-to-fail/mandate”, “group consent” and the “advice process” are outlined in the post, those are fairly standard formats of decision-making. 


This was new and exciting for me. Thinking about the process of choosing the right decision-making format more like a simple, lightweight decision-tree/escalation path with increasing levels of severity: 

Is this safe-to-fail? → Do I have an explicit mandate as part of one of my roles to make this decision? → Can the group reach consent (not consensus) about this? → Advice process. 

Specifically, thinking about the “advice process”, which is the most lengthy process of the three, as an escalation lever when the group fails to reach consent is very clever and avoids over-using this heavy process. Another interesting aspect here is seeing the escalation arc moving from the individual, to the group and back to the individual, which seems a bit counter-intuitive at first but makes a tonne of sense once you think about it.


This is another cool innovation. Defining a desired, healthy, usage distribution across the different decision-making formats. Heavily favoring and relying upon autonomous/distributed decision-making, using consent-based decision-making only when necessary, and thinking about the advice process as the exception rather than the rule. While the 90%/9%/1% should be thought of more as illustrative, order-of-magnitude guidelines rather than exact percentages, they create a healthy benchmark that can be used to trigger and support troubleshooting when the actual distribution looks significantly different. 


Not a new point but one worth emphasizing, since many, myself included, often make this mistake. When we compare the speed of various decision-making formats, we tend to compare the time it takes to reach a decision. But this is the wrong benchmark since decisions are just a means for informing a desired behavior change. So if we want to make a fair comparison on speed we need to look at “time to make a decision” + “time to change behavior” which is beautifully illustrated in this parting image: 

Source: Manuel Küblböck

Post Script: h/t Bruce Gant for pointing me to the true origin of the delegation ladder, a 1958(!) HBR piece by Robert Tannenbaum andWarren H. Schmidt called How to Choose a Leadership Pattern:

How we make decentralized decisions [Küblböck]