Coaching Model: Self

For Coaches

A Coaching Model Created by Bianca Prodescu
(Systems Coach, NETHERLANDS)


My mission as a coach has been to enable teams and organizations to find their own ways for sustainable continuous improvement. When asked how I would define a successful coaching assignment, my answer has always been: when the client can achieve high performance on their own and I am no longer needed.

To achieve this I have developed the Self Coaching Model. This model enables the client to build a system for themselves that supports the long-term structural change.

We start by defining your desired outcome that will be at the center of all actions, you dive into the relationship between your behavior and the environment around you, you experiment to increase awareness, validate assumptions and learn about what is needed for structural change, and then work out how to turn your desired new behavior into a reflex.

Systems Coaching Model Bianca ProdescuUnderlying principles

Small incremental steps. In face of big changes, our brains respond to stress. Research shows that small incremental steps combined with the principle of Kaizen[1] (Japanese management philosophy that translates as ‘continuous (Kay) improvement (zen)) are at the base of long term sustainable change.

The quest for continuous improvement can start as early in the process as the design phase of any change.

Fail-safe environment[2]. Nobody likes to fail, to embarrass oneself while making the wrong decision. Getting criticism is uncomfortable and in some cultures losing face is not an option.

However, failure is essential for learning because it provides first-hand experience, knowledge, and resilience. It puts things into perspective and enables you to recognize what you truly value.

Identifying within your own environment the space where you can learn and take risks without the fear of judgment, criticism, embarrassment or big consequences is key to building confidence in the steps and direction of the change you want to make.

Learning through experimentation[3]. When you don’t know if your step will be a success or not, you invest time in expanding your knowledge and investigating possibilities.  The most valuable and relevant information you can obtain is by trying out different things and optimizing the successful steps.

Having a fact-driven approach to change relieves the brain from the stress of uncertainty, and reduces the fear of trying something new.

Feedback loops & Retrospectives

But before you just try things, spend a few minutes planning what data you need and how you will collect it. Planning when you will collect it can also help you identify if the size of the step you are taking is just right.

As we don’t always have direct insights, any time there is an opportunity, get feedback: from your colleagues, from your clients, from the people that can provide you with objective observations.

This way you can experiment with any part of your life: work, hobbies, side-projects, behavior, relationships.

Scaling the experiment for the future. Once an experiment is successful, identify the opportunities for expanding the environment and application of the new learnings. Make specific the changes you are introducing by expanding the environment: is there a difference in situations, relationships with people, timing, etc.

This way you can validate how your learning can scale and gives you an approach to slowly incorporate it into your routine.

How to Apply the Self Coaching Model

1. The goal as a North Star

When change happens it can either be initiated by us, as an action to reach a goal, or it’s happening around us to our environment and we need to adapt to the new situation.

Regardless of how the change was triggered, you can still define your Objective. This will help you understand whether the actions you take and the experiments you make are successful. Objectives come in two forms:

  • goals, which are quantifiable and easy to verify such as: losing 5kg or running a half-marathon;
  • states, such as: feeling calmer, gaining clarity.

Once you have identified your end objective, map out the outcome.

There is a clear distinction between output – what you produce as a result of certain actions you took, for example taking training and outcome – the impact and the value the results of your actions have, for example: applying the knowledge gathered from the training or a behavior change. 

A good way to get in that direction is to look at the goal you have set and ask yourself:

  • What will be the delta between the current and future situation by taking this action?
  • What is the change I want to see in myself?
  • What is the change I want others to notice about me?

Most of the time when we make our goals, we make assumptions about what others think about us, how we think we are perceived, how a solution would fix a certain problem. The bigger the goal, the bigger and more complex the design of the solution, the more assumptions we make an estimate based on feelings. Thus the bigger the risk of failure. This often results in an analysis paralysis situation, and you may find yourself spending a lot of time describing your goal and not committing to a first step.

2. Map your current system

The first step is to identify the behaviors that you wish to address concerning your end goal. Then for each of these behaviors, articulate the social interactions around them and their respective outcomes within the individual in terms of thoughts and feelings.

Human nature is too complex and unpredictable to be able to model it. Therefore it is important to not spend too much time here and to recognize that this step is just a starting point for the process of observation that can enable self-awareness.

Explore such complex topics with a cluster map guided by a few questions:

  • What is the cause of my reaction?
  • What makes my reaction even more intense?
  • What decreases the level of intensity of this specific reaction?
  • What gives the exact opposite effect?
  • What reinforces this behavior through time?

There are no right or wrong answers to these questions. The outcome of this step is a set of assumptions — explicit or implicit — that you have about how your actions impact your goal.

3. Evolve the structure in your learning lab

The learning lab is the space where small-step active experimentation, reflection, and brainstorming can happen at little to no risk.

The first version of an underlying structure is now developed with the first insights into your behavioral patterns, informed by your history and experiences. It may become evident that you may need more data to complete the structure or to evolve it.

Looking at your system map, identify the assumptions and the leverage points, where small and easy changes can have a substantial effect on the system.

  • Which of the connections action-outcome do you have confidence in?
  • Which are the most uncertain or unknown?

Create your first small-step experiment

Decide what action or cause-effect relationship you want to observe first and formulate a hypothesis around it.

A hypothesis is an educated guess about something in the world around you. It is testable by experiment or observation. 

To formulate a hypothesis you make a statement: If I do this (action to a variable) then this will happen (reaction to a dependent variable). 

Use case example:

I was just promoted to a team leader role, but I am still doing daily tasks as part of my former role within the team. I struggle with making time for the new tasks and I don’t want to disappoint my team members.

My goal would be: Within 3 months I can fully focus on my new role and my team members recognize how I can support them best from this position.

In this use case, the behavior I want to change first is to be able to say “No” when I do not have the time, but that conflicts with my core value of helping others and keeping the relationship on good terms. Every time I try it, I feel guilty for letting someone down. 

One hypothesis I can formulate that satisfies both conditions (make space in my calendar and maintain the relationship) could be: It will be easier for me to say “Can I get back to you on that?” than to say “No, I can’t do it”.

This can easily be tried out several times, should the opportunity present itself and I can observe how reacting in such a way makes me feel.

But is this step the smallest one I can take?

While running this experiment, it may turn out that when the requests come during a face-to-face conversation the pressure to accept them is still high, while when they come in via email there is enough time to consider and formulate an appropriate reply.

In the hypothesis formulated above, there is an implicit assumption that the way the request is made does not have an impact.

By running this experiment I have learned a bit more about myself and what variables in the environment around me I can play with.  I can update the map of my system with the new triggers and conditions.

Time for a new experiment!

A step is small enough when:

  • It can be done now and you do not see anything getting in the way of starting it or getting it finished.
  • It’s perceived risk is low. If the step fails in delivering the expected results, the outcome does not generate a big disruption or it has an impact negative enough to discourage you from trying again.
  • You can evaluate after each try and can change direction based on the learnings.
  • Do I know it? Or do I just think I know it? Make very specific the assumption you are trying to validate. Think about what information you are currently missing, what small bite of learning is needed to move you forward.

Prepare the controlled experiment

In this process step, you are creating a run and analysis plan.

You want to be able to conclude whether the differences you see are meaningful or just by coincidence.

When you will evaluate your experiment later you need to account for both the variability in the sample (a type of experience) and how large the sample is (how many times you have tried out your hypothesis).

Your sample size directly impacts the probability of obtaining a sample statistic.

Too small of sample size and you might not be able to recognize that there actually is a difference when it truly exists.

When the sample size is too big, the time it takes to collect the data/observations and the amount of change that happens can result in a high amount of variables. This could make it difficult to identify the correct cause-effect relationships for your hypothesis.

To identify a testing environment that allows you to collect as much data as you need to map out the benefits vs risks.

  • What will be the cost to take that action?
  • What is the expected effect of the action?
  • What is the long term effect that can be incurred by whatever I am planning to do?

By setting your acceptance criteria upfront, you are now deciding on a fail-safe environment, the time you will dedicate to run the experiment and in what conditions, so that you have enough information to show a meaningful cause-effect relationship.

Run & evaluate the experiment

Starting with the first opportunity you have to run the experiment, record your facts after each action, and evaluate the following:

  • What new facts and data do I have now to either support or invalidate my hypothesis?
  • How do I feel about the results so far in terms of confidence to carry out the rest of the experiment? (this is crucial for determining the boundaries of your fail-safe environment)
  • What is my next opportunity?

4. Meta level analysis

What have you learned about yourself through this experimentation step? After each experimentation step, you can explore your system map and complete the picture with the new learnings.

Update current structure

At this step in the Self Coaching process, you might still be identifying your own internal feedback loops. Feedback is an important characteristic of complex dynamic systems and is used as a control mechanism in 2 ways: reinforcing or correcting a direction.

The main components to take along in your evaluation are:

  • The trigger(s) that elicit the old behavior
  • The trigger(s) that inhibit the old behavior
  • The trigger(s) that initiate the new behavior
  • The trigger(s) that inhibit the new behavior
  • Your actual response: the act or thought that occurred at that moment;
  • The size of the step -> how big of a change you can commit to;
  • The environment: where you try it out -> what defines your safe environment for exploration;
  • The craving: what motivates you for this change -> refines the reason for the change and keeps you focused;
  • The reward: what satisfaction do you get afterward;

5. Adoption Approach

Define the alternative structure

Loot at your current map and identify what should change for the system to support your journey towards your end goal. It is important to understand how your system resists change or pushes back on the effort.

Add the following insights:

  • The support system -> in case of challenges along the way, what structures, processes, and people around you can help you overcome them;
  • The control system -> how to control the speed of change and direction (what feedback loops you have in place).
  • Which loops amplify the effects of your actions? How can they be strengthened?
  • Which loops cause the system to resist your efforts? How can they be weakened?
  • Are there any feedback processes that are already trying to shift the system in the same direction that you are? How can you build on these?

Using real data and facts can make the steps towards a big goal more tangible.

Since we are only human, we cannot always artificially limit our behavior to the environment we have set for experimentation. By the time you are ready to evaluate your full experiment, you may notice the new behavior showing itself in other spaces.

A new behavioral pattern might have started to form and you are ready to start with a new change.

By evaluating those situations you can identify how to support yourself in expanding the new behavior to new situations, scenarios, or relationships.

Questions to take along:

  • How do I feel about the fact that it happened in another situation?
  • How do I want to continue with this behavior?
  • What would my next step be?
  • What system do I have in place to support me in case of challenges?

Realizing that a new behavior is showing outside of the intended situations might give the person the impression that change is happening too fast and that they are losing control.

It is important, to be honest about the feeling and address it, re-evaluate the assumptions made, and also the core values that it touches.


The main purpose of the Self Coaching Model is to intently your own system for behavior change. 

Human behavior is a complex dynamic system with many components interacting within it. By observing the internal process of such a system, you develop an understanding of why your system is behaving the way it is.

We have explored at the start of how the brain refuses big changes. This coaching model introduces a change in small steps, hence rewiring the brain one step at a time.

Seeing each step as an experiment that can have two probable results: failure or success releases the perceived pressure from succeeding the first time. 

A direct consequence of aiming for learning, as a result, is that the brain starts identifying the learning bit as a reward for the effort spent.

Therefore with every new experiment, a positive experience is created. With a couple of positive experiences around change, we dare to make the step bigger.

The brain starts anticipating the rush it gets from the next step and a new habit is being formed.

Step back and see how change works for you.


[1] “Kaizen: Books –”

[2] “Psychological Safe Environment: A Concept Analysis ….”

[3] “The Lean Startup.”

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