Converting a broadcast into a conversation

This post came about accidentally because of a discussion I’ve been having with a colleague about the Elevator Pitch and how we’ve been trying to use it as part of a vision statement. I say “trying to use it” as my team’s primary service is that of organisational change via agile transformations, and the product isn’t as tangible as real-life products like bicycles, cars etc.

The context we were discussing, was early on in an engagement, soon after when a client “buys an agile transformation from my employer” (and I’ll park my many issues with that statement – see things like this to give you a sense of how long I’ve been carrying that baggage). One of the first tasks is to broaden the awareness of what’s going to happen to the client’s employees and some lightweight communication & broadcasting is a typical medium for starting this awareness drive. As the elevator pitch is a natural fit for lightweight, accessible communication, it’s a fairly obvious choice as one of the tools to be used.

What’s the problem?

One of the common mistakes that I’ve seen with teams producing elevator pitches, is they spend most of their efforts trying to craft the perfect words to get across the sheer breadth and scope of what it is they’re trying to achieve. The work itself is rewarding, as successive iterations of the elevator pitch can heighten the emotional connection between the team and their product. Teams often hope that the energy and enthusiasm that they display while giving the elevator pitch is infectious enough for their audience to engage. To my mind, that approach is inefficient and can be ineffective. I also feel that strategy does not respect the perspective of the listener – there’s a good chance that your listener is not a “willing participant” (i.e. they’re already overworked and there you are trying to pitch something to them – even the apocryphal story of the lift journey has the CTO “trapped” in the lift with you).

Get to the conversation bit already!

A real conversation between two people only really happens when both people are listening. When working with elevator pitches, it’s not certain whether or not your target will actually be interested in listening. While that’s out of your hands, the amount of energy and effort they have to expend to begin listening to you is partially under your control. By lowering the barrier to entry, you have a chance at making it much easier for your target to engage with you. It’s what makes snake oil salesmen so effective – they understand what their victim want to hear, and know how to give that message in a way that’s captivating specifically to them

By making sure your content and your expressions use the language and semantics of the person you’re trying to reach, you drastically reduce the cognitive load that person has in order to understand what you’re saying. Otherwise they’d have to translate what they’re hearing into what they can understand. Which can be hard work, and if they’re not already invested in you, it’s quite easy for them to avoid the effort and delegate the task to one of their direct reports. Which essentially defeats the point of having an elevator pitch in the first place. By putting in the additional effort to make it easy for your target to consume your message, you also demonstrate a degree of respect of your target’s time.

A useful effect of this degree of tailoring of your content, is that aspects that may be unimportant to you would gain prominence in your message if it’s important to your target. Most organisations have very fragmented views on what is important, and a single unifying elevator pitch can be very hard to create, and may not have the impact you desire. By tailoring, you significantly increase the chances of making meaningful connection with your audience, one person at a time.

Use Personas

A good way to start this tailoring, is for you and your teams to create personas representing the people you wish to connect with, and then create tailored elevator pitches for each of these persona. Empathy maps are especially helpful in this regard.

It’s possible (if the personas are different enough) that different personas may prefer different communication channels or media. Some might prefer an informal conceptual discussion over a coffee, while others might like to see more tangible aspects as part of a guided demo. By creating models of your potential audience, you greatly increase the relevance of your content to them.

A meeting with a nervous CIO


I very recently had an interview for a broad coaching role and I wasn’t happy with the answer I gave to one of the role playing scenarios. This post is me getting the jumbled up thoughts under control and structured in a more coherent form, so hopefully if the scenario happens again, I’ll be much clearer.

The Question

Discussion with the CIO of an organisation. They’re trying to transform their organisation (7000 people). Essentially, their strategy distils down into a conceptually three stages of “train everyone” – “change the way of working” – “see how it goes and evolve”. The exam question was “I’m nervous, am I missing something?”.

My refined Answer

Firstly I’ll define your organisation with a boundary containing two fundamentally different processes:

  1. Organisational processes. These processes collectively define how your organisation behaves. Transformational change only occurs when these processes evolve. The key ones are
    1. interaction processes (communication)
    2. visioning processes (purpose)
    3. motivating processes (alignment)
    4. learning processes.
  2. Operational processes. These processes collectively define what your organisation does and simplistically, all other processes belong here. Continuous and incremental improvements happen when these processes evolve.

Agile and Training

Next lets look at “agile”. There are two main parts that I want to cover. The mechanical elements such as practices, techniques – the “how to do agile”; and the behavioural elements such as mindset, principles, values – the “how to be agile”.

Training can provide awareness and skill. Skill in the mechanical elements, and awareness of the behavioural aspects. Learning and improving skills can be done in a training context. However, changing established behavioural patterns is an internal struggle and takes time and requires support.

This means that your training-based transformation strategy can potentially deliver incremental improvements (Scott Ambler, from Disciplined Agile Delivery has been running a long standing agile survey that has helped him determine that adopting the mechanical aspect of agile methods can realistically yield a 6-10% improvement in overall effectiveness these days). However, this strategy is unlikely to deliver transformational improvements.

From training to coaching

In order to make a lasting effect on the organisational processes, additional leadership coaching should be employed. As a leader, you have to set the example that you wish your organisation to follow, as your behaviour patterns will be emulated through your direct reports into your organisation. Like it or not, you are one of the coaches that influences your organisation’s leadership community.

The Servant-Leadership model has a natural fit with an agile culture and elements can be incorporated by your leaders into their leadership styles. The greater the adoption, the easier it is for their part of the organisation to evolve into a more agile culture.

Evolving your management

Any changes to your organisation’s leadership models will almost certainly require changes to your management methods and measurements.

Note: This might turn into another post.

Things I read to help me articulate this


Agile Coaching – Building my mental model of a person


I’ve been thinking about how to remain effective as an Agile Coach while not being co-located with the entity (person / team / project / programme) that wants to be coached.

While a long term viable solution might be for me to rebuild my approach from the ground up as a “remote native” thing, I reckon my MVP is to patch up my existing process (see “The anatomy of my typical coaching engagement“) so that it is still fed with as rich a dataset as possible.

Mental model of a Person

Mindmap of the categories of information I use to build a mental model of a person
This is the mental model I generally try to build of each person I work with as an Agile Coach.
  1. What they do
    • things like their role, career history, future plans, what’s their speciality in the team etc.
  2. How they think
    • things like how they build their mental models, how they make decisions, how they prioritise etc. I also look to understand how they see themselves.
  3. Main character traits
    • things like whether they’re an extrovert, are they motivated by fame/recognition/peer acceptance, how they respond to stress and challenges etc.

I’m also looking to distil all this into some insights into what they feel is important, what they see is urgent and what they think they must avoid.

Benefit I get from using this model

The core benefit I get from populating this model of my coaching client, is it gives me a far richer relationship with my client, which typically translates into better / more accurate communication. These are some examples.

  1. By learning about the “What They Do” tree, I’m able to work out if I can mentor them, or who would be a good person to mentor them and help them progress from Present to Future Ambitions
  2. If I can combine aspects of “What They Think Is Important”, some of their Character Traits (e.g. Individualism or Collectivism) and that is either something I align with OR can mimic sufficiently to communicate, I can begin to build rapport with them. Rapport is the first step towards trust.
  3. If I understand “How They Make Decisions”, it makes it easier for me to structure a compelling argument, thereby increasing my levels of persuasion.
  4. If I understand how they’re motivated, that can also support my ability to structure a compelling argument.
  5. If I understand how they manage their risks, and what they’re trying to avoid, then not only does it help me structure an argument, I can help them think about relevant risk mitigation strategies.
  6. If I understand “How They Make Decisions”, and can describe it to them in a way that makes implicit processes more explicit, I have a chance to help them learn about new thinking models and they can devise new problem solving strategies.

Building this model


This is the easiest scenario. Much of this model can be built by forming hypotheses informed by the actions and behaviours that I observe. The person is also accessible so that I can discuss my models and predictions and see how close I can get to what they think. The main challenge is the amount of time it can take before some of the deeper elements can be inferred / estimated, if for no other reason that it requires a great deal of trust and honesty between the person and I, and that trust takes time to build.


Conceptually, my starting point was to find techniques for collecting the same raw data that worked with the alternate channels available – voice & video calling and email / written form. As everyone else was in the same boat, they also would need to work out digital equivalents for their normal team ceremonies and so I could piggy back and observe those easily enough.

I quickly hit a problem. While this approach was fine and would yield accurate data for the known unknowns (see this post for some context) such as the “What they do” sub-tree, it is easily corrupted into opinion (e.g. “How they think”) or even a duplicitous facade, portraying a view that they believe is socially acceptable even though it’s not the reality (e.g. “Character traits”).

I’m currently exploring what I can infer reliably from more open “essay writing” styled requests. For example:

  1. Please describe your recollection of the last completed iteration, highlighting the events that you personally saw as significant for your role in the team.
  2. Please describe the events during the iteration that led you to believe for the first time that your iteration goal may be at risk unless you and your team were able to get on the front foot.
  3. Please describe the events that led your team and product owner to collectively agree what stories were going to be brought into the current iteration.

I’m exploring the different perspectives each team member has on the same shared experience. My hypothesis is that it’ll give me a few insights into how various team members think (relative to each other, as it were) and maybe a few nuggets about some of the more prominent personality traits that I need to pay attention to. I’m also hoping that the different language styles would be useful, but it seems a bit too early to tell.

The anatomy of my typical coaching engagement


COVID-19 has forced the issue. All my teams are now distributed because everyone’s working from home. As a coach, this has given me a few things to think about. Mostly about how I need to rethink many of my coaching strategies, as they mostly take advantage of the rich information flow that’s tacitly a part of face to face.

As part of my attempts at designing new coaching strategies that could be used with entirely remote teams, I’ve been going back to basics. This post is about the basic structure that my coaching engagements end up being designed around.


Broadly speaking, I’ve found that all my coaching boils down to one of two categories of topics – known unknowns and unknown unknowns. My coaching engagements usually have two strands running, one for each of these categories. They have different cadences and topics from the “unknown unknown strand” can make their way over into the “known unknown strand”. I’ve not yet seen a topic move in the other direction. Please read The Structure of a Coaching Intervention for a more accurate view of the content I cover when I coach.

Known unknowns are relatively straightforward. This is closer to training, or facilitated learning. Both coachee and I are clear about what knowledge is needed, and we can usually rely on accurate insights from the coachee about their levels of expertise and whether or not it is increasing. I usually end up producing a catalogue of concepts and lesson topics, and my coachee orders them in a list. I suggest changes to the ordering only if I feel there’s a more consumable flow of content (or some pre-requisites). This also has the handy side effect of demonstrating how a delivery team and a product owner can work together to collectively order a backlog.

Unknown unknowns are much harder (especially if the gaps are deep ones such as culture or values & beliefs). Some unknown unknowns can be converted into known unknowns with identification (as there’s a degree of unconscious knowledge in the coachee). Maintaining a general principle of doing no harm, I usually end up doing something along these lines

  1. Observe the natural state
  2. Form a hypothesis
  3. Run an experiment to test
  4. If proven, identify “treatment” options
  5. At some point, bring the coachee up-to speed with what’s happened
  6. Together with the coachee, agree the treatment option
  7. Design the treatment plan
  8. Implement, measure effect, choose to keep or roll back
  9. Restart the loop.

Step 1 cannot be rushed, otherwise my biases play too big a part. In step 8, I’ve only ever had to rollback once in my career, otherwise I’d never have even considered it an option.

Remote Execution

For the known unknown category of topics, being remote poses no fundamental problems, mostly logistical challenges and a greater noise-to-signal ratio in the communication between my coachee and I. It also adds delay to the building of rapport, but that is less crucial when both parties know exactly what needs to be learned, as the coachee can also attempt to infer credibility by their perception of the quality of my coaching materials (legitimately or not is beside the point).

Being remote adds a lot of complexity to my structure – specifically the first step (but none of the steps gets away unaffected). I’ll write up how I approach this later and link it.

Cultural factors that affect your designs


COVID-19 has forced the issue. All my teams are now distributed because everyone’s working from home. As a coach, this has given me a few things to think about. Mostly about how I need to rethink many of my coaching strategies, as they mostly take advantage of the rich information flow that’s tacitly a part of face to face.

As part of my attempts at designing new coaching strategies that could be used with entirely remote teams, I’ve been going back to basics. I need to think about how cultural factors play a part in how I approach coaching. I’m using Geert Hofstede’s cultural dimensions as a framework.

Power Distance

This is the extent to which the less powerful accept and expect power to be distributed unevenly.

  1. Low Power Difference – people prefer to be engaged irregardless of their “position”. They’re more willing to challenge concepts if they disagree, but if they’re persuaded, they become strong advocates. This is where I can find future coaches in order to make myself obsolete.
  2. High Power Difference – people like authority, they prefer solid structures and rules. Agreements can be more easily obtained if they perceive you as being more powerful, but those agreements could swing to the next authority figure that comes along. If enough of the team is like this, then I’ll have to leave something like a “Documented Process with an Owner” to act as an authority figure.

Individualism vs Collectivism

This is to what extent the consequences of an individual’s actions are thought about.

  1. Individualism – These folks take the initiative and act on their needs and desires. They make decisions for themselves. They can be partial to “what’s in it for them” discussions. Maybe focus on how changes can help their career progression.
  2. Collectivism – These folks consider the impact of their social groups such as their teams – e.g. “what will my friends think if I did this”. Discussions about how collectives they care about (their team, their community of practice) can be helped can be effective.

Uncertainty Avoidance

This is to what extent uncertainty and ambiguity are tolerated.

  1. High Uncertainty Avoidance – Prefer deductive approaches, they think things over, make decisions based on reducing the perception of risk (NOTE: that’s independent of actual risk reduction). Also make decisions that follow their preferred deductive strategies (e.g. rational, intuitive etc). Focus more on limiting the downsides, but pay special attention to how they reason.
  2. Low Uncertainty Avoidance – more open to new ideas, better risk taking appetite. Articulate the potential gains that could be achieved.

Tough vs Tender

This is to what extent aggressive competition or nurturing cooperation is preferred. This used to be called masculine/feminine but I prefer more gender/sex agnostic terms as they’re less controversial, especially with new coaching engagements.

  1. Tough – prefer heroic achievements, material gains and competition. Might be worth engaging from a perspective on how the person can stretch themselves, how they can get reward and recognition.
  2. Tender – prefer a more nurturing and caring approach. More interested in a balanced work/life split. Might be an overlap with Collectivism?

Short Term vs Long Term Orientation

This is to what extent time exists in a person’s mental model. From a coaching agile teams perspective, I’d say short term is 1-3 iterations, and long term is 6 months – 1 year.

  1. Short Term – More focus on past and present. Prefer quick results in line with known values and traditions. Language like “low hanging fruit” will probably resonate. These folks will need habit forming nudges to get beyond short term thinking.
  2. Long Term – Better focus on the future. More likely to make trade-offs with short term pain for longer term returns. You’ll need people like these if you’re going to attempt “seismic shifts”.

Indulgence vs Restraint

This is the extent to which a team would act in a way that fulfils their desires, or acts with restraint according to their environmental rules (e.g. office dress code etc)

I’m not really sure if there’s anything I can usefully do with this dimension. However, if something comes up, I’ll amend this post.

Cost cutting and agile teams – finding a way to cope


  • This is not a post about avoiding cost cutting.
  • Not about paying lip service to cost cutting.
  • Not about hostage situations (we’ve come this far, you have to give us more money)
  • This is also not aimed at extremely agile organisations that have active executive engagement with delivery teams, they’re the lucky ones.
  • It’s also not aimed at organisations that have a “courageous executive” supporting an agile approach to delivery. Again, they’re relatively lucky.

Basic Admin

Determine your team’s annual run rate – most likely it’s the base cost to employ your team for a year. Can be awkward if you’re a contractor and have permanent members of staff in your team, but there’s usually a way. Many organisations have either a median cost figure for an “average employee” or a mid-band figure for each employee grade. Make sure you factor in holidays.

It is vital that “team” in this context is the full cross functional team. It makes far less sense to reduce headcount of just one or two roles. By reducing the team skill capacity “relatively evenly”, you reduce the chances that you make a fatal cut. The corollary to this, is if your team is significantly unbalanced when compared to the work they deliver, then consider a rebalancing exercise first.

It’s pessimistic, but reliable to assume that all the other “overhead” costs associated with project execution will remain unaffected. Given the likely conditions, being able to reduce the non-value-add-overheads would be something outside your sphere of influence.

Convert your cost cutting target into an equivalent team burn rate. This gives you an indication of how much smaller your team has to be in order for you to fit within the requested cost envelope.

Your most expensive people are usually more experienced. Therefore, it’s reasonable to assume that your pared down team will not be as capable, and therefore will increase the rate that errors are produced. You have a trade-off decision to make – accept the lower quality output or sacrifice some of your (reduced) “volume output” to maintain your quality levels.

The most significant factor (for me) in making this decision, is how long that system / component needs to be changed/developed. For example a single use component that will only be used for 3 months (i.e. disposable) can be generally tolerated with a significantly lower quality than a system that needs to regularly evolve over a period of a decade. Lehman’s Laws of Software Evolution are worth revisiting for inference.

Assuming that your reduced team will have to maintain their system for a long time (the average life of an IT system is about a decade, if this article is to be believed – “Software Lifetime and its Evolution Process over Generations”) then you have no real choice when it comes to quality or output – you have to prioritise quality.

That brings you to your next challenge. How do you compensate for the fact that your team will simply be not as skilled once you lose some members? Simply continuing your team’s way of working and hoping for the best is unlikely to succeed – with the reduction in expertise, your team will produce more bugs.

Your basic strategy should consist of two strands – to cope with the increased bug density, and to reduce that skills deficit. To cope with the bugs, use a suitably balanced combination of tactics:

  • detect bugs earlier in the lifecycle,
  • reduce the complexity of the bugs that are found,
  • reduce the cognitive load required to fix the bugs, and
  • reduce the impact  of the bugs that do make it through your delivery process unnoticed

A word of caution on the reduction of skills deficit strand – it’s a much slower solution than introducing coping mechanisms for the increased number of bugs and cannot be relied on as the primary solution strategy for short-medium term improvements.

When developing your mitigation tactics, it is sensible to avoid as many options as possible that rely on individuals in teams “working harder” or working with “elevated skills” as those are unrealistic. The lever you can exert the most significant change with is team behaviour, specifically team ways of working. It would also be sensible to incorporate working patterns that boost individual learning, as that is an approach to (eventually) reducing that expertise gap.

Detect bugs earlier

All bugs are detected because of an incongruity between what is observed and what is expected from a model (regardless of whether or not this model is tangibly identified or implicitly part of the knowledge that your product owner / subject matter expert / developer / architect etc. has. Each person / role would have a different model representation and therefore would be able to detect different bugs.

One strategy for detecting bugs earlier, is to compare observations to as many of these mental models as soon as a possible, for example by having product owners or SMEs be actively embedded within your delivery teams, working alongside the developers daily. The most established strategy for increasing visibility of the work being done as early as humanly possible is pairing, especially pairing with different roles (e.g. developer and analyst, or analyst and tester). Pairing is also one of the most effective mechanisms available for reducing that skills deficit.

Another strategy for detecting bugs earlier, is to perform downstream activities sooner (for example production deployments). There are associated costs – for example the delivery strategy will need to be based on incremental development where thin slices of “complete” functionality are built, integrated and deployed. Organisations that are more sequential in nature (for example, organisations that have a difficult / scary / time consuming / manual “route-to-live” process) tend to get the biggest benefit from attempting this, but they’re also the organisations that are the most afraid to try.

Reducing the overall duration between creating the bug, detecting it, and fixing it will reduce the cognitive load required to fix the bug, as the team’s working memory will already be loaded with the appropriate context. Discovering a bug “a long time” after it was created will require significantly more mental preparation to re-gain the mental models in play at the time of creating the bug.

Reduce the complexity of bugs

Given that all bugs are coded, the only fundamentally viable strategy to reduce the complexity of bugs that are found is to write simpler bugs. I find Einstein’s original quote can be helpful to communicate this message:

“It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience”

Albert Einstein

A scientific approach to analysis can be helpful as it can help reduce the number of “implementation patterns” that exist in your IT solution. That may introduce learning curve challenges, e.g. if your delivery teams are unaccustomed with hypothesis driven development.

Structured techniques such as test driven development can also help, as they help manage the “thinking complexity” of software development, as well as have the side effect of producing tests to be able to continuously monitor your code quality over time (even more helpful when your team’s expertise has been lowered). But watch out for common problems in tests – e.g.

But the biggest strategy to use to help reduce the complexity (and number) of bugs in your system, is to write less code.

Reduce the cognitive load

Employing strategies that reduce the complexity of bugs also have the side effect of reducing the cognitive load needed to understand and fix the bug. Additional strategies can include:

Working in smaller blocks would also serve to act as a limiter for the amount of complexity that can possibly be present in each block. Work partitioning techniques such as user story decomposition can help.

Techniques that use both visual and auditory inputs are easier to process by people, as the two modes are processed by different channels and use different working memories. Techniques such as Rubber Duck Debugging are a form of a think aloud protocol where the auditory channel can help an individual formulate a hypothesis along a fundamentally different line to what they can see, thereby increasing their effective cognitive ability.

Working in larger groups (for example, see mob programming) can be an extremely effective technique for always maintaining a high degree of cognitive capacity consistently as the overall effect is to smooth the natural peaks and troughs in the cognitive abilities of the individuals (e.g. some people are morning people, others are night owls etc., but there’ll always be someone “firing on all cylinders”). Linus’ Law is a concise articulation – given enough eyeballs, all bugs are shallow.

Reduce the impact of bugs that escape

It’s inevitable that bugs will escape into production. The final dimension to consider is about recovery. The easier and faster it is to recover from a production incident, the less severe the effects of the problem. Recovery time is spent:

  • locating the root cause of the fault
  • fixing the root cause
  • delivering the fix

Locating the fault: there are two basic (and complementary if required) steps to take. Your triage and fault finding processes could determine if the bug was introduced as part of the last release, as well as where specifically in your solution the fault lies. The first piece of insight could take considerably less time than the second. If the fault was introduced as part of the last release, one possible early response could be to roll-back the release, which act to stop further failures from occurring. A robust fix can then be developed and a new release planned. This naturally comes with an “opportunity cost” associated with not having access to the rest of the functionality also present in the pulled release. This opportunity cost can be virtually eliminated, but it will require the ability to release every single change independently. Development and deployment strategies (e.g. using trunk based development and feature toggles) can greatly reduce the complexity associated with this.

Fixing the root cause: strategies outlined earlier to reduce the cognitive load and identify bugs earlier also help here.

Delivering the fix: This is inherently limited by the speed, flexibility, resilience and degree of automation of your route-to-live processes. The single biggest change you can make to drastically improve your delivery processes is to reduce the size of each release (get as close to release each minor change independently) and repeat the release processes constantly (I’ve experienced multiple releases a day into production, even in a public sector context). Attempting to do this will identify all of the sticking points and problems associated with your route-to-live processes, and will give you areas to target improvements. It is almost always helpful to decouple software deployments (technical, automated, controlled by delivery teams) from business releases (business triggered, business features are toggled, aligned with wider organisational change programmes) as you are then able to decouple automation improvements from business change readiness.

Final Thoughts

These are useful strategies for coping when your delivery teams have to compensate for a reduction in their base capabilities. However, there is nothing fundamentally preventing delivery organisations from just implementing these strategies to increase the effectiveness of the teams that they currently have. Is anything stopping you?

The Structure of a Coaching Intervention

Coaching is an act of leadership. The main purpose of coaching a team is to improve the overall effectiveness of that team. Three key dimensions in assessing this are:

  • Productive output that meets or exceeds the standards of quality/quantity/timeliness of the consumer
  • Social processes the team use that enhance the future capability of the members to work interdependently as a team
  • The group experience that contributes positively to the learning and personal wellbeing of the members

There is an additional factor, often classed as crucial to team effectiveness – the quality of personal relationships within the team. However, I’d class any work done with the team that directly addresses problems with personal relationships to be counselling in nature, and isn’t in scope for this post. In my experience, when the delivery effectiveness of a team improves, the morale boost in the team members has a side-effect of improving personal relationships.

The relative importance of these three dimensions will vary over time, but successful teams always make sure that they are all considered and balanced over time, never completely sacrificing one to optimise the other.

The effectiveness of a team at performing a task is influenced by these three key performance factors:

  • The effort a team expends
  • The appropriateness of the strategies and techniques that the team uses
  • The skills and knowledge that the team can bring to bear

Therefore, in order to have any sort of effect on a team’s performance (beyond the Hawthorne Effect), coaching will need to help one or more of these factors.

There are three important factors to consider when delivering a coaching intervention, and all three must be balanced in order for the intervention to be effective:

  • Content
  • Delivery approach
  • Timing

Coaching Content

The messages that are conveyed during a coaching intervention typically conform to one or more of these three main patterns:

  • Motivational: coaching that addresses effort, e.g. inspiring team members to increase effort, or minimising freewheeling
  • Consultative: coaching that addresses strategy choice, method selection, helps teams determine locally optimised methods
  • Educational: coaching that addresses skills and knowledge gaps

It is important to use the right content to address the specific challenges that the team has. For example, if the challenge is a shortfall in specialised skills needed for a task, providing a highly rousing motivational speech isn’t going to help.

Three Main Coaching Approaches (plus a fourth – “eclectic”)

The reality is that most coaching interventions will have aspects that originate from more than one of these three approaches.

  • Process Consultation: structured/clinical examination of interactions from a workflow perspective:
    • between the team and external teams/stakeholders/etc
    • internal to the team
  • Behavioural Models: feedback on individual and team behaviours, mainly focussing on relationships and how feedback is given and received; often involves operant conditioning
  • Development Coaching: identification of areas that need improvement, along with focussed time set aside for learning / training sessions
  • Eclectic interventions: ad hoc interventions, with no specific underlying theoretical model; most commonly limited to personal relationships when coaches aren’t familiar with the specifics of the work the team is doing

It is important to use the most appropriate coaching style / approach to suit the context, the audience and the message. For example, when working with an inexperienced team to improve the effectiveness of their in-flight process flow, it is better to use their real work and their real process as opposed to a classroom styled session with an abstract case study.

Intervention Points

Teams go through different phases as part of them starting, working on, and finally finishing, a piece of work. There are several broad model categories that attempt to describe the team and their approach to work temporally (see ). Two patterns that I’m broadly aware of are:

  • Incremental (or Linear) Models (e.g. Tuckman)
  • Punctuated Equilibrium Models (e.g. Gersick)

The interesting thing (for me) is that I’ve seen groups of people becoming teams display characteristics found in both. For example, I see teams regularly using retrospectives, but for the most part, the improvements are relatively narrow and focussed in effect. However, there are usually a small number of seismic shifts in ways of working – usually as a result of a significant “precipice” being felt. The most common precipice is the realisation by the team that they’re halfway through their estimated (or constrained) timeframe. These events are where coaching can deliver the most impactful benefits and are typically found at:

  • the beginning,
  • the midpoint, and
  • the end

A side-effect of teams splitting large blocks of work down into smaller pieces (e.g. Epics, Stories etc.) is that these events occur far more frequently – each user story has a beginning/midpoint/end set that could be used as opportunities for coaching interventions. I’ve rarely seen coaching interventions at user story boundary, but I have seen them at Epic or Feature level.

Other team processes that also create opportunities for beginning/midpoint/ending events to occur include the use of iterative (or sprint) based development, using a delivery lifecycle (such as DAD’s risk/value lifecycle) etc.

Designing a Coaching Intervention

The design and structure of a team has a significant effect on the effectiveness of coaching interventions. “Well designed” teams gain more value from a coaching intervention, even a poorly executed coaching intervention. “Poorly designed” teams can suffer negatively during a poorly executed coaching intervention. I’ll focus on team design in a separate post. For this post, I’ll assume no ability to fundamentally change the structure of a team to better match the workload.

Looking at the three performance factors, what are the underlying constraints? If a team has a constrained “strategy & technique” factor, then any attempts to change the execution strategy is likely to be met with frustration.

Once you have some clarity on the performance factor you can help improve, pay attention to when you introduce the intervention. Teams at the start of a piece of work are generally unwilling (or sometimes even unable) to have an informed discussion about what their optimum delivery strategy should be – it’s usually better to get started and then make an adjustment at the midpoint event (when they have some actual experience to base the decision on).

Target Performance FactorEffectiveAvoid
Effort – Motivational Coaching
– The beginning
– Consultative Coaching
– Educational Coaching
Strategy  & Technique – Consultative Coaching
– The midpoint
– The end
Skill & Knowledge – Educational Coaching
– The end
– Motivational Coaching
– The beginning

Once you’ve got a sense of the target performance factor, the timing of the coaching intervention and the key messages that needs to be conveyed, the next step is the execution approach. It’s worth investing effort in explicitly designing coaching interventions (not to mention ensure sufficient variety to keep things interesting for you and your team). However, there are some natural alignments between the conceptual approaches and the content to be conveyed which could help get you started.

Coaching Content Approach
Motivational Behavioural Coaching – personal motivation, team camaraderie.
Developmental Coaching – focussed time set aside for “kick off events” (such as an Inception workshop or a Visioning workshop).
Consultative Process Coaching – clear understanding on pros and cons of alternative techniques so a mid-flow course correction can be made.
Educational Development Coaching – periods of reflection and improvement via a team retrospective, knowledge transfer via lunch & learn sessions, skills acquisition sessions using learning katas.

Courageous Executives and the Permafrost

Last week I started to think about how different parts of an organisation have different views on what is important.

This is nothing new. Why should I keep reading?

I think the existence of that permafrost layer is problematic if want to be inventive or innovative. If you’re looking to evolve into a “courageous executive” then credibility associated with reducing that middle layer could be useful. However, to stand a chance of success when you “fight the machine”, you should pay attention to the basics, including:

  • the degree of effective support you’ll have,
  • the culture underpinning your sub-organisation, and
  • how different the “volumes” are when comparing your sub-organisation’s culture with the wider organisation’s culture.

In this context, “sub-organisation refers to the subset of the organisation under your sphere of influence, either formally via org chart or informally via your influence, credibility, relationships etc.

If you intend to create space for your organisation to innovate and experiment, then it’d be advantageous if it is more naturally innovative and experimental. That requires a different attitude to failure than when saving face is a preferred reaction to failure. To paraphrase, you’ve got to shrink that middle layer (conceptually).

A useful strategy that can reduce the size/significance of this middle layer is dealing with fear from a cultural standpoint. Something that can help the formulation of specific strategies is an understanding of how the Loss Aversion and Loss Attention cognitive biases manifest in the individuals that you identify as being significant anchor points in this middle layer.

  • Loss Aversion: It is better to not lose £10 than it is to find £10.
  • Loss Attention: Tasks that involve losses get more attention than tasks that do not.

A clue to something that seemed to help me is that bottom level. When this scenario was presented to delivery teams, they didn’t seem worried about saving face when faced with that hypothetical scenario. Digging further, it wasn’t that face/reputation was unimportant, it’s that they didn’t care all that much about what the “middle management types” thought about them (it’s how individuals seemed to interpret the scenario). That middle management group was not considered to be their judging community. They were far more concerned about their reputation amongst other delivery folks. For example, a developer might try and force a software library to work, applying workaround after workaround, instead of just accepting that the library was the wrong fit for what’s needed (because they wanted a reputation of being able to make anything work). However, that same developer might not be concerned if their boss’s peers don’t think much of them, if they don’t care about the office politics.

That got me thinking that perhaps one way of reducing that awkward middle layer, was to change their perceptions about what was important to the community that they considered was judging them. I think this is different to tackling their priorities head on, in that it’s less confrontational, so stands a better chance of working (at least partially). That middle layer would need to view organisationally significant things like money or time or customers etc. to be something that could be truly lost (so that their normal loss aversion and attention biases would influence them in ways that were beneficial, if you were indeed trying to grow into a courageous executive). They would also need to feel that personal reputation could not be lost in the same way.

Changes to that community can be as a result of external or internal pressures. Assuming you’re not “senior enough” to be able to enforce a new operating model the community must comply with, your more effective strategies would be the ones that originate from inside that community.

Potentially Useful Infiltration Techniques

  1. Repeated Messaging: Humans are influenced by exposure. The first time something controversial is heard, it’s shocking. After the hundredth time, it barely registers consciously. Interestingly though, the subconscious still registers. In that way, people can be programmed. By repeating your message regularly into the target community (and with variations to keep it interesting), over time you’ll lower resistance to your ideas.
  2. Let others get credit, even if the ideas are yours: Having others in the community get an endorphin rush when they share an idea influences them to repeat the behaviour. So it’s your idea really, so what? You’re aiming for something else. Besides, a few people will know anyway. That “inside knowledge” can be a powerful aide to your attempts at growing an organisational culture that has you as an executive – it creates a sense of belonging between you and them, which if nurtured can transform into loyalty.
  3. Be seen to be visible to the next few power levels up: For the hierarchically minded, seeing you playing nicely with their boss and their boss’s boss, can signal that it’s more acceptable for them to align with what you’re saying. It has a secondary effect to help you gauge whether or not what you want to do is palatable to the next few levels up the power structure. If it is, then it can be an indicator that there is space for you to grow your leadership potential.

Save Money or Save Face – What would you choose?

Thought Experiment

You’re in charge of “A Thing” and are accountable for the successful execution of the objectives that the Thing has (e.g. you’re the CTO in charge of the IT Department, or you’re the Project Manager of a strategic project). Which of these scenarios is worse?

  1. A decision you make results in a significant financial loss for the Thing. However, you do not suffer any loss of face (e.g. you can successfully employ the “circumstances outside my control” defence).
  2. A decision you make results in the Thing avoiding a significant financial loss. However, it goes against the political winds and you suffer a significant loss of face.

Just what is important?

I’ve been trying understand how the notion of “what is important” varies in organisational structures. A pattern that seems to be emerging is that what is of primary importance falls into one of three zones.

  • The first zone values money, externally mandated timescales (e.g. legislation etc)
  • The second zone values their personal reputation, their personal “empire”
  • The third zone values their use of time – being able to spend it on valuable or meaningful work

These three zones look very similar to the zones in organisations when thinking about appetite for change (e.g. very senior leadership is the first zone, the delivery teams are the third zone and the “permafrost layer” are the second zone).

The thickness of each of the three zones/layers is an organisationally specific function, and seems to exist no matter what the scale (for example, I’ve even seen this sort of structure in project teams, for example when a product owner is too busy and a business analyst operates as a message passing proxy). The existence of this middle layer correlates with size, but is not caused by size. One factor that reinforces the middle layer is fear of failure, which is heavily influenced by the personal history of everyone concerned. Given any degree of employee churn, I think it’s impossible to have zero middle layer.

The important question for me, is so what? I’ll look at that next.

Building a Knowledge Sharing Community

Why am I trying to establish this?

Having an effective knowledge sharing strategy that my consultants and coaches use effectively can significantly boost the quality of their deliverables on engagements, as their access to knowledge and experiences will be richer. Richer knowledge leads to better decisions which lead to better outcomes blah blah blah.

No really, why?

The truth is far less grandiose. And much more personal. I want better relationships with my colleagues. And the main reason for that is selfish. When I’ve got something interesting/gnarly to solve, I’d MUCH rather solve it collaboratively with someone. I find the ideas that come out of a buzzing pair/trio are generally FAR superior (not just in terms of merit, but also the emotional responses – things like surprise, delight and even just pure joy) than anything I’d come up with on my own. A major contributor to that heightened emotional response is the fact that it’s a shared experience – this has a reinforcing effect on the individuals.

This topic is also related to my post on Courageous Executives – I think being able to create an environment where knowledge and help is shared freely and easily is helpful in establishing a progressive organisational culture.

Some things to consider

The first thing I need, is critical mass. I need enough colleagues with sufficient latent willingness to participate to increase the odds of interesting interactions to occur.

The second thing, is to recognise the reality of the group dynamic. I work for a consulting organisation, and like most others, they staff people on engagements. Those engagements have teams. Back at base though, I’m grouped with a set of similar people under the same line manager. That line manager’s “team” is not a team from a behavioural dynamics perspective, regardless of how the individuals describe themselves. Esther Derby is my go-to source for concise articulation of what it means to be a team.

The third fundamental aspect to consider, is how people participate. The “1/9/90” rule of thumb has been around for over a decade now, potentially longer. A quick recap: For online groups, there are three broad categories of interaction

  • 1% of the population will initiate a discussion thread
  • 9% of the population will actively contribute to discussion threads
  • 90% of the population will lurk

I also reasoned that in order to sell what I wanted people to do, it needed to be more engaging/arresting than just these numbers (which no doubt many of my target audience would have heard already, so there’d be little impact). While daydreaming about how to go about launching this, an idea flitted across my mind, which amused me. I ran with it, just to see how far I could go. Fishing.

  • Lures: These would be the “1% and 9%” of the population. Their job is to make the environment interesting/appealing enough for the others to participate.
  • Fish: These are the 90% of the population who lurk. My objective is to convert them into lures by engaging them.

Above all else, the most important thing to remember was that knowledge management was all about people. We have to avoid the temptation to create yet-another-document-repository, as those end up generally being pointless (keeping a stack of documents current is a huge time investment, so very few people do – the documents become outdated quickly and users lose confidence in the repository as a source of relevant information).

How did we start?

The first step was to get a sense of that latent willingness that I needed. To avoid unnecessary confusion, I stuck to a typical technique – I ran a workshop. The stated objective was to understand the key topic areas / themes that as a collective, we had some self-professed expertise in. The exam question was

write down topics, regardless of scale, that you would be happy for a colleague to come to you if they needed some help

Approaching the audience in this way would nudge them into feeling valued from the outset (the alternative would be giving them a candidate set of themes and asking them to sign up. The list at the end of both approaches would be the same, but the first scenario would have far more engaged individuals as they’d own the list). This workshop also let me find co-conspirators.

Then what?

In a word, admin. We had to create a navigable map of the topics that the audience had supplied (it would help people find the right place to ask questions). In the end, we settled on a very basic two-level tree consisting of high-level themes and more detailed topics. That allowed the grouping of individuals to be based on themes with related topics. The main rationale was that as experience and knowledge changed over time, the specifics of the topics would evolve, but the main theme would remain constant. That allowed for stability of membership – and that membership stability is a significant factor in determining whether or not a theme would survive. The candidate themes also had candidate lures – they were the list of people who volunteered for the topics that were under that theme.

We had to sell the themes to the potential lures.

We also had to set some expectations about what being a lure entailed. By this point the term “Theme Guardian” had started to emerge as the role that was to be played. This is what we ended up with.

  • Guardians own their Theme
  • Guardians are responsible for the quality and integrity of the Theme’s content
  • Guardians should invest in PDCA cycles to improve the environment in the Theme.
  • Guardians need to evolve their vision and strategy for their Theme.
  • Have “something” to help new joiners understand your Theme.
    • This doesn’t necessarily have to be a document. It could be quarterly intro sessions on WebEx (for example).
  • Set expectations of how you’d like the community to operate – and remind your community regularly

I find analogies very useful as abstraction models to help me understand a domain/problem. In the event that at least some of the candidate guardians operated in a similar manner, I picked a couple of potential models that they could use to refine their thinking about how they wished to operate:

  • Town Planners and Communal Spaces. What makes some public spaces incredibly successful, and others turn into ghost town?
  • Aboriginal Storytelling. In particular, explore the claims that the Dreamtime stories have remained intact for over 10,000 years without degrading, despite only having a verbal/pictorial, not written form.

Selling the concept

Now that we had a starting position (themes, candidate guardians, some guardian responsibilities), we needed to launch. To help that, we produced some general use guidance on themes:

  • People are at the core of any successful knowledge management strategy.
  • Information held in a person’s head is updated as a by-product of things that person does. Information stored in documents requires additional explicit effort.
  • For a Theme to be useful, knowledge needs to flow from person to person.
  • If a Theme’s only got one person who’s interested, it’s not a Theme.
  • When a question is asked, directly answer. Even if it’s been asked before. Never rely on a document (or link etc.) to answer for you. If necessary, end your answer with “this document/link/other goes further” (or words to that effect).
  • Think about what your “background radiation” looks like. Themes need to feel active otherwise you won’t get people stopping by and asking questions.
  • Have a variety in the complexity / subtlety / nuanced nature of the conversations and discussions. For example, if you only have very high brow discussions, you’re likely to put off the inexperienced. If you only have introductory content, then the experts may not participate.

Launch Day

These were our objectives

  • Start small: We picked one Theme that the co-conspirators were willing to act as Guardians or as participating members. We would attempt to orchestrate and create an active community for that theme.
  • Momentum: We wanted to create some observer habits in the wider community. With enough people checking in daily (for example), we’d greatly increase the chances that conversations would spark up. But we had to kick start the making-it-worth-everyone’s-time process.
  • Win over an influential sceptic: Having a known sceptic promote what we were trying to do would help persuade other sceptics that there may be some mileage in investing in this strategy.

What happens/happened next?

1 Week After Launch

There’s a smattering of interest from a handful of people. A few posts have been made and there has been some commenting on posts. Some of the early efforts from the co-conspirators have been around motivating and inspiring the community to participate. There is some optimism around that this approach feels different (probably because it isn’t tools oriented).


It’s still early days, but these are my (current) predictions.

1 Month After Launch

The conversation topics broadly split into a handful of themes. Most of the themes appear to be consistent with what emerged from the initial workshop, but the actual topics discussed are quite different. There is some dissonance from the earlier adopters as there are multiple unrelated themes being discussed in the same “place”, causing confusion.

3 Months After Launch

Enough interest in different themes has triggered new spaces on the platform for the conversations about those themes to be segregated, to simplify the cognitive load on the users. There is some frustration from some members who are interested in multiple topics, most likely due to how the individuals have modelled the interactions mentally – e.g. why should two people who are talking about a range of subjects have to keep switching which “chatroom” they converse in. Relationships are still point-to-point.

6 Months After Launch

Most of the theme chatrooms are now dormant, most of the activity has gravitated towards one or two Themes. There’s some blurring between the competing mental models – relationships are person-to-person and person-to-community.

Analysing my predictions

One of the most significant challenges I’ve seen in Knowledge Management things is the belief (usually tacit) that it’s all about the content. I believe it’s all about the relationship, and the knowledge of who to talk to when a person needs to know something. My predictions have a base assumption that Knowledge can be structured and organised at a fine grain. I think that’s an assumption that’s also being made by the majority. I’m expecting this assumption to be proven to be false and that we will pivot back to trying to be more of a community than a knowledge repository. Looking at the population numbers, I don’t believe there’s any need for more than two or possibly three communities (eventually).