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Navigating the Complexity of Learning & Performance in Sport

 
Mark Upton
 
Jul 29, 2015


The following is really just “thinking out loud” (hat tip Ed Sheeran) in the hope something coherent emerges. It emanates from recent discussions, experiences and reflections on the complexity of player/athlete development and performance at all levels, and the influence of coaches, sport scientists, parents, administrators and others.

In previous posts we have conceptualised players, coaches, teams and sporting organisations as complex systems so we won’t go back into detail on that now.

“For every complex problem there is an answer that is clear, simple, and wrong” — H. L. Mencken

Yes and no. For coaches that have little experience, base their practice on “what has always been done” and without critical reflection, then I would say this potentially rings true. For others that have embraced, navigated and “marinated” in these complex problem spaces for a period of time, the “clear and simple” solution may in fact be very much effective. This respects the nature of dealing with complexity, where relatively simple solutions (generated from rules of thumb & principles) can be highly effective. A recent example of this was an experienced manager opting to “do nothing” for the time being in relation to the next action in dealing with a complex (uncertain) problem. Unfortunately we often confuse complex with the need for complicated solutions and drift off into a futile search that, as a coach I used to work with would say, has us “flat out doing f***k all”, and often accompanied by a significant time & resource cost.

There are also social and cultural misconceptions about dealing with complexity and the inherent uncertainty that accompanies it…

The above sentiments were also echoed by a sport psychologist espousing the need to remove complexity from decision making processes. This desire to remove or reject complexity, in cases where it truly exists, is not helpful.

 


Many Sport Scientists struggle to deal with complexity and fail to respect that good coaches have developed (tacit) knowledge and expertise that enables them to function effectively without having to quantify everything and prove “cause and effect”. Coming from a culture of Newtonian Science where deterministic thinking reigns, young Sport Science practitioners can be “paralyzed” when data and a textbook fail to provide THE answer as to the most effective next action.

From the late-17th Century until the early 20th, the Laws of Motion and other linear, mechanical principles discovered by Isaac Newton dominated the understandings of science and filtered down into every aspect of the Western world. This view of reality over time penetrated our education system, our culture, our language, our organizations and our management practices so completely that it became taken for granted. Most people are not even conscious that they are using what is called the mechanical view of reality when they think and talk. This view of reality assumes:

* Things happen because something causes them to happen (cause and effect).

* We can understand what happened by reducing things to their components or parts and examining those parts (reductionism).

* The universe is orderly, follows natural laws, and works like an incredibly complicated machine.

* The best way to manage people is to organize them into a clear structure and control them with clear directions.

* The best results occur when work is streamlined to be as efficient as possible, with a minimum of wasted effort, producing the most output in the least amount of time (the “lean machine”).

source: http://www.codynamics.net/science.htm


Experienced practitioners have come to realise there are other ways of working. Nick Grantham has written a couple of excellent blog posts –Push the Button and Programme Design: The Answer. Nick describes an approach to dealing with complexity and uncertainty that is advocated by complexity experts — that is, pre-intervention analysis and data collection will provide limited value. The best way to better understand the dynamics of a complex system is to take action (ideally with small “safe to fail” experiments) and sense how the system (player/athlete/team/organisation) responds. This informs the next response, particularly whether to amplify the action or dampen it (try something different). Another caution when dealing with complex systems — “copy and paste” methods are likely to fall flat, ie what worked with one player/situation/environment possibly won’t with another.

An experienced sports nutritionist described this recently — a nutritional intervention that produced great results with one athlete was “copy and pasted” with the next athlete, but resulted in completely different (non-desireable) outcomes. We also see this with head coaches in team sports who think the “drivers” of success with one team/club can be replicated with a new team/club, only for things to pan out completely differently. The takeaway is that in a complex system, there are rarely single actions that are “drivers” – only modulators. It is an easy trap to fall into as we have a tendency for retrospective coherence – looking back on a specific situation and, with the benefit of hindsight, being able to identify the mechanisms that resulted in a certain outcome(s). We then risk “copy and paste”, claims of “best practice” etc.

Darren Roberts featured on a podcast recently and described the “performance playground” he tried to create for his extreme sport athletes. This exploratory space for trial and error (not to mention athlete autonomy) reflects a good way of working with complexity, in this case the performance and/or rehabilitation of these amazing athletes. The “performance playground” reflects the approach Al Smith and I are proposing in our quest to support people who want to create dynamic learning environments. Yet Darren’s was equally a cautionary tale, making specific reference to the fact that these environments do not lend themselves to easy forms of measurement and the pretty colours on spreadsheets that many are fond of.

This leads to my final thought on the escalating obsession with measuring and quantifying everything. Whilst there is clearly great value to be derived from data when used appropriately (narrative data is proving useful in complexity), I’m more concerned with the dynamics that are driving this obsession, which seems to stem from a desire to control everything and remove uncertainty, remove complexity. Attempts at Talent ID from a young age reflect this.

If we are genuinely committed to helping players/athletes be their best, we must embrace the fact that player development, coaching, applied sport science is messy…complex…uncertain. Our actions, methods, frameworks, policies, processes and organisational structures must then reflect this. Do this and we increase our chances of successfully navigating towards positive outcomes and rewarding experiences.

…“thinking out loud” complete 😉

Espoused Values

 
Mark Upton
 
Jun 17, 2015


Whilst enjoying my morning cappuccino in a coffee shop recently (coffee is inadvertently becoming a theme of our blog posts!), I happened to overhear a conversation on a nearby table. It seemed to be a job interview of sorts.

The “candidate” must have been applying for a position involving management/leadership of a team. During one section of the conversation the candidate was effusive regarding their desire and ability to empower team members with decision making responsibility, whilst also creating a “safe to fail” environment. This all sounded positive enough.

However, barely a couple of minutes later, the candidate elaborated on a past experience when a team member made a critical error on a project. They explained there was no choice but to remove the person from the project and take control of the process in order to “get the project back on track”.

Needless to say, my immediate thoughts centred on the misalignment between the earlier comments (espoused values) and the lived experience (behaviour). What happened to the empowerment and safe to fail environment? At the first sign of trouble, that all went out the window. Interestingly, the interviewer didn’t seem to pick up on this (or maybe they made a “mental note” without changing the flow of conversation).

This is not an unusual situation in coaching and the sporting environment. When the pressure comes on or errors are perceived to have been made, it seems a common response is to take back control (given it was actually “handed over” in the first place). As digital media has enabled increased access to coaching-related articles, information and people, “buzzword bingo” has also become a popular game. At times, and often still with the best of intentions, the values and beliefs espoused by coaches are incongruent with how they actually behave. Why is this?

Given the coach and their environment represent a “complex system” (here for our first post on complexity and here for HumanCurrent’s explanation), there could be many interacting factors at play that influence what a coach says and does. As one example, the de-contextualised classroom environment common in formal coach education may enable a coach to verbalise key topics, but limit transfer to the context of their coaching environment.

For those looking to enhance coaching effectiveness and the quality of learning environments, understanding these dynamics is critical in order to facilitate the emergence of functional patterns of behaviour. Whilst early days, it has been enjoyable exploring and applying methods related to this in our work in sport. We look forward to further learning and exploration as opportunities arise to apply these ideas in different contexts and help people be their best.

Is technology getting in the way of self-organisation?

 
Mark Upton
 
May 21, 2015

“Self-organization is not a startling new feature of the world. It is the way the world has created itself for billions of years. In all of human activity, self-organization is how we begin. It is what we do until we interfere with the process and try to control one another.”

Margaret J. Wheatley and Myron Kellner-Rogers

A quick scan of twitter and blog feeds never fails to turn up the latest technology ventures trying to make an impact in sport, generally making similar statements regarding a learning/performance edge. Take this claim from a new video technology offering…

“allows athletes to gain greater insights into the finer details of what their bodies are doing when the action occurs, which helps them improve their game”

Does it really improve their game? What does the emerging evidence suggest about skill learning?

Well it strongly challenges the claim that athletes having greater focus on the fine details of their movements is beneficial for learning/performance. This is based on a key principle of complexity theory – self-organisation. Top-down control (i.e. being consciously aware of and trying to minutely control the body) can inhibit these self-organising capacities, prevent optimal coordination of body segments and ultimately hinder learning and performance. “Form follows function” is important to remember in a complex system, be it an individual player, team or organisation. There is a need for intention/purpose, whilst resisting the temptation to exert rigid control over the manner in which it will be achieved.

Interestingly, we can equally apply the principle of self-organisation to a group of people — lets say a coaching and sport science team in a football academy. Rigidly defined roles, objectives and departments imposed from above can actually inhibit the ability of this team to self-organise and coordinate their efforts around a shared purpose of player development. In fact, silos, “turf wars” and “us against them” mentalities are likely to emerge. However, these tightly defined roles and objectives (and check box assessment of them) do suit performance management technology solutions. Just as the video technology mentioned in the opening, the increasing use of these technologies, used inappropriately, may actually be hindering the coordination and functioning of the off-field team.

These 2 examples demonstrate how complexity theory principles can scale to different system levels — from an individual player, to a team, to a club, to a governing body of sport.

We are basing what we do (helping people be their best) on emerging evidence from complexity theory and ecological dynamics. We use this to help people shape their (learning) environments and, in this particular example, make good decisions regarding the utility of technology in those environments.

N.B. an important addendum to the principle of self-organisation is the role of constraints. Expertly manipulating constraints can shift a system (player, team, club, organisation) towards a more functional state. Hence the growing interest in the constraints-led approach to coaching & pedagogy — something we will cover in more depth in future posts.

Helping People Be Their Best is Complex (not Complicated!)

 
Mark Upton
 
May 13, 2015

The I recently had an interesting conversation with a gentleman (let’s call him Paul) who has many years of experience in a leadership role with an iconic global company. The conversation sparked reflections on learning and performance of people. What makes Paul’s story intriguing is that the company he worked for manufactures products and relies on a strong engineering skill-set. Did they also take an engineering approach to managing the learning and performance of their people? Happily, based on the following examples, it seems they did not.

The first example Paul gave was being trusted and given the freedom to take ownership of his role by those “above”. They resisted the urge to micro-manage and measure his performance in great detail (a classic engineering approach). Paul described the positive feelings this generated and the subsequent benefit to his performance. Only late in his career did this micro-management invade his environment, partially leading to a decision to move on.

The second example he shared concerned the tremendous growth/learning he experienced through being mentored. He explicitly talked about having a “safe” environment to converse on any range of topics/problems/decisions that were on his mind. This mentoring relationship was paid for by the company and was ultimately about improving his performance, but there were no specific targets, measures, development plans, timelines etc attached to the mentoring process. Yet Paul described it as the most impactful developmental process he has undertaken.

The key message here is understanding how learning and performance of PEOPLE can be managed/facilitated in different ways. Assisted by the growth in technology and data, an increasing trend is to take an engineering approach. This implicitly frames the process as “complicated”, when in fact the learning/performance of one or multiple people is almost always “complex”. This distinction between “complicated” and “complex” is critical and seems to be one Paul’s company were attuned to (despite their core business being very much engineering based). John Kiely provides further insight…

A machine may be an intricately engineered marvel of human ingenuity; may be fabricated from the most resilient materials; assembled from precision engineered inter-locking parts, each methodically fulfilling its tightly specified role.

We, on the other hand, come in all shapes and sizes; even changing shape as life progresses. Yet, even though Nature has no mechanism for precisely replicating component parts; despite ill-fitting moving parts; we seem to fit together ok. We can survive the loss of component parts; we can continue our lives even after areas of the brain have been damaged or removed.

In fact, no dimension of our biology resembles machine-like behaviour. Unlike machines we constantly modify aspects of function — dispersing stress, sharing workloads — in response to changing life demands.

So there is a distinction to be drawn between ‘complicated’ and ‘complex’ systems.

Complicated machine-like systems typically follow one path to achieve a specific end, and as such are highly predictable; but also highly vulnerable. Complex systems achieve their objectives through a process of exploration and on-going adaptation; negotiating obstacles, solving problems through trial-and-error, and flexibly adapting to changing circumstances.

(for further insights into complicated, complex and other systems check out Dave Snowden’s work and the Cynefin framework)

Turning our attention to sport & the environments being created, we are seeing this engineering approach permeating the “elite” world of adult high performance as well as (more worryingly) talent development, youth and child participation. Rather than the descriptors associated with the positive experiences mentioned by Paul and thoughts from John Kiely (“safe to fail”, “mentoring”, “ownership”, “trust”, “exploration”, “solving problems”), it is becoming more common to observe environments and behaviour reflective of “measurement”, “control”, “fear”, “accountability”, “production lines”, “asset management”, “reporting”, and “benchmarking”.

As a result, we believe the learning, growth and potential of people in sport is being stifled. Drawing from complexity principles, we believe individuals, teams, clubs and sporting organisations can take a different path and emerge far better for it.

These beliefs link to our purpose — to help people be their best.