When David Tenney, High Performance Director for the Orlando Magic, is asked who manages performance the best, his answer isn’t within sport, but rather the construction and airline industries. And it all comes down to how systems and problems are categorised and dealt with.
According to Glauberman & Zimmerman (2002), systems and problems can be broken up into three classifications:
- Simple - e.g. recipe
- Complicated - e.g. man on the moon
- Complex - e.g. raising children
The below table identifies how to manage complicated and complex systems, showing that complicated systems rely on formulae, have assurances for future instances, require high levels of expertise, each initiative is similar in critical ways, and there is a high degree of certainty with the outcome.
Meanwhile, complex adaptive systems have limited application, limited assurance between instances, not reliant on expertise, influenced by relationships, and there is uncertainty with the outcome.
Table 1
|
Complicated systems |
Complex adaptive systems |
|
Formulae are critical and necessary |
Formulae have limited application |
|
Sending one rocket increases assurance that the next will be ok |
Raising one child provides experience but no assurance of success with the next |
|
High levels of expertise in a variety of fields are necessary for success |
Expertise can contribute but is neither necessary nor sufficient to assure success |
|
Rockets are similar in critical ways |
Every child is unique and must be understood as an individual - relationships are important |
|
There is a high degree of certainty of outcome |
Uncertainty of outcome remains |
The below table looks at different leadership tasks for the different systems, showing that complicated systems rely on role definitions, decision making, tight structuring, knowledge, and staying the course; complex adaptive systems rely on relationships, sense making, loose coupling, learning, and notice emergent directions.
Table 2
|
Complicated systems |
Complex adaptive systems |
|
Role defining - Setting job and task descriptions |
Relationship building - Working with patterns of interaction |
|
Decision making - Find the ‘best’ choice |
Sense making - Collective interpretation |
|
Tight structuring - Use chain of command and prioritise or limit simple actions |
Loose coupling - Support communities of practice and add more degrees of freedom |
|
Knowing - Decide and tell others what to do |
Learning - Act/learn/play at the same time |
|
Staying the course - Align and maintain focus |
Notice emergent directions - Building on what works |
To best manage the demands of high performance management in sport, David uses the below matrix model, with the goal of providing the organisation the following:
- Displaying trends in performance and injury risk
- Creating cross-communication language and metrics that are agreed upon by all silos
- Creating awareness amongst athletes
- Developing a feedback system (and quantification) for daily practice and end-stage rehabilitation.
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