Never confuse confidence with competence. There are many brilliant people in sport, tech and media. Over several years I have been lucky to work with many fantastic policy makers and executives.

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But there are also some profound problems at the core of how the industry makes decisions. Three years ago, this would have been an eccentric viewpoint. No longer.

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Ideas for dealing with these deep problems are provided by many sources, often junior executives and generally supported by leaders and investors. Of course, there are concerns — some with foundation, most without.

Now there is a confluence of: sport, technology and media, there are opportunities and pitfalls at the frontiers of data science, AI and cognitive technologies.

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6yz wants to improve performance and make executives, like me, much less important than they often think they are. Too many have to make decisions well outside their circle of competence and experience. If this changes, individuals, society and sports communities' benefit and companies are more efficient.

We focus on the intersection of decision-making, technology, high performance teams, strategy and government/federation policy.

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We draw an important distinction between fixers, serial conference attenders, PR bluffers, go-betweens (you know who they are) on the one hand; and people with real models for action – irrespective of age or position.

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Four things to get right , in order of priority:

(i) people,

(ii)ideas,

(iii)technology/tools

(iv) communication.

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I have had direct experience of how the most disruptive and successful technologies and services in the sports tech and media space have been able to identify how the ‘hidden simplicities’ of high performance.  Often these simplicities are 'low tech' or 'no tech' and so are not recognised. The big difference is people and aptitude. Less important is polish, character and network. Most relevant is aptitude. People who are  above average on intelligence, relentless effort and operational ability. We always earmark those with attainment on high impact projects and have learnt these vital lessons, as able to think rationally and provide insight and change in uncertain markets and societies.

 

Another thing. If we look at contemporary strategy planning, it represents extremely compressed information conveyed through a very old-fashioned medium, the written word.

They do not show the behaviour of communities, society and markets in a visual interactive way - so we can see the connections between changing values in the models and changes in behaviour of people, markets and societies. There is no immediate connection. Everything electronic is pretty much the same as a paper and pencil version.

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There is a very powerful feedback between: creating dynamic tools to see complex situations deeper (to see inside, across time, and possibilities), thus making it easier to work with reliable knowledge and the potential for big improvements in the performance of organisation and decision-making.

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Relevant scenarios for the above:

(i) Existentialist threats to sports ecosystem such as video piracy

(ii) Merger and acquisition

(iii) Launching new technology, particularly around AI and data science.

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The most progressive and successful developments within the sports field have been when leaders move rapidly from stories (sales executives in senior management) and authority (politically adept CxO) to evidence (science) and quantitative models (product design)

An inefficient process for creating growth is when executives regularly conflict over stories and authorities, where almost nobody even tries to keep track of the facts/arguments/models they’re supposedly arguing about, or tries to learn from evidence, or tries to infer useful principles from examples of extreme success/failure.

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Consider the problem of how someone can usefully get to grips with a complex strategy area involving technological elements.

Key to my approach is to encourage technologist find their way to sub-problems within other people’s projects where they might have a relevant idea? How can they be exposed to problems common across many projects –

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What are open problems in the field?

Who’s working on which projects?

What are the fringe ideas?

What are the process bottlenecks?

What dominates cost?

What limits adoption?

Why make improvements here?

How would communities or the world benefit?

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None of this information is easily or openly available — companies and individuals boast about successes, not failures or problems.  For each topic, it is necessary to spend weeks tracking down and meeting with industry insiders. What we’d like is a tool allowing one to skim across entire fields, browsing problems and discovering where he/she can be most useful…

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Now suppose a problem is uncovered in say the efficiency of bringing context to convolutional neural networks used in computer vision tech; or inefficiencies in forensic watermarking in dealing with live video piracy and your team comes up with an idea for an improvement. Now what?

 

I would ask:

 

Is the improvement significant?

Is the solution technically feasible?

How much would the solution cost to produce?

How much would it need to cost to be  viable?

Who would use it?

What are their needs?

What metrics are even relevant?

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Again, none of this information is to hand, or even accessible. It would be necessary to spend weeks doing an analysis, tracking down relevant data, getting price quotes, talking to industry insiders.

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What companies,  start-up accelerators, private equity groups, policy makers need to construct  are tools for quickly estimating the answers to these questions, so teams with new ideas and capabilities can  fluidly explore the space of possibilities and identify ideas that have some hope of being important, feasible, and viable.

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Simon Cothliff