Data driven insights are challenging our assumptions in sport
Sport. It's quintessentially Australian, close to our hearts. It's a labour of love, a community, a family. It's an emotional rollercoaster of joy and heartache; a gut-feeling, intuition-driven phenomenon.
Or is it?
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Scenario 1. You're the head of a national sporting organisation. You want to know how many new members joined your sport within the last 12 months, for a submission to the government, which, if successful, will secure much-needed funding for the coming year. You consult your staff, your Board, but no one is absolutely sure of what to tell you. So you pluck a number out of the air, based on a gut feeling and anecdotal information. And you're not entirely happy about it, but it's the best you can do.
Scenario 2. You're the participation manager of a state sport. You're looking to find out how many clubs you have across the state, and how well they are fulfilling their governance obligations. The ultimate aim is to reward clubs who are doing well, and incentivise those who are on their way. You do have a rough count as a result of a landmark statewide survey conducted 10 years ago (when the thought of working in sport wouldn't have even crossed your mind!). But that was 10 years ago, and this is now. Have you lost or gained clubs? And how would you even begin to gauge their governance health?
Scenario 3. You work at a council covering a large regional area. With physical inactivity and sedentary lifestyle habits on the rise, you set out to uncover the number one driver of what causes participants to leave sport. Your goal is to combat these factors, to keep more people physically active, and to reward clubs and facilities who put measures in place to achieve this. Your idea is to ask the clubs in your region to provide membership churn and exit survey data. Ideally. The reality is that only the largest, well-developed clubs will even have a chance of collecting and analysing this information. As for the rest—it's anyone's guess.
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Threaded through the above scenarios are some key challenges faced by sport when it comes to data driving insights and decisions.
- Sports—especially at the grassroots level—often don't have the technology, resources, or knowhow to obtain and extract data.
- For the sports that do have the technology, there is a level of mistrust, due to perceived unreliability of technology, driving them to run their own separate analyses to 'fact-check' the tech—a doubling of their workload.
- For the sports that can rely on their technology, there is a 'brain drain' around what the data actually means. It's one thing to rattle off the numbers—but it's entirely another to interpret them with analytical rigour, and present them in a way that can drive meaningful change.
- Because of the difficulties—perceived or actual—around sourcing, applying, and interpreting data obtained through technology, the only other option is to fall back on 'data' drawn from intuition and gut feel.
Through working with sports, ranging from small grassroots clubs to elite-level and national organisations, we've come to understand how crucial it is to develop key strategies to:
a) obtain the data,
b) understand what it means,
c) determine whether the findings challenge or confirm your assumptions, and
d) use these insights to drive meaningful decision making and future-proofing.
It all sounds a bit lofty—but it is actually achievable. And you don't have to be a jumbo or elite sport to reap the benefits. Many of the organisations we've worked with have successfully applied the above strategies to achieve positive data-driven outcomes.
Take Sport A, a state sporting organisation in Victoria. When we first struck up conversations with this organisation, they hazarded a guess that they had roughly 3,000 members, based on clubs emailing them spreadsheets once a year. They also reported huge issues with formal membership uptake (clubs were avoiding registering new members—and some were even artificially removing still-active members—for fear of moving to a higher 'band' of club affiliation fees). However, after moving to a new membership platform and mandating new statewide business rules, Sport A was able to properly ascertain their membership numbers—more than double at almost 7,000 participants—and completely overhaul their affiliation framework to encourage rather than penalise club growth.
What about Sport B, another state-level sport, who were looking to understand their churn rates of their ~30,000 members? (Churn is the number of non-returning members, divided by the sum of new members plus returning members). Having moved to a new membership database roughly 2 years prior to this project, they had sufficient data to drive this analysis. Before commencing the project, we asked around their office, and each staff member provided a guess as to where their churn rate might sit (the prize for the right guess being a delicious bar of chocolate). The CEO came in with a guess of 7%, indicating low movement of incoming and outgoing members, and a large base of returning members year on year. 'Shock' was an understatement when the project concluded and the churn rate determined at 35% (a rate that is actually quite standard across most sports). Needless to say, no one succeeded in winning that chocolate bar.
After the disbelief subsided, Sport B went to work seeking answers as to why member movement in and out was so high, and, based on these results, were able to extract distinct insights and develop action items to help attract more new members, and keep existing members engaged. One key insight they uncovered is when they asked the specific question to non-returning members: 'why did you leave?' The surprising top answer was 'pregnancy'. Members were leaving the sport in high numbers—not because they didn't enjoy it or had other competing commitments or had moved onto a different activity, but because they were starting families. The future-proofing light bulb lit up—perhaps Sport B can now encourage their clubs and associations to lobby the opening of creche/daycare facilities in high-traffic venues, or incentivise venues already offering these services.
And finally, we have Sport C, an elite national sport who recently migrated to a new technology platform, and were looking to understand the size of their sport nationally. Prior to the migration, we did our due research to assist in answering this question—a key aspect of which was figuring out how many clubs existed across Australia. Easy? We asked around. 'I think it's around 150', said one staff member. We went online to their website, which quoted 'over 300 clubs across Australia'. We read through their most recent annual report, which pegged the number of clubs at 127. Not so easy.
But the sport persevered, mandating that all clubs must 'register' via an online form as part of their new affiliation process. After a 6 month registration period, the final number came through—108. And yet, you may argue, what difference does it make whether it's 108 or 127 or 150? It's not so much the exact number that matters (although one would argue that you cannot get any better than exact numbers!)—but that Sport C now has a solid, reliable foundation upon which to further develop and analyse their club and membership data.
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Gut feeling and intuition certainly have a place in sport—ultimately, we are human, and the emotionality of sport cannot be denied; it is, in fact, what keeps us engaged and wanting more. However, it's clear that progress cannot be had without an analytical understanding and appreciation of the data underpinning our insatiable thirst for 'what's next'.
Unsubstantiated growth is not growth, and growth is not sustainable without a solidly built foundation of reliable number-crunching to inform decisions, enhance your sport's structural integrity, and ultimately unveil a future-proof architectural masterpiece.