Data & Innovation, Performance | Jun 9, 2020
10 tips that help your organisation to develop a mature culture of data-informed decision-making.

Sophisticated cultures of data exploration continue to develop across global sport. 

By John Portch

While it is true that team budgets can dictate the size and scale of your data and analytics initiatives, it is within the power of all organisations to develop mindsets around using data that make the most of what you do collect. 

Get the culture right and you can begin to make the most of the datasets you have at hand. Here are 10 tips from our panel who, despite their divergent needs and resources, have worked to develop cultures of data exploration at their organisations. 

1. Remember: datasets are not just numbers 

Numbers are just a part of any well-intentioned data analysis programme. “The first thing we need to keep in mind is that data also includes text and notes,” says Xavi Schelling of the San Antonio Spurs. “Data can be a note from a physio that says ‘check on hip extension restriction’. It’s not a number, it’s a very relevant subjective assessment by the physio that is put in the athlete management system that can be quickly shared by the department; in order to be able to act upon that. We talk with players, coaches, strength coaches, physios and doctors on a daily basis about data and information, but what is important here is to find the best channels and formats to communicate with each one of them. We have more technology collecting information, but the key is to put order and make sense of all that information.” 

2. A data strategy needs front office support 

Schelling explains that he has seen the use of data proliferate during his six seasons working in the NBA and attributes this trend to evolving attitudes in front offices. “Front offices, GMs and CEOs detected a discrepancy between international pro sports and the US,” he says. “It will take some time to reach the same levels as Australia, for example, when it comes to data-driven decision-making in sports. I don’t know if it’s going to be in two years or six years, but we will get there for sure because the resources are there and the goals for leadership and front offices are also there. Whoever best implements the programme, including the educational part, understanding the context, and being patient, is the one that will reach that operational level sooner than the others.” 

3. Data is the connector between departments 

Andrew Gray of Wests Tigers, says that data link each department in the club’s rugby operations. “It’s a connector and communication platform within our football programme between practice, recruitment, medical, strength & conditioning, rehabilitation,” he explains. Data can provide both clarity and drive for athletes. “That’s the role that it provides, a very central role; for our coaching department who are very invested in our data as well along with our recruitment and retention division too.” Gray is describing a culture of data exploration in action. “That is the beauty,” adds Schelling. “If you have that level of maturity in the system then staff realise that what is happening next door is going to have an impact in this room and, in the future, the other room. That interconnection is the key.” 

4. Take an incremental approach – don’t rush 

As stated above, Schelling has been in the NBA for six years. The scenarios he is describing did not develop overnight. “When using data, you want the coach to understand and be able to optimise the training,” he says, “and you want the player to engage with the technology and to recognise and realise that that data is not just for the sake of collecting data, it is to optimise your session and your training. All those moving parts are the key to that process and, in those six years, we have been adding little by little, piece by piece. Don’t try to rush it.” 

 5. Be proactive… or reactive 

Your data collection must meet specific needs within your organisation and, as Schelling argues, your approach can be either proactive or reactive. “If you’re an expert in the field and you know the organisation, you can be proactive. ‘OK, I know this is a common recurring question for me and I’m going to build something to answer that.’ Now, if you are not an expert in the sport or you don’t know the organisation very well, then you have to invest a lot of time with coaches, physios, and front offices, and probably players, to understand what is the most urgent need or how you can help optimising the efficiency of a decision-making process. You learn what the need is and then you help to make a decision on that need, reactively.” Whichever first step you need to take, proactive or reactive, your next step needs to be perseverance. “It is not just delivering a report – you have to spend then time reminding the user how to interpret and interact with the report, and what can be optimised.” 

6. Ensure that you are informing your athletes’ intuition 

With an understanding of athlete needs, datasets can be used to test hypotheses or belief systems. “That will be the starting point,” says Machar Reid of Tennis Australia. “With a tennis player, it might be as simple as ‘am I as effective when I serve wide on the court? When I open the court by hitting wide to the deuce, am I really more effective than I might be otherwise?’ And that might be a belief that a coach or an athlete themselves might hold. You can look at data that way, with a view to confirming that hypothesis. Once they get comfortable with that or once they feel they’ve used data in a way to make them feel more comfortable, they’ll say ‘OK, over to the data professionals now to tell me what I don’t know’.” Danny Holdcroft of British Skeleton hold similar views. “Skeleton is not a sport that’s grown off data and facts,” he says. “It’s grown off opinions and what a coach feels is the right way forward. Over the years, as we’ve put more sports science around our programme, data has become more important. The last bit of the jigsaw is putting data around the on-ice coaching aspect, because it’s quite difficult and challenging. It’s trying to bring data to the fore at the same time as educating the coaching team around what data can give because coaching in our sport sits in a very old-school traditional sense of seeing, instructing and doing.” 

7. Be mindful of the vocabulary you use around data 

Datasets inevitably bring new words and ideas to the table and you need to be able to explain yourself if data can be used to optimise performance outcomes. Schelling says: “When you are introducing new systems or new knowledge into an organisation, you have to invest time to make sure that whoever is at the table understands the basics, with specific definitions of words or interpretations.” Sometimes that knowledge is already held within an organisation, but the terminology may be different. Schelling suggests using that to your advantage. “I would not spend time giving them a new and fancier word if you have that vocabulary already in your organisation. Unless it is wrong, keep it there and use it. Then invest time educating them in other things because there is so much that you have to educate and be selective about where you want to spend time on.” He has noticed the evolution at the Spurs. “It’s very interesting to see how the vocabulary evolves with coaches, athletes and the front office. For example, they understand what a ‘percentile’ is or what a ‘cluster’ is or different metrics; accelerations, decelerations; what an asymmetry is or what an imbalance is. It’s cool to see how conversations evolve. Again, don’t try to rush it. Grow with your department, organisation and players.” 

8. Believe it or not, some athletes will enjoy a spreadsheet 

Perceived wisdom is that athletes will switch off if you present them with dry numbers and some almost certainly will, but, as cultures of data exploration develop, you will find yourself helping athletes who wish to take a deeper dive too. “I’ve found that colour-based systems are great but we’ve also found that there will be some players that love an Excel spreadsheet,” reveals Gray. “They follow it and really ask some good questions around it. Whereas there’s others that colours will work better for; there’s others that the graph format will make a lot more sense. Our challenge is to have that as visually digestible as possible for everybody but also retain enough data for the different learning preferences. He adds: “There are more and more players now who are comfortable with numbers and sophisticated dashboards. They’re looking for more. That’s just generational exposure too. I guess we’re trying to make things look more like the screens they look at more often these days.” 

9. How to build trust with athletes and coaches 

How can you build trust with athletes and coaches when it comes to data? “I think it’s very personal how you want to achieve that,” replies Schelling. “I always say the key here is having empathy; that is step No1. You need to understand who you are interacting with, you need to understand that whatever you are building and whatever data you are collecting, it’s to help them perform better, to help them have a better programme.” Key to that is the clarity of your purpose. “This is relevant for coaches, physios or strength coaches, they don’t need to understand the data collection as an assessment to the programme; it is part of it, but it’s not the end goal. The end goal of data collection and data usage is to optimise the process; if we optimise the process you will be a better professional. This is not to assess how well you are programming, it is to help to you programme better.” 

10. Work with startups or industry partners 

Not all organisations will have the finance to explore data collection independently but teaming up with startups could prove fruitful. “That’s something we’ve tried to use to our advantage, getting involved with startups and those  companies that might be looking to giving us some tech to understand how it can be used in teams,” admits Gray. “When you’ve got really good staff and really good systems and you’ve got the ability to bring something in like that and actually assess it, and give back to that  company; ‘this is what makes sense to teams and this is what makes sense to us’ then I think you  can turn a poor financial situation into a little bit of a win-win for the provider and the team.” 

This chapter was taken from the latest Leaders Performance Institute Special Report, Analyse This: Managing Your Metrics

It features a variety of sports organisations, from the San Antonio Spurs and England Netball, to the Wests Tigers and Tennis Australia, via British Skeleton. Download it now.

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