Since she was six years old, Emily McInerny has dreamed of representing Australia in the national women’s basketball team, the Opals.
To achieve her goal, she knew she needed the X factor to give her the edge to secure a coveted berth in the national team.
Emily found her X factor by analysing her personal data, looking at her every action, assessing it and using science to show her how to reach her peak performance.
For Emily, it was the difference that allowed her to achieve her lifelong goal of playing for her country and winning a World Championship with the Opals.
Emily is the first admit her method of data collection was raw and rudimentary but nonetheless it gave her the information needed to be able to assess her behaviours to learn what resulted in success.
Jumping years ahead to a life post-basketball, Emily still believes the ability to be able to look at your personal behaviours can give you the edge to gain success, whether it’s in a sporting arena, personal growth or at work.
It’s this same philosophy that’s behind the basis for SWOOP Analytics, a dashboard that shows the online collaboration behaviours of every person in an organisation, from the individual to the team, business unit, department and overall enterprise.
By seeing the way you work, you can change the way you work, said SWOOP Analytics Chief Scientist Dr Laurence Lock Lee.
“That’s why it’s so important to allow each individual employee to see their online behaviours at work,” he said.
“Just like Emily with her data collection, using your own data to see how you work allows you to change your behaviours to achieve your goals. This is especially important for leaders to see how they can make an impact to keep employees engaged and connected.”
Back to Emily’s story. It was 1984 and Australia’s women’s basketball team was making its debut appearance at an Olympics, in Los Angeles.
Watching from country Victoria, a young and ambitious Emily knew then and there that was what she wanted to do.
“I wanted to play basketball for Australia at the Olympics and I was the ripe old age of six,” Emily said.
It was a huge commitment for a six year old but it became Emily’s goal.
“I had very good fortune through my junior years to be selected in every team that I ever wanted and I had success with those teams, from Bendigo where I grew up with my club team, representative basketball, country Victorian basketball, then National Junior team captain and silver medallist at the World Junior Championships in 1997,” Emily said.
“It was after that point that I had my first stumbling block in my ambition to be an Olympian, where I couldn’t get my foot in the door to be in the Opals.”
Emily was struggling to get a berth in the selection trials for the national team.
“Steve Metcalfe, conditioning coach at the Melbourne Tigers, said; ‘Well, if you want, I can get really scientific with you. If you’re willing to push yourself we can get scientific and make it so the selectors have to notice you and put you in with contention to make the team’,” she said.
Using analytics to find the X factor
The idea was to use Emily’s personal data to ensure she was the supreme athlete, the one selectors could not knock back.
Emily was a defensive specialist which requires both speed and strength, a combination not easy to master at the elite level.
“I wasn’t a classic particular-position player,” she said.
“I had a role in a team that was to guard anyone from the point guard to the power forward, I was assigned to shut them down. So it required that I’d be really fast and fit but also really strong.”
The first thing Steve asked Emily to do was to buy a diary and start each day by recording her resting heart rate, hours of sleep, quality of sleep, training for the day, the intensity of the training, how she felt afterwards and what she ate.
“I had to record quality of nutrition, a rating out of 10, and all these things were my feel, how my general well-being was, how I felt energy-wise and if there was anything else going on in life at the time,” Emily said.
“The two points my coach was concerned with was the resting heart rate and the general well-being rating because, in his mind, they were the two markers that could predict potential over-training.
“I maintained that diary for months and months and months because I was training quite hard and still playing games and any time I felt at practice or in a game, when I felt great, on top of the world, or I had a really fantastic performance and I felt that was a great day, I had to put a marker on that page to say; ‘Hey, I felt great that day’.”
It was about eight months later when Steve asked Emily to go back to the diary and look for those markers.
“He asked me to try and see what was happening in the lead up to those games or those training sessions,” Emily said.
“As primitive as the data collection was, and as basic as my analytics were, I noticed that every time I felt really great, the intensity or the duration was either a short, sharp, hard session or a regular length session that was really light on in intensity for two days in the lead up.
“That tapering into a game made me feel fantastic and made my performance better.
“The outtake of that was, even though it’s not an exact science, it gave me the confidence to know that if I had a big game or something that I needed to perform coming up, I would prepare that way and I actually used that methodology of preparing for big games my entire career.”
Not long after that eight-month period, when she realised what helped her perform at her best, Emily was selected in the Opals squad in the lead up to the Sydney 2000 Olympics.
“Keeping this diary, analysing this data, it achieved the objective to get me into the squad,” she said.
Emily went on to win gold for Australia at the 2006 World Championship in Brazil and the 2006 Commonwealth Games in Melbourne. Sadly, she missed selection for the Olympics and retired from WNBL competition in 2009.
The importance of seeing your own behaviours
One of the differentiators about Emily’s data collection method, she said, was the fact it was her own personal data. It wasn’t collated and averaged data from other elite athletes but her own behaviours and reactions.
It’s the same way SWOOP Analytics views the importance of every individual looking at their personal data to see their own behaviours and how they work. SWOOP has classified behaviours into five different personas, with nudges on how to achieve better performance.
“I felt, because it was my data, I put in the input that I believed it was best for me so of course it changed my behaviour,” Emily said of her data diary.
“For the rest of my career, I knew that if I was going to feel ready to go on a big game day…I would use that taper approach in the lead up to it.”
Emily, now the People & Culture Project Lead at Cbus Super Fund, is no expert on how capturing personal data applies to individuals in the business world but believes it could be just as important as for an elite athlete.
“Had I not taken all those additional data points, I would not be able to extract those insights, so my thinking is that sometimes we don’t know what the data is going to be used for in terms of performance, or just knowledge about yourself or your workforce, but if it’s in there, one day there might be something that shows up and it could make a difference,” she said.
Along with data for each individual, SWOOP shows the behaviours and collaboration of teams – something just as important as individual data when it comes to a sport like basketball.
Emily explains the importance of collaboration and diversity of experience for a team to work successfully, measures all available on SWOOP.
“For collaboration, we needed to have diversity of skill sets and experience because in a team of basketball, there are five people on a court and potentially seven sitting on the bench, so not everyone can play all the same amount of minutes and often the more experienced players at that elite level would start the game, take the heat out of the game and then other players would come on to pack some punch,” she said.
“It’s about having a range of skills but also a range of experience that enables the best collaboration because not everyone is the leader.
“You’ve got more people willing to listen to someone who has been there and done it before and you’ve got natural leaders who have experienced different scenarios, different cultures, different playsets – all those types of things that are there to help guide those who haven’t done it before.”
In a work sense, without the ability to measure the different “playsets” of each employee, it’s difficult to reach the elite level, said Dr Lock Lee.
How to collaborate at an elite level
Collaboration is about how you interact with other people and SWOOP has made it easy to measure your personal collaborative performance in your online work networks on Microsoft Teams, Yammer and Workplace from Facebook.
By checking just three measures from your online activities at work at least once a week, or ideally daily, you can see how well you are collaborating and how people reciprocate.
- Get the balance right between posting, replying and liking. Aim for this ratio: 1 post, 2 replies, 3 likes.
- Ask question: Aim for 17% of your messages to include questions. This invites people to engage with you.
- @ mention people. @mentioning people is a powerful way to draw them into a conversation.
If you do the above well, you’ll see people respond to you by replying and liking. We know messages with questions typically get 150% more replies and @ mentioning people increases the response rate of a post by, on average, 73 per cent.
If you want to reach the elite levels of your game, you’ll need to apply some of the same dedication as an elite athlete. Look at your metrics. Reflect on what and how you are contributing, and how people respond. Learn and adjust.
Main photo courtesy of The Bendigo Advertiser.