17 November 2017
Dimension Data unveils mobile application to track health and wellness of Africa’s pro cycling team
Cape Town / London – 17 November 2017 - Dimension Data, the global USD 8 billion ICT solutions and services provider, today unveiled its health and wellness mobile app at the annual training camp of Africa’s professional cycling team, Team Dimension Data for Qhubeka. Called Phila (pee-lah), which means ‘to live’ in Nguni, the app was custom designed to Team Dimension Data’s specific requirements.
The app tracks the daily physical and mental performance of the team’s 39 World Tour and Continental riders located in 10 countries. Data collected from the team includes geographical location and time zones, quality and quantity of sleep, response to training, muscle soreness, as well as mood, motivation, and stress levels.
Developed by Dimension Data’s Digital Practice in partnership with Team Dimension Data’s riders, and Australia-based MIK Health, Phila is also a communication and data-sharing management tool for the team.
Every day, Phila prompts the riders to complete an assessment via their mobile device. The information is correlated with existing training data captured by the team’s TrainingPeaks application, and is used to monitor training performance alongside overall health and wellness.
“It was crucial that we designed an app which was easy to use 365 days a year, and riders could upload their assessment responses in two to three minutes,” explains Dr Carol Austin, Head of Performance Sport and Medical for Team Dimension Data. “Our goal was to keep the questions to a minimum, but extract the maximum data to identify any factors that could jeopardise our rider’s ability to train – even weather conditions and equipment issues.”
In addition to the riders being geographically distributed, they’re often in different cycles of racing, training, and resting. It’s difficult for riders, coaches, doctors, and performance staff to stay in constant communication. Phila is a simple way to capture key information and share it with the team’s support staff, who can respond immediately to injuries or illness and adapt rider racing and training schedules.”
Scott Gibson, Dimension Data’s Group Executive – Digital Practice said, “The health application is just one component of the collection mechanism for critical data that we’ll feed into the analytics platform we’re building for Team Dimension Data. This data will be enhanced with additional datasets, and the implementation of a machine learning solution together with predictive analytics to improve team planning and management performance.”
Dimension Data is the title sponsor of Team Dimension Data for Qhubeka. However, says Gibson, the sponsorship is not just about financial investment in the team. “In the same way that we believe the technologies of the new digital age will help our clients achieve their business outcomes, we aim to develop digital technologies that will assist Team Dimension Data to achieve their 2020 vision of winning the Tour de France.
More about the health and wellness data collected from Team Dimension Data’s riders
Location of each rider: Which country and continent the riders are in when racing or training.
Travel: The teams’ performance management need to understand the impact that travel has on the health and performance of riders, for example the impact that travel across time zones may have on the riders.
Sleep: Data such as whether the rider sleep at home, in a hotel, or on an aircraft is collected; and where he slept the previous night; what time the rider fell asleep and woke up, how longer the rider slept; the quality of sleep; and the altitude at which the rider slept and woke up, which is very important on a science level.
General wellbeing: Using scientifically validated scales that are simple to answer, riders are asked to rate their mood levels each day, their motivation and current stress levels, if they’re feeling fatigued, or have muscle soreness.
Training: Riders are asked to provide a subjective view on their performance in training - or racing the previous day: did they perform as expected? What’s really important about this data is how the rider feels about his training: what his rating was on perceived exertion? Is the rider responding well to the training that the coach prescribed? Did the effort feel like a 7/10, a 5/10, or a 9/10?