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In 2014, sports analytics was a $125 million market. By 2021, its value is expected to balloon to $4.7 billion. But this market wasn’t always so lucrative or widely accepted. Back in 2002, the Oakland Athletics General Manager Billy Beane earned a trip to the Major League Baseball playoffs despite having a payroll of just over $40 million — $80 million less than major market teams like the New York Yankees. The key to the A’s success? Not just their scouts’ intuition, but sabermetric principles and rigorous – though at the time, overlooked – statistical analysis. “Moneyball” changed the way front offices across the sports world conducted business. From baseball to hockey and football to basketball, general managers are increasingly relying on analytics to make smarter decisions when scouting, drafting and trading players. They are now using data to build the very best possible teams. But a team’s success depends on more than compiling a roster of skilled players, it requires putting the best combination of talent into the game – and that means keeping players healthy. In an industry fixated on numbers, biometric measurements and workload metrics can offer just as much insight as the box score. At least that’s what companies like Kitman Labs and founder Stephen Smith believe. Building on his experience as a strength & conditioning coach for Leinster Rugby and a thesis on injury risk, Stephen created Kitman Labs’ Profiler tool in 2012 to highlight, manage and reduce the risk of injury in professional athletes. He believes analytics can be used to not only draft the best players, but maximize that investment by keeping them healthy. At Experian, we’re fascinated by the idea of using data to manage risks and maximize investments – in sports, but more importantly, in business. As a company, we are intimately familiar with the many ways Big Data is being used to solve strategic marketing and risk-management problems through an advanced data analysis process, research and development. Thereby, helping us utilize data as a force for good. In fact, every day, we are compiling, analyzing and transforming massive amounts of information into actionable insights. Whether those insights can help consumers secure an affordable loan, understand their credit score, or protect their identity; or for a business to manage risk, help prevent fraudulent transactions, and to ensure they are marketing their products and services to the right consumers at the right time and across the right channels. So we took a moment to sit down with Stephen and Kitman Labs to hear more about their work, compare the worlds of sports and business, share insights and examine what the future might have in store for both industries. Here are the highlights and takeaways from our conversation: What’s your mission at Kitman Labs? Our mission, quite simply, is to create competitive advantages through technology and analytics. We sell to professional and college sports organizations. Our clients are some of the most elite in sports. Our goal is to use our sports science backgrounds to help them win. As you may know, the movement to use analytics in sports has been enormous over the past 15 years, especially with data related things like Moneyball and statistical analysis. Our work is in this tradition, but a lot more components go into it. Risk management is a key focus for us at Experian, would this be an example of such a component? Yes. Risk management is exactly what we do in the world of sports. Our platform is designed to identify injury risks and help players stay on the field. Because anyone who follows sports will tell you injuries are an enormous problem. Every single year, teams lose player performances and huge amounts of money because of injuries. If there was a company out there that could help solve this issue, in a quantifiable way – that would be huge. We believe that’s what we’re building here. So how does it work? There are a number of different components. We have a screening tool that we use to run diagnostic tests on athletes as frequently as possible. That goes into our database system, called Profiler. We’ve taken our years of sports science and engineering experience to develop a system that pulls together all data points tracked by a team to objectively inform us of all stressors placed on athletes and how they are responding to these stressors. Using this information we can identify when certain players are at a higher risk of injury. As far as we’re concerned, this is the next frontier in sports analytics – this is the vanguard of sports technology helping teams to win. Is there one sport in particular that you’ve seen this take off in? As far as the United States goes, we are talking to teams in every sport, and have worked with such a wide variety of data and analyze it all uniquely. Our system can analyze enormous datasets in real time and process this information to find the slightest important variation outside the realm of normality, that coaches just do not have time to find themselves. But this isn’t a problem confined to sports. We’re solving a human problem. We’re in the business of human optimization and we are committed to delving into the minute details to help revolutionize the way this industry looks at these issues. At Experian we’re seeing first-hand the many ways data and insights can solve real life challenges for businesses and people alike. How are you seeing the data that you’re collecting transform your industry, with relation to sports science and sports medicine? Essentially, we’re turning that data into actionable insights that can be used every day. We’re giving the practitioners that work with these teams, the ability to make better, more informed, data-driven decisions to help improve the welfare of their teams, and ultimately, their performance. So what we’re doing in sports right now is no different than the majority of Big Data companies like Experian * * * We, of course, wholeheartedly agreed with Stephen’s final point. The cutting-edge work being done at Kitman Labs is exactly in line with what we’re doing at Experian. Today, we are turning data into actionable insights to help consumers, financial institutions, healthcare organizations, automotive companies, retailers and governmental organizations make more informed and effective decisions. For example, our DataLabs team provides a safe and secure environment to partner with our clients to enable breakthrough data experimentation and innovation. In our labs, we're able to combine Experian's data assets with those of our clients to present a larger picture and to experiment with new and innovative ways of analyzing that data to deliver greater competitive advantages. Just like Kitman Labs is using analytics to help sports teams make better decisions to manage risks around training, improve player and team performance and extend careers, Experian is using Big Data for good to help individual consumers and businesses make informed decisions, grow the economy and improve society.

Our world today runs on data. It's changing the way we browse the Internet, run our businesses, treat medical patients and invest in technology. It's the key to solving society's biggest problems: famine, disease, poverty and ineffective education. And it is powering the global economy. But the data-driven economy is at a crossroads. With the eruption of information, we also open ourselves up to new risks and privacy concerns. As companies adopt more interconnected products and systems, the "Internet of Things" could usher in the next wave of challenges that range from data breaches to other potential privacy concerns if information is used improperly. As a society, we must decide whether to champion the explosion of connected information or allow its detractors to significantly constrain the innovation and growth ahead. Since 2007, data-related products and services have generated about 30% of real personal consumption growth, second only to healthcare goods and services, according to a 2014 report from the Progressive Policy Institute. The mobile app industry alone accounted for more than 750,000 jobs in 2013-jobs that didn't exist a decade ago. Meanwhile, the explosion of the Internet of Things promises to mine our households' daily or minute-by-minute behaviors to save money and improve lifestyles. Soon it is very likely that our personal genomic information will be used to clinically treat our current ailments and prevent the next ones. And of course, the financial industry is using big data to help consumers secure more affordable loans, improve their credit scores, protect their identities, ward off fraudulent transactions and ensure that they are marketing products and services to the right customers at the right time and across the right channels. Companies need to be able to sift through large amounts of data, find patterns and distill the key takeaways in order to make better decisions, improve our society and in turn, drive our economy forward. But with all the headline news surrounding fraud and data privacy, consumer confidence may be shaken. Over the last year and half, cyberattacks on corporations have become more common. Many consumers have fallen victim to the loss of personal identifiable information in many forms. These events have had a tremendous impact on the way consumers and companies think about data and the future of data. These are very real concerns, and they should be at the center of every discussion we have about the future of the data-driven economy. However, as challenging as these times may be, we cannot let these events dissuade us from realizing the full potential of data to help us do really good things for society as whole. Fortunately, today's corporate leaders have an opportunity to proactively head off consumers' uncertainty and fears about big data and keep the data economy open and healthy. But doing so will require businesses to operate differently than they have in the past. Companies need to operate on bedrock information values-values that dictate and ensure mandatory training for all employees, strict compliance rules and regulations, dedicated compliance officers and data governance experts and ongoing improvements to keep security and ethics at a company's core. These philosophies should be so central to a company that they find their way into key business processes, and touch every single employee and every aspect of operations. It's up to the business sector to earn the trust of consumers and lawmakers and create the legislative and regulatory conditions that allow the data-driven economy to thrive. And it's up to the people and companies that work with big data every day to advance how data can be used for good. In the late fifth century, the emerging medical profession reached a point where it needed unifying principles to guide the actions of physicians across many countries and many time periods. Now data-driven industries also need a way to ensure they advance data for societal good even at expense of profit optimization. We can do this by establishing common goals that give data professionals core values to adhere to, irrespective of their location and their individual companies' own culture and standards. The data economy has both incredible opportunity for growth and a real danger of stagnation. Only by committing to the responsible use of data can we transform our economy and the ways we operate within it. Originally Published: American Banker

Today’s data-driven world creates exciting new opportunities, but also new challenges. Many of us see the promise of being able to make more intelligent decisions by fully understanding our customers and the needs of the marketplace. There are data scientists that can do incredible analysis to give us new insights into areas we didn’t think were possible. We have more data than ever before and it is only increasing in volume. According to a recent Experian Data Quality study of CIOs, more than half believe the volume of data their organizations need to manage will increase in the next 12-18 months. Data volumes are expected to increase by an average of 33 percent. All this is changing the way that we operate and how we do business. However, most of us are not fully exploiting the data assets we have available to us today. A large problem with data management strategies today is that most organizations are not managing the data process centrally. Sixty-eight percent of the CIOs we surveyed think it is difficult to find stakeholders who take anything other than a siloed view of data management. In addition, 70 percent of CIOs believe it is difficult to make decisions because no one in their organization is taking full ownership of the data. For many organizations, the responsibility of data is falling to individual departments or the CIO. In the last 12 months, more than half of the CIOs we talked to have become increasingly responsible for data management, and an equal amount have felt increased pressure to provide data to the business faster. While the data management roles certainly need to become more centralized, the challenge is that the CIO is already stretched thin. Data management cannot be just another responsibility added on to their workload if at all possible. To combat this issue, a solution some companies are starting to explore is the hiring of a chief data officer (CDO). The CDO is becoming more common in highly regulated industries and is serving as the individual in charge of the data and information strategy, governance, control, policy development and effective exploitation. The CDO role is as much about advocacy as anything else. Part of the problem with many data governance or data strategies today is that they change the status quo for employees. Process changes are forced into place without the employee understanding why this is better for them. Consequently, employees find workarounds to get back to the way they were doing things. It’s important to note that the CDO is not a data ‘cop.’ They are an evangelist for data in the business, pointing out its benefits and how it provides insight. They are a guardian for data quality, making sure information is trusted. In addition, the CDO is responsible for managing large data management programs involving multiple stakeholders around the business, creating consistency. This role will only get more common in the years ahead. Gartner predicts that 50 percent of all companies in regulated industries will have a CDO by 2017. I think that is certainly true, and could even accelerate if data continues to evolve at its current pace. Data needs an owner and someone to take responsibility for its management and usage. A CDO is a great role to consider when evaluating the people needed to maintain an aggressive data strategy. To learn more about this top, be sure to read our new report The Chief Data Officer: Bridging the gap between data and decision-making.