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Federal and local governments around the world are expected to spend $475.5 billion on technology products and services by 2019. From New York to Chicago to Rio de Janeiro, metropolitan centers around the world are looking for new ways to be “smart” – to become more sustainable, improve the efficiency of public services and citizens’ quality of life. Forward-thinking civic and business leaders are experimenting with massive amounts of data – and the tools and technologies to compile and examine it – in order to improve how efficiently and effectively cities are managed. But the explosion of data is not without obstacles. According to the research firm, Gartner, it may take a full decade or more before the maximum utility of government open data is realized. So-called, “smart cities” require more than data alone – they require technologies to collect and analyze huge amounts of information and they require cross-sector solutions that can be scaled to size. “Smart cities” require leaders to use Big Data for good – to make better decisions, drive smart growth and benefit society as a whole. The true smart cities will use Big Data to enable the preemption and prediction of urban issues, improving efficiency and quality of city services from healthcare to traffic management. If used properly, and in conjunction with tools that deliver actionable insights, smart cities will transform the lives of urban residents. The timing of this transformation couldn’t be better. The number of people living in cities worldwide is expected to increase to 6.3 billion by 2050 – up from 3.6 billion in 2010. To meet the demands of growing urban populations, more and more cities are taking up data-smart initiatives. In fact, at the state and local levels of government, alone, spending on information goods and services is projected to grow at a 3.3 percent rate between now and 2019, increasing to $70 billion. The initiatives vary in scope and focus, but the drive is the same – improve efficiency, save costs and generally improve the urban experience. In New Orleans, for example, leaders are responding to ongoing fiscal challenges with NOLAlytics – a unit spanning multiple departments focused on using data to improve the city’s services. The unit’s first project aims to reduce fire causalities and save costs. The Targeted Smoke Alarm Outreach program – a door-to-door smoke alarm campaign leverages data from the Fire department, Census and American Community Survey and the New Orleans Fire Department to prioritize outreach in neighborhoods that are least likely to have smoke alarms. Meanwhile in Singapore, leaders are building a network of sensors to collect and analyze data at bus stops, public parks, traffic intersections and other areas to improve public services with the goal of making them not only more responsive, but anticipatory of needs. And the General Service Administration has figured out a way to save $13 million annually in energy costs by using a proprietary data algorithm to monitor 180 buildings for malfunctioning exhaust fans. At Experian, we are also embracing the potential of Big Data to improve society and support smart cities. We are using data assets to glean insights and help consumers, financial institutions, healthcare organizations, automotive companies, retailers and governmental organizations make more informed and effective decisions. For example, with rising insurance costs, deductibles and copays, some people struggle to afford the out-of-pocket expense that can come with seeking medical treatment. Because of this, some consumers decide not to seek treatment, which could have negative effects on their health and overall well-being. Experian works with hospitals, medical offices and clinics to provide unique data and analytics to provide insight into each patient’s financial situation. By leveraging healthcare-specific predictive models, Experian enables healthcare organizations to easily and efficiently determine which patients qualify for financial assistance programs or help them set up a payment plan that fits within their current budget. And in Orange County, California, for instance, Experian worked with local officials to verify the county’s list of 260,000 inactive voters – those who had not cast a ballot in the last four years – against our extensive database of known addresses. Once Orange County had the proper addresses they were able to send out post cards for residents to either update their contact information or confirm that they had moved out of the county. The process saved the county $80,000 in the next election. And in our DataLabs, teams of data scientists with experience in machine learning and analytics are using data for good in bold new ways, developing data-driven solutions and pinpointing previously undetected strategies. By leveraging technologies, such as Hadoop, Spark, Hive and advanced machine learning techniques, we are able to crunch through massive amount of information and discover new insights to help local businesses and governments understand their customer and constitution base to provide better services. For example, the DataLabs is working with social media and de-identified data to better understand and predict consumer activity. By analyzing this data, our DataLabs can identify the generalized daily travel patterns of consumers, which can in turn be used in combination with the government’s open data to improve public services, from transportation planning to land use and public safety in large crowds. With the abundance of data, we have the potential to improve the efficiency of government and build smarter cities. To achieve such goal, we need to encourage data sharing, standardization of data, and the application of the data science to use Big Data for good and truly transform urban life. Originally Published: The Hill

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