The Practice of Health Analytics

The Business Analytics Institute will once again be hosting its Summer School in Data Science for Management in Bayonne, France from July 2 to 11 2018.  In this exclusive five-part series on Why Future Managers Should Invest in Data Science, we will explore the BAI’s unique value proposition around improving managerial decision-making.

Michel Foucault once argued that the only viable yardstick for measuring the value of technology is its contribution to developing human well-being. The near future of Health Analytics may provide substantive proof of this vision. Each day, the human body produces two terabytes of usable data on an individual’s heart rate, sleep patterns, blood glucose, stress levels and brain activity.[i] By 2020, roughly 25,000 petabytes of patient data will be available to the industry.[ii]  As healthcare organizations invest heavily in technology and analytics to take advantage of these opportunities, what are the opportunities for aspiring data scientists?

What is Health Analytics?

Health Analytics involves deriving insights from patterns and correlations in the data that can fuel better decision making in the Health and Life Sciences. KPMG’s recent survey of healthcare professionals reveals that fifty-six percent of the participants surveyed believe that analytics will largely contribute to health care processes, while 35 percent cite lowering healthcare costs, and 32 percent suggest improved health outcomes.[iii]

According to the recent study by Research and Markets, this market is expected to reach USD 24.55 Billion by 2021 from USD 7.39 Billion in 2016, which represents a CAGR of 27.1%.[iv] This exceptional market growth is driven by factors including a multiplication of government initiatives to enhance the adoption of electronic health records, rising pressure to curb healthcare spending, the perceived need to improve patient outcomes, the increase of venture capital investments in the industry, and advancements in analytics and big data technologies.

Can Data Science make a difference?

How will the development of Data Science impact the delivery of health care?  There is a panoply of areas in which a better use of patient and clinical data can make a measurable impact on the industry. Because administrative costs make up about 15% of all healthcare expenditures- providing better patient and physician level data allow clinicians make quicker and more cost-efficient choices. The National Healthcare Anti-Fraud Association estimates the loss to health care fraud in the US alone to be about $80 billion annually, yet current data practices recover less than 5 percent of these losses are recovered.[v] Most importantly, data science can facilitate the transition for “cost care” to “health care” by allowing the industry to identify at-risk patients and encourage them to make lifestyle changes to their future well-being.

In an increasingly competitive healthcare market, eighty-nine percent of industrial executives interviewed by Accenture believe that implementing big data analytics will be the key to maintaining market share.[vi] Partnerships between the medical providers and the pharmaceutical profession, like DataSphere, HealthConnect, and PPC/HealthCore, have provided frameworks for the future of Health Analytics. European and national initiatives, including the Directive 2011/24/EU and the national health card scheme in France are already providing tremendous amounts of data on industry costs, practices across demographics. Local attempts to pool resources in the form of “groupements médicaux territoriaux” have allowed local practitioners to share resources, knowledge, and best practices.

Where are the opportunities for Data Scientists?

The boom of the Quantified Self movement is also fueling the market. Constant streams of Little Data on individuals physical and mental states from a multitude of connected devices capture the quality of our mindfulness, exercise, and diet. The proponents of the Quantified Self claim that this data can potentially improve the quality of our sleep, the way work, and the way we play. Applications of Little Data, like those of Asthmapolis, Quadio, and Zepher are particularly promising both for populations who face specific health challenges (allergies, asthma, heart conditions, etc.), as well as athletes looking for a competitive edge.

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Machines don’t take great decisions, people do

The Business Analytics Institute will once again be hosting its Summer School in Data Science for Management in Bayonne, France from July 2 to 11 2018.  In this exclusive five-part series on Why Future Managers Should Invest in Data Science, we will explore the BAI’s unique value proposition around improving managerial decision-making.  

We live in a time and space in which data is constantly mistaken for facts. Taking better decisions, rather than manipulating the data, is the ultimate benchmark for improving management. We are currently producing roughly 2.5 quintillion bytes of data each day — more data in the last two years than in the previous history of mankind.i To date, there is little evidence that this revolution has led to better decisions than in the past.  Are today’s fake news, faked facts, and manipulated opinions the cause or the result of poor decisions? Most importantly, what can be done to improve your ability to take better business and career decisions?  

“A manager who ignores Data Science is much like a drunken man beside a lamp-post – he grabbles for support rather than illumination”

 What does improving decision-making entail?

Data Science is about transforming data into impactful decisions that address fundamental organizational challenges. In decision science, we learn that the major challenges to decision-making are perceptions of the complexity, ambiguity, and uncertainty of the environment in which we take decisions.ii In the cognitive sciences, we are taught that our pre-conceptions and prejudices both distort how we see the problem, and limit our ability to propose innovative solutions. In management schools, we are trained to recognize that there are distinct types of problems and that each requires unique approaches that can’t be solved in a uniform manner. Finally, in business, we sense that the culprit isn’t just our own decisions, but often those taken around us.  Read more

Why should future managers invest in Data Science ?

Digital technologiesThe Business Analytics Institute will once again be hosting its Summer School in Data Science for Management in Bayonne, France from July 2 to 11 2018.  In this exclusive five-part series, we will explore the BAI’s unique value proposition around improving managerial decision-making.

Ever since the Harvard Business Review declared a few years back that Data Science was the “sexiest job on Earth”, students have flocked by the thousands in pursuit of degrees in the field. Recent estimates suggest that there are roughly fifteen thousand qualified data scientists working today – a pale comparison to the eighty-one thousand openings for data scientists on LinkedIn this week. Alphabet’s Eric Schmidt recently summed up the situation, “a basic understanding of data analytics is incredibly important for this next generation of young people…”As a future manager, why should you seize this opportunity by enrolling in BAI’s Summer School on Data Science for Management?

 

Why are companies so interested in data?

Klaus Schwab suggests that data and analytics have provided the foundations of a Fourth Industrial Revolution.  Statista’s figures back up this claim – the data centric GAFA corporations accounted for $229 billion of revenue in 2017.The European Commission estimates that the value of personalized data will reach 1 trillion euros by 2020, almost 8% of the EU’s GDP.[v] Cap Gemini’s survey of corporate business executives found that 61% of the respondents “acknowledge that big data is becoming as valuable to their businesses as their existing products and services.Given that the volume of data companies capture grows by an average of 40% a year, it is not surprising that Data Scientists are in such high demand..

Why some much fuss about data?

Data is no longer a simple by-product of a business process, it has become the lifeblood of modern enterprise.  Riley Newman of Wave Capital reminds us that data isn’t just data — it is an imperfect mirror of our customer conversations. If captured and nurtured correctly, data reflects our understanding of current economic realities, and help us predict and influence how consumers will value their experiences over time. Data in itself has no intrinsic value, value is produced in the platforms, processes, and mindsets we put in place to capture and influence customer experiences. Unlike investments in capital goods, the value of these “intangible” digital properties grows over time through network effects as more and more people use them.

What is Data Science?

Success factorsData Science is less about theory than it is about practice, integrating these decision-making fundamentals into the way we work.  Data Science is less concerned with what we do (descriptive) than what we could (predictive) or should do (prescriptive analytics). Today, organizations are looking for data scientists in industries ranging from the health sciences to finance, IT, and the media and public service. The scarcity of specialists to fill these openings is largely because Data Science is marketed as a mashup of analytical, business, and technical skills that are rarely found in any one profile. The only common denominator is a universal vocation of using data to learn about real life business challenges.   Read more

Making A List. And Checking It Twice; Gonna Find Out Who’s Naughty And Nice…

by Professor Lee Schlenker,
EM-Lyon, chair of emerging economics & technologies

[photos by antimuseum.online.fr unless stated otherwise ]

Years aren’t measured in just months and days, but in the intensity of our experience.

November 15th wasn’t quite a day like the others. Woken up in our New York City hotel room by an SMS alert at two in the morning, we learned that the police were evacuating Zuccotti Park.  We consequently changed our morning’s plans and decided to visit the sights of Lower East Side. The protestors were now everywhere but occupying Wall Street, the movement’s sympathizers and the curious provided quite a spectacle.  This circus atmosphere clashed sharply with the peculiar beauty and eerie silence of the 9/11 memorial just a street away. The dissonance between the two left us both dwelling on the past and wondering about the future, and convinced more than ever of the need to focus on what’s important.

D18 immigrants occupy

[photo by OWS at http://occupywallst.org/]

The morning’s events led us inevitably to look for coffee off the beaten path.    We found a small convenience store on Lafayette that offered hot drinks a few tables and chairs to rest our feet. The store’s major attraction apparently was neither Starbuck’s nor Ghirardelli’s, but a myriad of conversations of the indigenous population around Chinatown.  The store wasn’t exactly packed at three in the afternoon, but the conversations about the day’s events, projects and challenges occupied every available space.  As we took in a few sips of coffee and several earfuls of conversation, we couldn’t help but think of Paul Auster and Wayne Wong’s film Smoke, and especially Auggie’s conversation with Paul Benjamin about his photo album. Although places are often haunted by similar people and events, their stories are continuously shaped and refined by experience.

Our eyes slowly focused on a police officer sipping his own coffee at the table next to ours, seemingly oblivious to the conversation around him.  Alone, of medium build, perhaps in his fifties, and not exactly fashion conscious, his weathered skin and uniform seemed to underline the troubles of the day, or perhaps of a lifetime.  We were struck not only by the fatigue that seemed heavily draped over his shoulders, but by his intense concentration in filling out some kind of list. We imagined how hard his day must have been, and asked him if he was glad that it was almost over. He looked up from both his paper and coffee, his weary smile and drained eyes seemed to welcome the opportunity to tell his story.

He explained that his day was pretty much hundreds of others in the past – trying to insure that the pain, the energy, and the commotion of the City didn’t get too far out of hand. Much more important in his mind  was the list he was compiling of his favorite songs that he wanted to record for the end of the year.  As he saw that we didn’t quite understand, he filled in the details.  His life had never been easy, but his girlfriend’s condition was even worse – he feared that she would not make it through another year. His work as a traffic officer differed little that of his colleagues: he didn’t want to be just another uniform.  Decorating the house for the holidays, playing the music his girlfriend loved, and by doing so piecing together their collective memories, was his way of making a difference.  The stories people share  when we take the time to listen….

This chance encounter certainly couldn’t compete with the more media-ready headlines that day. To put things in perspective, the jury is out on whether the events of that day will ever “make” history. I’m not even sure that I could find that coffee shop again on Lafayette, let alone recognize the fellow that took the time speak his mind. Yet there was something profoundly human in that fleeting exchange. I hope I will long remember what he was doing his best to share.

With our warmest wishes for the holidays.

free whitepaper: beyond big data, a business perspective

a bird's eye view of number crunching by Lee Schlenker and the chair of emerging technologies (photo Yann Gourvennec htt://bit.ly/picasayann)

By Professor Lee Schlenker

The emerging technologies and methodologies outlined in this paper can increase our abilities to use data to put our business into perspective. The figures are a good place to start in understanding what they reveal about our work and our work place. Frames, which shape implicit convictions about what work is all about, condition how we capture and interpret the data at our disposal. The business horizon separates the realities we see in the market today from the trends that may well define what opportunities the future holds. The case testimony using Big Data, the Cognitive Sciences, Crowdsourcing, and Social Network Analysis suggest that we can gain considerable insight in understanding how decision makers interpret the data. If work is not about doing things but getting things done, how are you using the data to incite managerial action? We know how to work cheaper and faster, but do we know that we are working on things that matter?

Download the free whitepaper entitled Looking beyond the horizon

 
@ 2011 EMLYON Business School/LHST sarl

The Chair of Emerging Economies and Technologies, established at the EMLYON Business School, coordinates applied research and pedagogy on the potential synergies between emerging forms of organization and disruptive technologies. Under the responsibility of Prof. Lee SCHLENKER, current research of this multi-sponsored Chair includes different applications of Cloud Computing, Management 2.0, Mobile computing, and the evolution of IT partner channels. EMLYON is ranked by the Financial Times as one of the top 10 European Business Schools. Devoted to lifelong learning for entrepreneurial and international management, its distinctive quality is founded on teaching innovation and an entrepreneurial approach to management education. The school offers a full range of graduate programmes in stimulating the social responsibility and the entrepreneurial approach to management of its participants.