Analytics’ contribution to Well-Being : Big Data and « Technologies of the Self »


Michel Foucault once argued that the only viable yardstick for measuring technology was whether or not it contributed to human potential. The near future of Health Analytics may provide substantive proof of this vision. By 2020, roughly 25,000 petabytes of patient data will be available to the industry.[i] KPMG’s recent survey of healthcare professionals reveals that fifty-six percent of the participants surveyed believe that this data will largely contribute to our practice of business intelligence, while 35 percent cite lowering healthcare costs, and 32 percent suggest improved health outcomes.[ii] As healthcare organizations invest heavily in technology and analytics to take advantage of these opportunities, what are the opportunities for aspiring data scientists?

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Queen's International Innovation Challenge

How can data spur innovation? 


If management is about reducing risk, uncertainty and ambiguity; data science is about transforming data into collective action. This year’s Queen’s International Innovation Challenge provides postgraduate students an opportunity to use their analytical skills and creativity to address Food Security — a universal, perpetual challenge that just won’t go away. The competition is open to all students registered in a degree or certificate postgraduate program during the during the the current academic year. What is the relationship between data science and innovation, why engage in such a challenge, why « food security », and what will be the payback for your effort?

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Managing Complexity

A manager’s day job isn’t in front of a screen…


…but with colleagues and customers. 

Before diving into the data each day, we would do well to a step back from our desks to review the nature of the problems our organizations are trying to solve.

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Data Science Education

What is the who, where, and when of Data Science education?


Ever since the Harvard Business Review declared five years ago that Data Science was the “sexiest job on Earth”, students have flocked by the tens of thousands in pursuit of degrees in the field.[i] 

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Business Analytics Institute - How can we define Digital Economics ?


Digital Economics

In producing the content for a poster for our 2018 summer school courses on business analytics, I suggested the term “digital economics” as the title of our introductory course on the primacy of data in modern economies. 

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BAI - What do managers need to know about Data Science?

What do managers need to know about data science?


The French publisher Ellipses contacted my colleague Farid Makhlouf and I recently to produce a university textbook on data science for business students. Because there are several valuable introductory texts to data science already on the market, we decided to address the more inclusive subject of Business Analytics. What do future managers need to understand about data, decision science and machine learning to add value to their organizations and their clients?

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Successful management isn't a question of machine learning...

Successful management isn't a question of machine learning...


In the last few weeks of Spring Term, the students aren’t the only ones looking forward to summer. As I was listening attentively to the group presentations one Tuesday morning, I couldn’t help but wonder whether I would be heading off to the tennis courts that afternoon. As I received a call from a friend during the mid-morning break offering to play, I took stock of the weather: sunny, hot, windy, and slightly humid. The last fourteen times I had considered playing, the conditions weren’t quite the same. All other things being equal, can you predict whether I was on the courts that afternoon?

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Banking on the Facts - what is expert advice worth?

Banking on the Facts - what is expert advice worth?


When moving on to my next assignment a few years ago I received the visit of three of my new colleagues. I was quite surprised to hear the first confess that “the first thing you have to learn here is that everyone lies about everything”. The second visitor wasn’t any more inspiring in vouching that she alone told the truth. The third visitor — as they say in French “jamais deux sans trois” — tried to “reassure” me that previous two would be struck by lightning if they ever spoke honestly. In a Smullyanian world in which people are either eternally truthful or disingenuous, which of my three visitors was to be believed?[i]

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Turning Data into Dollars?

Turning Data into Dollars ? 


During his interview last week at the DataWorks summit, Bill Schmarzo brought up the fundamental question of the value of the data organizations are collecting with each click of the mouse.[i] When confronted with claims that “data is the new currency” [ii] and that organizations should strive to “monetize their data”[iii]; one should point out the difference between data’s value of exchange vs. its value in use. I couldn’t agree more with his conclusion that “The value of that data comes from putting it into use to make better decisions.” As we have previously suggested, data is nothing more than a proxy for the reality of our business, it has no intrinsic value outside the customer experience of our colleagues, business partners and external stakeholders.[iv] Which types of data will highlight these differing perceptions of value?

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Measure the quality of your decisions.... and not just your data


Measure the quality of your decisions....

and not just your data


Data will always take a back seat in the drive towards better decision-making. As companies spend increasing amounts of time and effort in capturing organizational and market data, the return on these investments will continue to depend on our ability to transform the data into impactful decisions. Data alone doesn’t produce good decisions for decision-making is constantly handicapped by uncertainty, ambiguity, and complexity. Measuring the quality of our decision-making may well prove more important than improving the quality of our data. Let’s look both at why measuring decision-making is so difficult, and why it is so potentially rewarding.

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