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

Selling technology : What are the challenges ?

Through this article, I would like to take you on a trip to India, and give you a tour of how sales happen. Selling technology is an interesting phenomenon to look at, especially in India.

Selling technologies : techniques matter

I was in a mobile store in India and was looking to buy a mobile phone for myself. As I was in the queue to meet one of the salesmen, I saw something amazing. The customer-salesman interaction was basically a speech given by the salesman. Based on the customer’s willingness to pay, the salesman would pick up a phone that fell in that range and start to list all the features for the customer. At the end, I could sense that the customer was confused. Perhaps, he would have ended up thinking if it was really what he wanted to buy, or, was it too sophisticated for his simple use. The customer did see some other models, and again got descriptions from the salesman. There was no deal and the customer left. Since I could not find a proper match for my requirements in that store either, I moved to another shop. This one was way more crowded, and I again had to wait for my turn. I was observing the salesmen again and I made my own hypothesis on why there were more people in this store. The salesmen here would ask people at the very beginning about their requirements, what they actually wanted. One of the customers said, “I am troubled by my phone hanging during every second call that I make”. The salesman quickly picked up a phone and said, “Sir, this one has 2 GB RAM and since it’s a Nokia product, you can be sure that it won’t hang often”. The customer asked the price and after telling him the price, the salesman said “in this range, this is the best one for your requirements”. The deal was done and the product was sold.

In case of the first store, the salesman would begin his monologue like “Sir, it has 8 MP camera, 720 X 1280 pixels display, 16 GB internal memory, 2 GB RAM, dual sim and you can put a microSD card of up to 256 GB”. Now, even though this description includes the one feature that the customer is looking for (say 2 GB RAM), it gets messed up between so many other features which are more or less relevant to him. Moreover, there is very little room left now for a further description of this feature that could satisfy the customer by letting him know that since it has 2 GB RAM, the phone won’t be afflicted with hanging problems. Hence, this “enumeration of all the features” technique, in my view, is not a great methodology to sell technology.

Salesmanship is an art which not every salesman masters.

Selling technology requires this art to be well mastered by the salesforce of a company. Many sales people tend to delineate the features of the product while explaining a product to a potential customer without getting familiar with the actual and precise requirement of the customer. For B2B technology-selling, it is critical to know and comprehend what the business to which we are about to sell a technology, needs. A total unveiling of all the product features is not required in many instances and may end up confusing the customer instead. Just mentioning the right ones shall do the trick. Thus, the description of the product should be propelling enough to create an inclination of the customer towards buying it.

And in B2B , how does the sale happen ?

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Boosting your company marketing with these tools

Online advertising can be a competitive landscape: when it comes to boosting your company marketing, there are a lot of different directions that brands are being pulled in. If you’re wondering which marketing strategies are worth your while and backed by years of success from big brands and small businesses alike, some of the tools below are going to be worthwhile marketing strategies for your business. These are tools that technology businesses, software as a service providers, GPU database companies, and dozens of other business industries are using to grow online.

Email marketing

Although email has been around the longest, it’s one of the most effective strategies for boosting your company marketing. Email allows you to stay in constant contact with your subscribers, continuing to showcase new content, pitch your products or services, or announce company news. Email is a direct marketing tactic allowing you to send commercial messages to an entire group of individuals within seconds. Email marketing campaigns are great ways to get a higher return on your investment when you’re driving traffic to your website.

SEM or pay per click marketing

Online advertising generally refers to search engine marketing, also known as pay per click marketing. This is where you pay search engines like Google on a per click basis to provide traffic to your website. You do this by setting up text-based advertisements that are displayed at the top of search results for targeted keyword phrases. Many businesses use SEM to drive thousands of visitors to their website on a monthly basis. It can provide an overwhelming flood of traffic and boost your company marketing significantly.

Online tools

Search Engine Optimisation

Optimizing your website to rank in search engines is another way to attract traffic organically. By simply creating great content, your website can actually rank at the top of search engines for targeted keyword phrases. Of course, you need to follow optimization standards and do extensive keyword research to integrate these phrases into your writing in a natural and realistic way. Search engine optimization doesn’t provide an immediate return on investment but it is a long-term strategy that can be very effective.

Display advertising

You can advertise with text-based ads, logos, images, graphic design, web banners, or any other type of advertisements on blogs and high-traffic websites in your industry. It’s best to use display advertising with content-based websites that are not a competitor of yours but do have targeted traffic that could benefit your brand. Display advertising has evolved over the years and now includes re-marketing, a way to target individuals that have previously visited your website. This allows you to create high conversion campaigns that are optimized toward traffic generated through other methods. Read more