Big Data = Bigger Health Inequality?

We’ve already established that big data is a game changer. This is as true for business as it is for our daily living – including our individual and public health.

Big data is already being used in health research, preventative health care, treatment and therapy. For example, new websites are popping up that allow patients to track their symptoms and outcomes in real time. This allows others in similar medical situations to analyze the individual and aggregate outcomes to help make their medical decisions. Some of these websites, like patients like me, even show an expected outcome for your case for each potential intervention based on the available data on the website (watch the website creator explain it here). A January 2013 McKinsey report entitled “The “big-data” revolution in health care” describes the impact of big data and how it is helping and can continue to help lead to right living, right care, right provider, right value and right innovation.  

The May 2011 McKinsey report Big data: The next frontier for innovation, competition, and productivity estimates that “big data can enable more than $300 billion a year in value creation in US health care”. As exciting as the potential of big data is on public health, I can’t help but ask if big data represents the next big thing in health inequality?

It has been long established that health is strongly correlated with socioeconomic status (just check out gapminder if you aren’t convinced). Low and middle-income countries bear a disproportionate mortality and morbidity burden. In addition, within a country, poor, vulnerable and marginalized groups have inferior health and health outcomes.

Traditionally, these are the groups who receive the lowest level of health care coverage and fewest research dollars – currently less than 10 percent of medical research is devoted to diseases that account for more than 90 percent of the global burden of disease. Unfortunately, they are also the groups who generate the least data and, consequently, where big data will have the least impact.

If big data is going to revolutionize our world as quickly and as profoundly as predicted, and if “primary data pools are at the heart of big-data revolution in healthcare” (McKinsey, 2013 report), it is these already underserved and overburdened groups who will benefit the least. This risks creating an even greater health inequality.

What’s the solution? We need to work to generate a robust data reserve for underserved groups and start using it. Here are some simple steps that we can take to get there:

Go digital: Many of the information systems used in global public health don’t give us big data because they don’t use digital data collection. Many large and resource intensive sociodemographic and epidemiological surveys are still conducted using paper and are never fully entered into a digital format. New technologies and tools should make these collection methods a thing of the past. Joel Selanik explains the problem and presents one great solution in his TED talk (here).

Ask for help…from non-experts: a research team from the Harvard School of Public Health used 1,000 non-scientific volunteers to analyze an enormous data set of tuberculosis bacterium growth videos. The team of volunteers was able to analyze the information in two days, which would have normally taken the research team three months. We need to start unleash the power of crowd sourcing solutions.

Open your mind to open data: The culture of traditional research has created incentives for groups to protect their data. This has to be a way of the past. Key players like the United Nations, including the World Health Organization, have already made their data sets public. All organizations, countries and researchers should follow suit and allow the public access to non-personal health information so that evidence based public health can be crowed sourced for all diseases across various contexts.

                                          Paper Data Collection on Health in Rural India

Big Data - Why you pay more than your neighbor on a plane...

Next to consumer goods and financial institutions the travel industry sits on one of the largest data repositories regarding customer information and number of transactions. In addition, it is one of the most flexible and complex industries since prices and in parts capacity can be adjusted on a real-time basis to balance supply and demand. Moreover, we all know that marginal costs for an empty room or seat on an airplane are low for the company and that an unsold spot is a forgone revenue opportunity.

Key to manage these complexity and to exploit all revenue opportunities is therefore to have up-to-date information systems that not only present isolated information about an individual customer, but rather integrate information across all important data sources and allow to derive superior insights and strategies. Potential data sources in the travel industry could be market share and pricing information of competitors, capacity information as well as current and historic transaction information. By combining all this information valuable insights can be created and concrete recommendations and trends being derived automatically by the system to maximize revenue. Having such systems in place radically changes the needed skill profile of your employees though, which becomes significantly more analytical and shifts to making tactical and strategic decisions rather than executing rule-based pricing. Companies need to adjust for these changes and train their employees accordingly as well as giving them the needed level of freedom and responsibility to act in such an environment where static rules do not work. The Pricing Manager eventually becomes a trader that takes calculated risks on a daily basis.

In addition, all the information helps the companies to better understand their customers and to create new product offerings that differentiate them from competition and help to win market share. An example for this can be hourly pricing based on check-in and check-out times, but also product bundles that increase the convenience of booking for the customer. By analyzing the booking pattern of customers companies can even try to derive the willingness to pay of certain customers and start customer-specific pricing strategies throughout the booking process, which is quite powerful in combination with loyalty programs that provide additional transparency about the customer’s travel behaviors.

Big Data is therefore extremely valuable for the entire travel industry and companies should be on their toes to early adopt and take advantage of this new field of data analytics. 

The future of HR: Big Data

As we mentioned in our first post, Big Data is “everything we do”, it is in our daily life wether we want it or not. Although some people may think it is only on Facebook, Google, YouTube, or Amazon, Big Data is much more that that and can be used in many areas of a company such as Marketing, Sales, HR and R&D. 

In this post we will focus on some of the relations between BD and Human Resources. Today’s world makes recruiters compete for superior talent while the company’s top management asks for more input to make faster and better recruiting decisions. Big Data can improve the company’s selection process, by helping us to better hire, understanding the market and filtering among hundreds of CV’s to select candidates that will be the right fit for our organization. 

Moreover, if we focus on employees, companies employ hundreds of people and over the years they have created databases with all the demographic and performance information, education, age, marital status, among many other factors. This information can be use to predict metrics for the organization and to make better “people” decisions in advance and most importantly to predict organizational performance. 

The success for Big Data and HR involves combining and analyzing metrics as performance, previous positions, and salaries, among others to provide more accurate and smarter solutions to business problems that face the organization. 

For more information on Human Resources and Big Data: 

http://talentmgt.com/articles/view/hr-can-t-ignore-big-data/1

Guess what?! Big data "knows" who you will vote for in next elections!

Do politicians build strong platforms or do they just follow Big Data to win in the elections?

Elections: The process that involves thousands of people and takes massive character every few years across all elected governments on earth. Elections are the time when huge campaigns run at each distinct part of the countries and when consultants prepare massive polls and analyze loads of information to identify and target millions of voters.

The US Politicians learned fast to adopt Big Data and now they apply it to the attitudes and preferences of the population to “understand why people are voting for them or why they’re not, and that has the effect of hopefully being able to change policy in a more meaningful and democratic way”. The 2012 US elections displayed how Big Data could be used for turning gigantic campaign data into detailed practical information. Data analyst Nate Silver became a celebrity when he managed to predict the results in each of the 50 states accurately.

Few contraindications for the application of Big Data in elections exist though. In the 1948 elections, the polls (Big Data back then) predicted a Thomas Dewey victory over Harry Truman. That election marked the first time pollsters relied on telephone surveys, giving them access to more voters. It turned out that a lot of Truman supporters didn't have phones. The real results turned out to be otherwise. Or bringing parallels to nowadays, when huge campaigns and platforms are built to count the polls of voters on Facebook and other social platforms we must consider that “the elderly woman in Philadelphia, who doesn't have a photo ID, also probably doesn't tweet much or otherwise contribute to the 15 terabytes of new information on Facebook every day”. This example shows that Big Data can be very helpful in our everyday life and that no one can escape from it, but analysts need to keep their critical mind to not blindly fall into the data gap.

Is big data the new oil?

Oil has been a major driver for the economic development around the world in the last century. Big data is probably becoming a key resource for businesses in any area in the 2010s and going forward. It will be used in a different way, but may have the same critical impact on daily business life. The raw data collected has similar to crude oil a limited usability. Like oil, raw data needs to be processed before it can be used. In fact, raw data needs to be refined or more appropriate in the case of data filtered, order or distilled. In this respect, big data represents an oil well with a great amount of information. Compiled in the right way the data allows businesses to make better decisions.

As discussed above big data may have a similar impact as oil on the world's economy The value of data is priceless when we are able to properly make use of it. Some would call it a “game changer”. Consequently, the data base may become the oil barrel of the 21st century:

We are just at the beginning of a rapid development. The opportunities that derive from the effective deployment of data are uncountable and very valuable to every type of business. From today’s perspective we are not able to conceive what will be possible in 10 years from now. Current use of big data especially for the tracking of customer information already supports marketing & sales efforts. Steven Spielberg’s movie “Minority Report”, in which face recognition is used in a scene in a shop to approach the client with a tailored offering, is only one aspect. While the movie takes place in the year 2054, this kind of application seems to become available in the next view years. However, privacy rights and face recognition seems to be an area of potential conflict. What is more important, a perfectly customized product or the privacy rights of every individual?

Follow this blog closely over the next few weeks as we will add the potential impact of big data on several industries... 

It makes LIFE so much easier!

BIG DATA - How is it changing the world around us?

What is Big Data?

Everything we do, using Facebook, watching movies on YouTube or Netflix, Chatting on Skype, Talking on Mobile, shopping online or off-line or eating at restaurant generates data at an unbelievable rate. A multitude of sensors, cameras, smartphones, laptops tablets are fueling

 this unprecedented rate of data generation. This rate of data being generated every minute has been previously unseen. These data flows can be of thousands of gigabytes, and because of the sheer size of such data, it is called the BIG DATA. In the digital world we are leaving a trail of data when we search, browse, buy, comment, like, share, blog, watch. This trail of data creates a digital foot print of each of us. A lot can be derived about us from this data trail – from the car we drive to whom we like to when we wake up in the morning.

Why is it Important?

This data has opened a window into our world. There is more and more information available about us.  Google has been collecting data on our search behavior. Google uses this data to provide relevant search results and advertisements. Similarly Facebook collects data on all the things we do (like, share or comment). It uses this data to assess the strength of the relationship with our Facebook friends. This then determines what updates appear on our page.  The size of the data provides unlimited ways in which this data can be used. However, we may feel a bit concerned about the personal privacy, but the utility of data is tremendous.

Government and companies can benefit by using this data in variety of ways to improve efficiency and productivity. For example let’s say there is lot of Twitter feed about a new product. A firm can analyze the data of these feeds and see what is the response, who is driving the response, who are the early adopters, who are excited or not so excited about this product, what kind of networks are being formed. Analyzing this data can provide useful insights and help developed new and effective solutions.

How it is being used?

Big data offers huge opportunities, for instance, in healthcare. Analyzing data about patient history, his lifestyle, health history of his or her family and close relatives can provide useful information about what health issues can arise in future. At a macro level it can be used to analyze health issues of large populations and government agencies can use big data to intervene and understand the issues better.

Another example is Netflix; it has been collecting big data on consumer movie viewing habits. It has used this big data to refine it movie recommendation algorithm. This algorithm can very accurately predict if we would like a movie or not based on our past viewing preferences.

It is clear and evident that big data is going to change our future and many more ways than we can think now. For starters we will use data from our Blog post (using Google analytics) to analyze & improve our blog.  Watch this space for more....