Archive | October 2, 2015

How to buy the cheapest airplane ticket


The most flexible prices in the world are the ones of airline companies. At one moment the price is €90 and a few minutes later the price is €100. In this article I will try to unravel a part of the pricing algorithm of Airliners. From now on, you know how you can find the cheapest ticket, or at least as cheap as possible.

‘Airline pricing is a combination of art and science’ a spokesman of Kayak once said. The goal for the airliner is simple: make as much money as possible on each seat and make sure that no plane leaves with an empty seat. Of course this is not possible, but Ryanair is making a good effort. This summer Ryanair managed to break a record, it had an occupancy rate of 95%, while KLM had an occupancy rate of just 90,1% (Standaard, 2015) (Telegraaf, 2015). So how can airliners make as much money as possible from every seat? And how can you use this knowledge againt them?

Seat availability

Most people think that booking as early as possible is the key for the cheapest air plane ticket. In some way this makes sense. People who book in advance are mostly leisure travellers, and people who book only a few days before the flight are mostly business travellers. They probably have to go to an important business meeting and would like to pay a lot to get on the plane. In contrast to this assumption, research has shown that the best moment to buy your ticket on average (just) 45 days before departure. But keep in mind that this is an average, and it really depends on your destination. For instance, this rule also does not apply in the summertime. During the summer it would be better to buy your ticket about 100 days before departure. One thing is certain, last minute deals do not exist anymore. Booking a ticket one or two day before departure will probably be the highest price the airliner would dare to ask (CheapAir, 2014).


Are you a Mac user? It might be handy to buy your airplane ticket on a Windows next time. As been told during the lecture, Orbitz got sued because they asked higher prices when a Mac computer is used, than when a Windows computer is used. Although this is in the hotel industry, I dare to guess that this trick is also used in the airline industry (Dignan, 2012).

The cheapest ticket I ever bought was €12,50, a ticket from Manchester to Dublin. The transfer price to the city center of Dublin was even more expensive. But I did not get this price without a fight. I was browsing through different booking sites and eventually I found a ticket for €12,50. When I later came back for the same ticket the price was raised to €13,50. I, as a true Dutchman, was of course not planning to pay this stunning €1 extra. I deleted my cookies and the price was back to €12,50 again. When you are booking, always keep in mind that the airliners use cookies. Some websites even keep track of your IP adres, which means that you have to use another router to get the original price. Moral of the story: Big airliner is watching you.


One of the first things you learn during your business course is that the price declines when there are more competitors. Every year the average ticket prices decline with 2-3%, and it is estimated that this price trend is not going to change in the upcoming years (Eldering, 2015). So do you want to go on a cheap vacation? Look for destinations with a lot of (low-budget) airliners, the pricing algorithm of an airline always looks to the price of competitors.

Right place, right time

With Ryanair you fly from the middle of nowhere to the middle of nowhere. Flying to less popular destinations (like London Stansted instead of London City Airport) keeps the prices of budget airliners low. For the airline it is also cheaper to buy departure times in the morning, which has an effect on the ticket price. Being an early-bird can save you a lot of money!


Now you have an idea of how airliners determine their prices. Although there is no golden rule for getting the cheapest price, it turns out it is better to book really early, than booking really late.


Cheapair (2014) ‘When should you buy your airline ticket’, 2 october 2015

Dignan, L. (2012) ‘Mac users just love to pay more says Orbitz’, 2 october 2015

Eldering, P. (2015) ‘Vliegtickets wordt goedkoper’, 2 october 2015

Standaard (2015) ‘Ryainair verbaast zichzelf met nieuwe records’, 2 october 2015

Telegraaf (2015) ‘Stijging aantal passagiers Air France KLM’, 2 october 2015

Social network… What are the limits?

“A new app that promises to let users review individuals has caused controversy before it has even launched.” I am actually referring to a new, soon to be, social network called ‘Peeple’ (, 2015). Peeple can be seen as the Yelp for people. As you can see in the figure below, there slogan is “learn about people. For the people. By the people.”. The question I would like to raise is, what are the social network’s boundaries?


As we discussed last week, there are two types of uncertainties within online markets. First of all the product uncertainty and second of all the seller uncertainty (Dimoka et al., 2012). Peeple will give people the opportunity to actually give others ratings about, for example, their personality and their actions. Could this reduce the seller uncertainty?

Referring to the news article, provided below, there actually is already a lot of controversy about the launch of Peeple. First of all most find it a bit creepy and terrifying. Second, it could cause a lot of legal headaches. Once people are submitted on Peeple’s network, they cannot delete their account. Besides that, people can just make comments about someone, while the person who is being commented, cannot delete these comments without confronting the person who made them. Peeple says that comments will be ‘pending’ for 48 hours, during which the person who is being commented can resolve the issue with the commenter. It all sounds a little blurry, but the whole idea op Peeple could cause legal fights between users. Third of all, people do have a natural fear regarding to Peeple.

Besides all the negative sides, Peeple argued that there will be no legal issues or what so ever. There will be a ban on profanity, degrading comments, abuse, sexual and legal references, racism and hateful content. Currently, the app is expected to launch in November this year. Tests have been made with regards to Peeple’s formula; 5000 members, and every hour 100 requests were made for access. Could Peeple be a success, besides all the controversy?

Maybe most of the users aren’t aware of all the dangers that social network sites could bring with them. Tufekci argues that most of the people have a higher need to be seen than a fear about privacy intrusions (Tufekci, 2008). Do you have a certain fear about social network sites? What do you think of Peeple? Would you subscribe to it?


From Google to Alphabet – “Refactoring” the company

google-alphabet-logo-1439294822Google has been around since 1998. We are all familiar with its presence. Many people have this muscle reflex to type in when they want to look up something. The search results are well optimized that only in rare instances you need to click into the second page. It is so successfully marketed that it even reserved itself a permanent entry in Oxford Dictionary. Google is also a very successful company in numbers. It dominates the global online search industry and its market share outruns the second place by more than 50%. It employs more than 50,000 employees worldwide and it has become an Internet conglomerate.

Normally, when a tech company reaches this stage, we would expect the management style to be more conservative and risk-averse. Intuitively, managing a company of 50,000 employees is, by a number of magnitudes, harder than a company of 5,000 employees. In a large company, a small mistake could have cascading effects and become disastrous.

Google seems to be an exception. On Aug. 10th this year, Larry Page announced his plan to found a parent company named Alphabet, and he seats the CEO position. It oversees all traditional Google products like Gmail and Android; Google X, which hosts several moonshot experiments; Calico, the life sciences branch on longevity; Nest; and Google Venture and Capital. Sundar Pichai, SVP of Google, has now officially become the

This is a bold decision with a possibly very bright future, but it could also be atrocious over the years and destroy the culture that Google has built over the past 18 years. Larry Page explained in his public letter, “in the technology industry, where revolutionary ideas drive the next big growth areas, you need to be a bit uncomfortable to stay relevant”. Alphabet is now comprised of several parts of the old Google. All the experimental branches like Google X or Calico can operate with more independence and momentum. Ever since Google X was incubated, it suffers from limitations brought by traditional parts of Google, because it operates on a much higher velocity. Investors and general public have expressed concerns on unfruitful experiments, and it reached a peak when Google announced to shut down the consumer branch of Google Glass. All these concerns have become irrelevant now. Each individual company has its own goal, and it is free of the limitations set forth by the traditional Google. Furthermore, the management benefits are phenomenal: Larry Page and Sergey Brin are more excited in experimental products, and Sunday Pichai is a proven successful manager who can focus on the continued growth of the traditional Google.

Nevertheless, the downside of this decision is also nontrivial. Apart from its obvious risk level, it separated the revenue generator, Google Ads, from the moonshot projects. It is not likely that Google Ads will stop funding the moonshot companies in the immediate future, but it is possible that all these experimental projects will seek for venture capitalists or private equity investments. Over the years, the corporate culture will likely be very different across all individual companies. This makes talented Google employees harder to join moonshots, and detriments the overall talent acquisition process. Another downside is that the traditional part of Google might lose its innovation velocity. As all the moonshots depart from the traditional company, Google might give more focus on stability. It hurts the search engine in the long run because the market share might drop as innovation becomes stagnant.

In conclusion, Larry Page and Sergey Brin’s rebranding decision is very ambitious. If it works, Alphabet will be even more successful financially, and it will have more impact on people’s daily life. It gives more freedom to experimental projects like longevity research, drone delivery and Internet penetration into rural areas. However if it fails, it will become a management disaster where companies compete with each other for resources and eventually it hurts the traditional Google brand. It is essentially a refactoring in the computer science vernacular. The refactoring will likely take very long time to implement, and only time will tell whether it is effective or not. However, when it does prove to be successful and implemented correctly, the benefit is very substantial.

Your Reference

Page, L. (2015). Google Announces Plans for New Operating Structure . Available: Last accessed 2nd Oct 2015.

Internet of Things: Does it generate service revenues for organizations?

Many of you would think that Internet of Things (IoT) would generate service revenues for organizations. Surprisingly, a recent study of Capgemini showed that over 70% of organizations do not generate service revenues from their IoT solutions.


I am aware that a lot of you already wrote a blog about IoT, that is not unexpectedly since there are more connected devices then humans on the planet, so it is a very popular and upcoming topic. Everyday objects now have sensors whose capabilities might vary. This fundamental shift is leading to an Internet that is far grander in scale and opportunity than we previously imagined. I personally find the IoT world very fascinating. In my circle of friends I have heard a lot of people talking about the convenience of the Nest. The Nest thermostat measures user behaviour. The temperature can be adjusted automatically when someone is asleep or not at home. This also creates a user profile, which indicates how a person lives. In addition, Nest also offers a smoke alarm, and from 2016 it is going to support a smart lock within the system. Last Thursday, Achmea, the largest insurer in the Netherlands, had announced that they are working together with Nest, so that they can have access to the customer data. However, Nest denies that they are collaborating with Achmea. Would you have security and privacy concerns if you were using the Nest? I think a lot of people do. This is also one of the main challenges organizations have to face when they offer IoT solutions.


In a recent study of Capgemini the reasons why organizations are falling short in monetizing the IoT were highlighted. A combination of external and internal challenges make it difficult to generate service revenue for organizations (Figure 1).


Schermafbeelding 2015-10-02 om 14.21.23


In short, the main challenges are that most consumers are concerned that a connected appliance could result in data breach of sensitive information. Second, only a few organizations offer IoT solutions that integrate with third-party products and services. Third, organizations need to augment their product management capabilities with the skills needed to develop and market services. When organizations succeed to cope with these three challenges service revenues will be generated.



Capgemini Capgemini Consulting Worldwide. (2014). Monetizing the Internet of Things: Extracting Value from the Connectivity Opportunity | Resource. Retrieved 2 October 2015, from

NU. (2015). Achmea geeft premiekorting voor data van klant. Retrieved 2 October 2015, from

NU. (2015). Nest ontkent samenwerking met Achmea. Retrieved 2 October 2015, from


The future of work

Technology is changing the way we work, and many of the exciting new developments are just around the corner. But these developments also make a lot of people worried about whether they might be let go since many companies rush to implement automated systems (Fiscutean, 2015) for the sake of efficiency and to avoid human error.

Already long before IT, the way we worked has always been changed by new developments. For example, the upcoming mass production in the industrial revolution caused many people to start working for a boss instead of for themselves. Right now, technology is affecting the type of work we do, how we do it, where we do it, and who our competition is (Choudary, 2015). Crowdsourcing is now creating a completely different competitive market, and new communication tools makes physical distance much less important. In addition, technical advances equip us with new tools to do our work, changing the way we used to do it. For example, mobile sensors and machine learning are helping people in healthcare make decisions.

The type of work is influenced by the amount of automation that is adopted by an organization. Software can, and already has, taken up repetitive jobs from workers (Fiscutean, 2015). Therefore, some jobs will surely be automated out of existence (Choudary, 2015). But new jobs are created as well, the work done by humans will increasingly shift to more innovative thinking, creativity and social skills, as machines don’t typically do these things well (Choudary, 2015).

So just like what happened before, inventions do change the way we work and will make some jobs obsolete. And logically, people fear these developments. However, again the new technology will make people shift to new jobs instead of putting them out of business (Thibodeau, 2014). And these new jobs will entail more creative processes (Fiscutean, 2015) and more implementation related tasks. The real challenge for businesses is to implement automation where it is beneficial, and to exploit the qualities of their people that software is unable to grasp.


Healthcare and Big Data

Health improvement has always been one of humankind’s biggest challenge. Knowledge and methods have evolved along the years bringing continuous amelioration to our everyday life. Two expressions come up often when talking about health: Healthcare and the Healthcare System.  Healthcare, according to Collins, is the prevention of illness or injury on a comprehensive and ongoing basis. The healthcare system refers to the program by which healthcare is made available to individuals.

Using information is, however, a more recent trend. The past ten years, we have witnessed great advances in both data generation and collection but also in our ability to analyze and understand this data. Combining these two trends is referred to as “Big Data” (Marr, 2015).

It may seem as if these two fields have nothing in common, but combining them could create a revolutionary change in the way the healthcare system functions. Moreover, because we collect data about almost anything, we can affect both health and the healthcare system in many different ways.

Even if it remains a new field, it has already attracted major investors who see a bright future in joining big data and health. In total, venture capital firms as well as corporate venture funds of  Google, Samsung… have invested more than $3 billion in healthcare IT since 2013 (Byrnes, 2014).

According to where you position yourself in the healthcare industry, you will use data with a different goal in mind. If we consider pharmaceutical companies, their main challenge is to use data in order to improve profit through overhead cost reduction (Marr, 2015). However, not all parties involved aim, directly, at profit maximization. In fact, many believe big data can lead to better illness prevention.

We all witnessed the increased number of wearable devices such as FitBit, Samsung Gear, TomTom Runner, and many other, that are available for sale.  They all provide you with a somewhat similar information (heart rate, calories burnt, exercise time…) in addition to a progress overview, allowing the user to track progress as he or she exercises. It may not seem like much but if, for example, the information collected was then forwarded to the user’s doctor, he could advise his patient to, follow a more adapted exercising routine, stop unhealthy behaviour or favor certain types of food. Thus taking the system a step further.

This type of information is useful to many, but can also be essential to some. WellDoc and are two examples of firms that collect data about people suffering from chronic conditions such as diabetes, heart disease or depression. Thanks to the data they collect from their patients, they are able to provide a daily “patient coaching system” (Byrnes, 2014) which is sent on the patient’s smartphone, indicating, for example, how much insulin to take or which medication to choose.

Focusing on the ones who benefit highly from such use of data can allow us to better understand the relation between data and health before extending it to the rest of the population.

A ground breaking idea, proposed by the Pittsburgh Health Data Alliance, aims at collecting data on an individual from multiple sources, in order to obtain a comprehensive picture of the person and provide him with “a tailored healthcare package” (Meritalk, 2014). Furthermore, they believe that combining information about millions of people could allow the design of predictive patterns and help spot incoming epidemics, but also provide hospitals and doctors with the most adapted treatment for their patient. Having instant access to a person’s medical record and health information could also prove very useful in case of emergency. It will allow doctors and hospitals to respond faster to a person’s need since no test is needed to check whether the patient’s body accepts all types of treatment; therefore saving lives, time and money.

Many more examples of the revolution that big data is bringing to the healthcare system can be found and it will keep growing. According to McKinsey & Company, “the business opportunity in making sense of all health-related data represents about $300 billion to $450 billion per year. In addition, a PwC study shows that 95% of healthcare CEOs want to explore better techniques to understand and leverage big data.Healthcare’s future is still under construction but we can already see trends going towards a real-time and personalized healthcare, allowing a smarter management of ones health, while reducing costs across the continuum of care (SAP Healthcare, 2014).



Byrnes, N. (2014). Can Mobile Technologies and Big Data Improve Health? | MIT Technology Review. [online] MIT Technology Review. Available at: [Accessed 1 Oct. 2015]., (2015). Collins Dictionaries | Always Free Online.. [online] Available at: [Accessed 2 Oct. 2015].

Diana, A. (2015). Healthcare Dives Into Big Data – InformationWeek. [online] InformationWeek. Available at: [Accessed 2 Oct. 2015].

Marr, B. (2015). Forbes Welcome. [online] Available at: [Accessed 2 Oct. 2015].

Harvard Business Review, (2015). How Big Data Impacts Healthcare. [online] Available at: [Accessed 2 Oct. 2015].


The robots are coming – aren’t they

Humanoid Robots are the embodiment of artificial intelligence but the concept of human like automatons is very old. Karel Capek introduced the word robot in 1921 in a science fiction play (Behnke, 2008). However, these robots were not mechanical man made of metal but they were molded out of chemical blatter and looked exactly like humans. Nowadays, we would call these creatures androids, which is a humanoid robot designed to look as much like a real person as possible (Capek, 2008).

The development of the humanoids is now very advanced and possibilities are becoming bigger. Robots are becoming essential for that kind of tasks that are too dangerous for people. A great example is the Fukushima nuclear meltdown in Japan. Radiation levels became to high for humans to safely enter, so robots went first. The military and law enforcement also see possibilities. Power could be projected and wars could be fought with minimal risk to ‘real’ soldiers, with high accuracy and potentially less risk to civilians (Gillmor, 2013).

An example of the use of humanoids nowadays is in the US army, which tries to shrink the size of the brigade combat team by filling the gap with robots (Scholl, 2014). In order to do this, the Defence Advanced Research Projects Agency (DARPA) and Boston Dynamics, developed a humanoid, called Atlas (Gibbs, 2015). This humanoid can walk bipedal leaving the upper limbs free to lift, carry, and manipulate the environment. Also, when the terrain is very challenging, this humanoid is very strong and coordinated. Atlas, is still being improved and researchers are also trying to develop robots as a platform for useful assistance in disaster scenarios, so they can take over dangerous situations where humans should not or cannot operate. In order to stimulate this research and development a contest has been started with a two million dollar price (Rosen, 2014).

Another example of humanoids is in hospitals. The Alberta Children’s Hospital in Canada has introduced robots to help young patients to stay calm as they get a blood test or a needle (Modjeski, 2015). These robots, called ME102565960-high_5_medi.530x298Di, work as a pain coach and accompany children when they are undergoing a medical procedure. This humanoid is also equipped with cognitive behavioral skills and can talk to children what they are going to experience during the procedure. By doing this they help the children to understand and anticipate on what will happen, which can lead to a reduction in pain experience of fifty percent (Kratochwill, 2015).

Another humanoid, similar to MEDi, is used in nursing homes. Her name is Zora and she is made in Belgium. This humanoid is not only developed to assist in sports and bingo but also to dispel loneliness. The social impact of the aging population is increasing and so are health costs. To prevent these costs from rising further, worldwide millions of dollars have been invested in health robotics. (Nijland, 2014). Robots, like Zora, might disburden caregivers and improve the quality of life for those cared for. However, an important role in the future success of robots is the acceptance of humans. Many eZora2-600x399lderly people see robots as impractical for the tasks they need help with including showering and dressing. However, improvements are made and researchers are working on building personal robots that are socially intelligent and interact and communicate with people in more human ways. While some people will prefer the care of an actual person instead of a robot, robots bring huge opportunities. They could respond to human cues, and provide care and reminders, which will help to relieve family members and the expense of elderly care (Bernard, 2014).

Would you accept the help of a humanoid regarding to personal care like MEDi and Zora? Or do you think this goes to far and humanoids should only be used in situations which are dangerous for humans?


Behnke, S., (2008), Humanoid Robots – From fiction to reality, KI- Zeitschrift, Vol. 4, Iss 8, pp. 5-9

Bernard, D., (2014), A robot to care for you in old age, <>, Retrieved on October 1, 2015

Capek, K., (2008), <>, Retrieved on October 1, 2015

Gibbs, S., (2015), Google’s massive humanoid robot van now walk and move without wires, <>, Retrieved on October 1, 2015

Gillmor, D., (2013), With robots and data, can Google keep to its promise not to be evile?, <>, Retrieved on September 30, 2015.

Kratochwill, L., (2015), CES 2015: RXrobots’s cute humanoid robot helps kids during treatments, <>, Retrieved on October 1, 2015

Modjeski, M., (2015), Alberta’s Children’s Hospital introduces robotic bedside buddies, <>, Retrieved on October 1, 2015

Nijland, M., (2014), Zorgrobot Zora: een feest in het verzorgingstehuis, <>, Retrieved on October 1, 2015

Rosen, M., (2014), Desiging robots to help in a disaster, <>, Retrieved on September 30,2015

Scholl, C., (2013), US Army to replace human soldiers with “Humanoid Robots”, <>, Retrieved on September 30, 2015

Bridging the everyday gaps of solar energy?

With the ice melting, energy prices rising and less healthy air to breath the world is looking for new ways to feed our never ending hunger for energy: renewable energy.

In the United States 39%(1) of the energy comes from coal plants. These coal plants produce huge amounts of energy and transfer the generated energy via the grid to households and other industries. The same principle holds for some renewable energy sources. For example windmill parks work via the same principle, energy gets generated in a big windmill park at sea and all the energy goes one way to the places where it is used.

However, what we currently see is that the generation of renewable energy is getting closer and closer to the actual user and therefore often also on a smaller scale. On one hand Solar can be generated in farms such as the Topaz Solar Farm located in California, which is currently one of the biggest in the world.  On the other hand more and more individual households are putting solar panels on their roof to provide themselves with energy.

Since energy production is starting to get decentralized there is need for a smart grid. With the private production of energy through solar panels one can imagine that during the day a peak amount of energy is produced and transferred to the grid whereas at night when energy consumption is relatively high and local production is low the demand for energy is extra high.  This increases the strain on the traditional grid and therefore measurements need to be taken, for the consumer to avoid peak prices and for distribution network operators to avoid increasing maintenance costs.

Enter Tesla, at the end of April 2015 the company released the so called Power wall which is basically a battery pack for your house. The Power wall  comes in 7Kwh and 10Kwh, to give you an idea: a fridge uses about 1.6Kwh per day and laptop 0.05kwh per hour (2). An industrial version called the Power Pack  is also available, this will allow factories and even small villages to store energy . One could say that the Power wall will solve or at least help solving the problem of the overused grid by saving extra energy for later use at the source where it has been generated.

So will this actually transform the way we consume energy or is it just a silicon valley dream? The Power wall  comes at a price of 3500 $ for the 10Kwh version. This excludes installation costs and of course the cost of solar panels. Forbes calculated that you will pay around 15cts per kwh (3)  when you use the Power Wall solution whereas the U.S. Energy information administration (4) gives an average price for most regions way below that price. For example in West South Central which includes Arkansas, Louisiana, Oklahoma and Texas you pay 11.19 per Kwh.

So the technology might give some future perspective on how to solve our energy problem but at this point it is still debatable whether or not these power packs will have a big influence on your electricity bill.





The rise of the errand boy: crowdsourcing job creation

Crowdsourcing means getting a large number of people to all focus on one task in the hopes that the outcome will be more valuable and successful than the endeavor of one man. As the saying goes: two minds are better than one. Or in this case: hundreds or thousands of minds are better than one. However, most people think this concept is new when actually it started quite a while ago.

Although the term “crowdsourcing” was coined by Wired writer Jeff Howe in 2006, one of the first crowdsourcing projects in the world actually took place in 1714 in England (although Philip of Spain offered a reward for anyone who could solve this problem in 1576). The longitude problem was that, back in that time, sailors had no easy way to calculate the longitude while at sea, causing long voyages to often get lost and result on the death of its crew. Thus, the British government offered £20,000 to the person who could solve this problem, which in the end was John Harrison. Clearly, crowdsourcing is not a new topic. But then why do people think it is so new?

This is because it has only recently become such a rich area of innovation. The concept of crowdsourcing has started to become implemented in very interesting places. Most recently, Amazon has launched its service called Amazon Flex. Most likely inspired by Uber, Amazon allows people to become flexible delivery workers for its Prime service. All you need to get started? A car and a smartphone. Two items which a lot of people own anyway these days. The great thing about services like this is that you are your own boss. You get paid for how productive you are, how much value you bring, as opposed to a set number of hours that you spend in the office.

This could give rise to a whole new area of workers: I like to call them errand boys. These people will most likely choose not to have a stable a job and instead fill their days with various, smaller paid jobs. For example, they could take on a web development job on and when they need a break from working in front of the computer, they can take an Uber run. After their Uber run is done, they can potentially deliver a Amazon Flex package on their way home.

Do you think you might work like this someday?


Insurance company wants our Big (personal) Data

Yesterday an article was published in a Dutch financial newspaper about Achmea, a big insurance company, willing to provide a discount to customers who share personal data. So interestingly, also insurance companies are trying to find new ways to employ big data. After a trip to Silicon Valley, Achmea gained the knowledge about a device that can be installed in your car and registers the driving behavior of the customer. In exchange for the information retrieved, the customer gets a discount on the insurance premium. Is this an acceptable exchange or not?

From the moment the device is installed in your car, it will register how fast you drive, break or accelerate and where and when you did it. The first purpose of the device in your car will be to help drivers avoid damage. The data will help the insurance company to inform their customers about where others have consistently caused damage. In the future, the TomTom for instance will be able to warn you in advance about a risky turn or garage that you are approaching. In addition, the information about your driving behavior can tell what risks the driver faces and hence the probability that the insurer has to compensate for any damage.


Achmea is very enthusiastic about this new idea, while critics are already expressing their worries about the privacy matters that come with it. First of all, it is not always clear what happens with the information that the companies will receive. Will the insurance company use the data against you in case you end up in a crash and they know everything about your driving behavior? Furthermore, some argue that this development will turn privacy from a right into a privilege. As long as you can afford to pay for your insurance without any discount, you do not have to share personal data. However, if the discount can be really convenient to you due to your financial situation, you have to give away a piece of your privacy.

Would you be willing to share data regarding your driving behavior? Is the benefit of a discount worth taking the risk of sharing personal data?


Big Data: Government our protector or enemy?

With respect to big data the government has to deal with two parties with different interest. On the one hand they need to protect their civilians against misuse of data gathered about them. On the other hand they need to stimulate the economic growth and enable companies to use big data tools in order to make their companies grow.

But what does the Dutch government do in order to protect their civilians against misuse of data? Companies are allowed to make predictions about their customers using big data. But the base principle is that everyone should have access to the same products/services according to the government. This means that companies are not allowed to segment on race, religion, gender or nationality (Kamp, 2014). The Dutch government states that this is not allowed, but what are these women clothing ads doing on my Facebook page?! They obviously know what my gender is and adjust their ads based on this information. Next to this there is a big law package that should protect us as civilians against the misuse of big data. But how are they going to enforce these laws with such a huge amount of data created everyday in our internet-based society?

In mister Kamp’s letter the focus is on protection of civilians. But in the introduction he talks about stimulating SME’s to acquire tools in order to process big data (Kamp, 2014). Overall this letter comes across as a shout out to all the companies: “Use big data, it is beneficial for your company!” But we are going to protect the civilians as well. But how? With some laws etc. etc. They don’t say a word about how they can guarantee us, as civilians, that these lines are not crossed.

Personally I think that the government should protect its civilians by focussing on big data legislation and law enforcement. I would like to know how they are checking big data use at companies and if it is in line with the countries laws. What do you think the government’s role should be in the big data topic? Should they focus on economic growth or protecting their civilians? And my biggest concern; how are they going to enforce these laws?

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Kamp, H. (2014). Kamerbrief big data en profilering in de private sector. The Hague: Department of Economic Affairs.