Archive by Author | birgitfriemann

Digital Transformation Project Group 18: Transforming HousingAnywhere B.V.

Our Digital Transformation Project revolves around the student housing market. As most of you know, the student housing market in the Netherlands as well as in most university cities is fierce and especially for exchange students and international interns, housing is often difficult to find. Finding appropriate housing remotely and for a limited time period can be very difficult, since the traditional way of looking for housing entails the viewing of several rooms and usually housing contracts have minimum durations that are longer than university exchange semesters last.

The company that we have analyzed is Housing Anywhere B.V., a local start-up company founded in 2009 in Rotterdam by two former students of Erasmus University. Through their website, they provide an online platform which aims at solving the afore mentioned problem.

The current business model of the company intends outgoing students to sublet their rooms to incoming students, enabling them to find appropriate housing. For both, the housing-suppliers and the housing-consumers, the platform is free to use. Nevertheless, HousingAnywhere’s business model entails several weaknesses and threats, as the revenue created does neither originate from the housing-consumers nor the housing-suppliers but is generated through contracting a third party, namely the relevant universities in each city, who pay for their students to have a positive experience.

Overview of HousingAnywhere’s platform structure:


Since these universities do not directly benefit from HousingAnywhere’s offer, this system creates dependencies and threats to the sustainability of the growth and competitiveness of HousingAnywhere. Integrated in the problem of the dependencies on the universities is the problem of a limited adoption rate of the platform and a limited revenue because the current business model focuses on students as platform users on both sides and excludes many potential suppliers of rooms, as controlled by the universities. Thus, a critical mass on the supply side is missing to ensure a fast growth of the network.

In order to counter these identified problems, we propose several changes in the overall business model, such as broadening the possible supplier base and changing the revenue model from a sole dependency on the universities to a model where the housing-consumers generate the main revenue stream. Additionally, we suggest to subsidize the supply side not only monetarily but also through the offering of value-adding services.

Along with a change in the business model, HousingAnywhere has a need for an information strategy that accompanies its transformation. Thus, we present three information systems that will help HousingAnywhere to add value to their offer and attract more users on both sides of the network: (1) A data system, that shall analytically add value to the data gathered by HousingAnywhere’s platforms, (2) an automated payment system, that provides a more secure payment environment to housing-consumers and suppliers, and (3) an automated contracting system that shall help suppliers around the world to easily set up and exchange contracts with their respective customers online. The analysis of benefits, costs and risks encourages us to suggest to implement all three solutions in order to improve HousingAnywhere’s business model.

In order to leverage the benefits of the proposed solutions as early as possible, we suggest that HousingAnywhere starts the planning, development and implementation of the systems right away, thus increasing the potential for growth and a sustainable competitive advantage in the market.

Nevertheless, in order to reduce the risks incorporated with such a major change in the business model and the information strategy, we recommend HousingAnywhere to plan the implementation of the new information systems incrementally and run pilots before fully rolling out the systems. Together with thorough market research and an aligned marketing strategy these recommendations can help HousingAnywhere to defend their competitive position against new market entrants and to grow.

Amazon optimizes delivery time through anticipatory shipping

Anticipatory shipping When you wanted to buy a CD or a book a couple of years ago, the fastest way to get your new product was going to a shopping mall or the city center and buy it there from a bricks-and-mortar shop. With regard to the time passing betweeen your buying decision and holding the product in your hands, online retailers have still been at a disadvantage. This is changing now with advancing digitalization – especially in the books and music segment.

Nowadays, products in the form of downloads can be bought by and delivered to the end customer instantly; it merely takes seconds before, for example, an e-book appears on your kindle e-reader. But what about other, physical products? Do bricks-and-mortar shops still beat online retailers delivery time-wise? Currently, they certainly do – but for how long?

Exactly this issue just described has been on Amazon’s mind for a while now. After all, no company knows its customers better than Amazon does, so it should be possible to turn this into an important advantage, exploiting its possibility to gather big data on customers to render one of the last pro’s of bricks-and-mortar firms insignificant. Amazon’s answer to this problem has become manifest in a patent that they filed in December 2013; the solution seems to be “anticipatory shipping”. Anticipatory shipping means packaging and sending out a product before a customer even hits the “order now” button. More specifically, products are sent – in advance – to a warehouse in a region where Amazon expects an order according to their internal CRM system, thus optimizing the dispatch route. This way, Amazon wants to leverage its immense knowledge about its customers, so that in some cases where they could be very sure of a future order, they would already completely package a product and put a full address on the parcel before the order is fulfilled. When the order then reaches Amazon’s system, the parcel can be sent out directly and on the shortest possible route, making same-day delivery the norm rather than an exception.

According to Amazon, the technology already works well with very popular products, allowing people to receive items like a new iPhone on its release day. With Amazon’s possibilities to collect data however, it should be possible to extend this opportunity to less popular products. Order histories, product searches, wish list and shopping cart analyses, and even the time your cursor is directed to a certain product – it all helps to make you the ultimately transparent customer. Each click and each order helps to refine your profile and to anticipate your next order.

Until this point, it is not sure whether Amazon will exploit their patent and implement the idea of anticipatory shipping. But if they do, it might be possible that Amazon knows its customers – you – better than they know themselves. How long will it be until a mailman rings at our door before we even hit the order button?


Wall Street Journal: before-you-buy-it/

United States Patent and Trademark Office:

Quantified Self – control gain or control loss?

Self-trackingWhen we found out about the massive data collection of America’s NSA we were more than alarmed. Truth is, today more and more people collect and share very personal data – voluntarily and frequently. The trend of so-called “Self Tracking” has become popular in the USA and is increasingly spilling over to Europe.

Imagine Rick, a hobby self tracker. Wearing the wrist band has become normal for him. His day starts when his heart rate indicates a light sleep phase, the perfect time to easily wake up. He heads to the bathroom; keeping track of the amount of water and warm water in particular that he used. His scale measures his weight and body fat, directly connecting to the respective application on his smartphone that creates clearly arranged diagrams for him. When ready for breakfast he checks his last night’s sleep – apparently, he did not sleep very well. His first meal of the day begins his exact food tracking of every day. In order to decrease his relative body fat, he is on a special diet at the moment. When leaving the house, Rick starts counting his steps. 10,000 steps are quite a goal, so he decides to skip the first tram station and to walk instead. When reaching university he takes the stairs instead of the elevator – a behaviour that he’s become very used to. After class in the library he uses a special software to track his own productivity and the pages that he has read in a specific amount of time. This way, he knows exactly when it is okay for him to go home and head for a run. Without Runtastic, of course, he wouldn’t have an idea of the progress he is making. At the end of the day he looks at his diagrams satisfied, knowing that he achieved his goals for the day. He is ready for a hopefully better sleep this night.

This short story tells features of today’s reality that almost everyone has gotten in touch with by now. The trend of quanitfying yourself has become more and more common – the launch of the Apple Watch is just another indicator.


  • Behaviours that were very unconscious in the past can be made explicit
  • We can gain more control over our time, body and health
  • It is easier than ever to live a healthy, fit lifestyle
  • It is cheaper than ever to buy the necessary gear
  • Very often, self tracking involves some degree of gamification, it’s fun
  • The link of everyday life and technology is fascinating


  • We lose control over our very personal data
  • We often do not know which application collects which data and what is done with it
  • There might be severe security issues with regards to how your data is stored
  • We don’t know who does and will have access to your data
  • Increased risk of identity theft
  • Tracking ourselves can cause addictive behaviour, our realistic perception of our own bodies etc. might get lost
  • Humans are reduced to numbers

Apart from the listed con’s, risks become very concrete when thinking about who could or might have access to our very personal data in the future. Do you want your health insurance to know you don’t work out enough to maintain a good health status? Do you want your employer to know that you were not really sick the last time you were on sick leave? Do you want a potential burglar to know where you are – and where you are not?

Thinking about this trend of tracking and quantifying everything about oneself leads to many questions. Do the benefits of these technologies outweigh the costs? Do we not give away the last bit of privacy that we had left?