For its 10th Service Science Café, revolving around the hot topic of Big Data, the Service Science Factory (SSF) in Maastricht decided to make its guests experience the world and possibilities of data right from the start.
Upon arrival, participants were greeted with a smile and an invitation to have their picture taken with an instant camera and to put it up for display on a public board next to their business card for everyone to see. Next, they were offered to participate in a short profile survey by answering a few questions, using a digital scanner, about their gender, age, professional background (academia or business), their favourite super hero and their preferred mode of transportation.
Within minutes, the SSF team had managed to collect a set of data that could prove very insightful in its efforts to better know and serve its audience. This was done by way of entertainment and fun interaction, but at a deeper level the experiment showed the potential value of data gathering.
Connecting people and expertise
For loyal visitors, a trademark of every Service Science Café is its open and welcoming set-up. This time was no exception. Participants were treated to refreshments and a celebratory creamy pastry (tompouce) marking the 10th edition of the initiative. The afternoon started with a brief overview by Scientific Director Gaby Odekerken of the nine previous events and a playful “meet and greet” session with Lego bricks led by Strategic Account Manager Sjannie Hulsman. This helped to break the ice and create an informal atmosphere which lasted during the presentations and the several networking moments that were planned throughout the afternoon.
Another trademark of every Service Science Café is the way it brings together and connects different types of people and different types of expertise, thereby triggering new ideas and perspectives around chosen themes. This very much mirrors the way SSF carries out its projects, by setting up each time a new team consisting of members with different backgrounds and skills.
The afternoon was divided into various sessions ranging from presentations of recently completed projects to a panel discussion with specialists in the field of Big Data to interactive workshops.
What is Big Data?
In her opening words, Gaby Odekerken immediately touched upon the complexity of the day’s theme: “Big Data is a buzz expression that seems to mean something different to everyone,” she said. “It is often used to convey the immense possibilities offered by the increasing supply of datato analyse and understand the world we live in, but it also implies a number of challenges and even threats in terms of ethics and privacy issues.”
The adjective “big” in “Big Data” also suggests a sense of urgency. When we refer to something as being big, we highlight the fact that it is not standard and also indicate that it may need to be monitored and perhaps acted upon.
The four Vs of Big Data
The concept of Big Data is usually defined by the four Vs, with each letter V representing a specific aspect to take into account when dealing with the topic: Volume, referring to the large and growing amounts of data; Variety, indicating the different types of data available, ranging from sounds to locations to messages to images; Velocity, stressing both the high speed of data generation and the high speed of analysis required; Veracity, relating to the dangers associated with Big Data, from individual privacy issues to intellectual property protection.
Data however, whether big or not, does not have much value by itself. It is only when it is transformed into usable information that their value emerges. “New insights gathered from data analysis can even lead to tremendous new revenue streams,” explained Project Leader Vanessa Lusian, as she introduced the Big Data Centre project that SSF recently completed on behalf of the Maastricht University School of Business and Economics (SBE).
“Big Data is often considered to be the New Oil,” she said.
A Big Data Centre at Maastricht University?
The aim of the project was to study the desirability and feasibility for Maastricht University to facilitate the implementation of a Big Data Centre that connects the expertise of academics at Maastricht University and other knowledge institutions to the need for insights organisations are looking for today. Such a centre might create opportunities to unleash new analyses, insights and business innovations, specifically in the field of services.
Baptised CODE2, for Centre of Data Expertise and Experience, the Big Data Centre would provide a platform that unites experts from various disciplines who, through Big Data analysis, would be able to tap into uncovered market niches, answer questions and develop innovative services, serving a variety of potential customers such as researchers, students, governmental organisations and businesses in the South Limburg region and well beyond.
The project, initiated by SBE, is now entering its second phase in which SSF will explore how the Smart Services Hub initiative in Heerlen could benefit from the ideas developed during the first project.
Big Data applications
The presentations and sessions that followed explored several technological and ethical issues related to Big Data.
User Experience Researcher Aditya Pawar presented the results of a project he recently conducted for Canon on the future of healthcare. “New models of healthcare will increasingly be based on working with the patient as a collaborator,” he said. “To realise this type of integrated, self-managed care, future healthcare systems will increasingly depend and rely on patient centric data, enabling the patient to be part of the decision-making process.”
During the panel discussion on Big Data, Simon Gobert, Process Expert at DSM, praised the enormous potential for business intelligence offered by Big Data, while Pascal Slaats, lecturer at Zuyd University of Applied Sciences warned about the possible negative side effects of data manipulation. Both Georgi Nalbantov, Senior Research Scientist at Maastricht University Medical Centre+ and Evgueni Smirnov, Assistant Professor at the Department of Knowledge Engineeringat Maastricht University, were more interested in the development of Big Data systems to serve specific societal needs, in the field of healthcare and education for example. They both indicated that their main challenge was less in the volume of data than in the linking of various existing data systems to produce new services and applications.
Smirnov provided a very interesting example of an application of Big Data that is being offered at UCM. “We have developed a system that helps our Bachelor students find the best Master study for them. It has been running for two years and we receive a lot of positive feedback on it. The next step is to develop a system that will help us advise our students on possible jobs. The difficulty here is to link our system to the job agencies. But the idea has great potential.”
Big Data and Service Innovation
The last activity of the Service Science Café was an interactive workshop where the participants were first presented with six new societal trends, such as the shift from passive to empowered consumer, the development of personal information gathering, the rise of collaborative consumption models, among others. Then they were invited to split into small groups to do two rounds of brainstorming, first on the kind of data that these trends would generate and second on the potential these data would have for developing new business ideas. The purpose of the exercise was to demonstrate the potential of Big Data for service innovation.
After a final networking moment with snacks and refreshments, and more conversations on questions such as: “What is the difference between Data and Big Data?”, “What is the difference between Data mining and Big Data, and which one comes first?”, “Is the word Big in Big Data a reference to Big Brother?”, participants were invited to share their feedback by taking a quick digital survey on their level of satisfaction about the event.
The results of the first survey were already hanging on the wall. They indicated that more than half of the participants that afternoon represented businesses, most were older than 30, that there was a balanced gender division and that the Hulk had been a big loser as a preferred superhero.
In what way will these findings influence the set-up of the next Service Science Café?
By Sueli Brodin