Business analytics and Big Data: Opportunities for VU University Amsterdam?

BigDataKlein

By dr. Frans Feldberg and dr. Tibert Verhagen 

When the subject is Big Data, the discussion can become heated. Industry sees abundant opportunities for using Big Data to achieve revenue growth, improve performance, generate new business models and so forth. Market research bureau Gartner reports that industry has consistently put Big Data in the top ten of strategic technology trends in recent years.

The scientific and academic worlds have also discovered the relevance of Big Data, even calling it ‘the mother lode of disruptive change in a networked business environment’ (Chen et al. 2012, p. 1) and a foundation for digital innovation (Fichman et al. 2014). From a social perspective, Big Data is certainly not viewed solely as an ‘opportunity’. The discussion about Big Data focuses as much on ‘threats’ as on opportunities, and centres around important issues such as privacy and ethics. A customer intelligence manager at a major telecommunication company captured the concerns succinctly in a recent presentation: ‘Big Data: big dilemmas!’ From this perspective, Big Data is certainly a phenomenon that universities should be exploring.

But what exactly is Big Data? ‘Big’ should not necessarily be interpreted as ‘a lot of’ data. The term is used for applications where the quantity of data and analysis techniques are large and complex enough to require unusual, advanced technologies for storage, security, data management, visualization and analysis (Chen et al. 2012). These applications are accordingly beyond the reach of traditional database and data warehousing technologies. Big Data has also been called the modern equivalent of the microscope (Brynjolfsson and McAfee 2011). The arrival of the microscope in the seventeenth century meant that scientists could scrutinize objects whose very existence was previously unknown. This Dutch invention had a considerable impact on scientific opportunities and achievements. The impact of Big Data may be similar. Big Data has the potential to reveal hitherto unimagined features by setting powerful analysis tools to work on the subtle details within enormous quantities of data.

Is Big Data new for VU University Amsterdam? Regarding the essence of big data, which is about translating data into action-oriented insights, research groups in various faculties have been engaged in this aspect for a very long time. Many different labels have been given to the research involved over the course of time. The term ‘Big Data’ was coined in 2008 in a special issue of Nature (2008), but is consistent with a line of thought in which the importance of data is shifting from a ‘transaction vehicle’ to a ‘source of value’. This line of thought started in the 1960s with the introduction of management information systems, and recently spawned the term ‘data science’ (Davenport and Patil 2012). Big Data is closely related to Business Analytics (Chen et al. 2012), an area of research devoted to the analytic component of transforming data into knowledge. This analytic component can be concerned with statistical analyses, or the development of models for forecasting, extrapolation and optimization. The importance of Big Data in this context is that it provides ‘microscopes’ for managing both large quantities of data and the complexity inherent in the analyses. Big Data makes new analyses in the Business Analytics domain possible and feasible. For example, Big Data tools allow analyses that would once have taken days to complete in a matter of hours. Business Analytics is an area of research in which we at VU University Amsterdam have been engaged for many years, and in which we have accumulated substantial expertise and experience. The VU University Amsterdam Faculty of Sciences even has a separate ‘Business Analytics’ programme, in which the Faculty of Economics and Business Administration plays an important role.

Our success in combining the increasing importance of Big Data with our scientific expertise is a matter of noblesse oblige. The departments of Information, Logistics and Innovation (Faculty of Economics and Business Administration) and Mathematics (Faculty of Sciences) duly combined forces in 2012 to set up a multidisciplinary research centre known as the Amsterdam Centre for Business Analytics (ACBA.nl). The goal of ACBA is to develop, disseminate and commercially exploit Business Analytics knowledge by bringing science and industry together. Fairly soon after its foundation, the Department of Computer Sciences (Faculty of Sciences) joined ACBA, creating not only a unique pool of ‘business’, ‘analytics’ and ‘informatics’ knowledge, but also equipping the centre with a platform that encompasses all the components needed for decision support: data, models and interaction (Sprague 1980). For example, companies are grappling with the large quantities of data (Big Data!) that their users generate on their smartphones, along with ways of converting these data into knowledge (models), and of using what emerges to help clarify issues surrounding customer satisfaction and loyalty (interaction with markets). These three elements are not isolated from each other, but demand an integrated approach. As a multidisciplinary research centre that possesses the right expertise and technical infrastructure, ACBA offers companies such an approach. A ‘one-stop shop’ has thus materialized within VU University Amsterdam that companies can approach not only with questions related to Business Analytics, but where ‘labs’ are also available to support all relevant components.

Various organizations are now involved in ACBA. One is a medium-sized company in the bicycle industry that views mobile interaction with its users, Big Data and social media as the determinants of digital innovation. This company needs to know what gets cyclists going, both literally and figuratively. Together with ACBA, it is developing a smartphone app to support amateur cyclists in training and competitions. The app can be classed as a decision-support system that gathers data about such factors as distance travelled, speed and training session times. The large quantities of data (Big Data) are collected online in real time, analysed, and fed back to the cyclists. The pilot system developed for this purpose uses the existing research infrastructure that is integrated into the platform. Computer Sciences has the expertise to manage large quantities of data in multiple locations (the cloud, smartphone, etc.), Mathematics can develop the models to feed back the requested information in real time, and Information Sciences can arrange for valuable interaction with the cyclists and identify just what it is that ‘gets them going’. Human movement scientists will be invited to contribute their know-how regarding training schedules, fitness level and health. And it goes without saying that the entire team is considering the impact of this kind of solution on privacy. Another example is a municipality that has joined with ACBA to research opportunities for using Big Data and Business Analytics for public administration, and for supporting residents in relevant decision processes. This municipality is running several pilot projects, one to support informal carers, and another to promote healthy behaviour. Furthermore, Deloitte is the sponsoring partner for a study on the opportunities for using Big Data in revenue management. Finally, we would like to mention a research project about the use of ‘wearable devices’. These systems, often in the form of an armband or wristwatch, are used by individuals to log movements, sleeping patterns, nutrition and state of mind. Based on the data, users receive information about their personal performance (biofeedback), and they can use what they learn to make decisions of their own for a healthier life. With the research we hope not only to shed light on the ideal combination of factors, but also on whether the use of the data that this kind of system can deliver really contributes to a healthier life. All these projects go beyond investigating opportunities and also consider privacy-related and ethical aspects.

The projects described above represent a very limited subset of everything that is going on in the field of Business Analytics and Big Data at VU University Amsterdam. A great deal of relevant research is also being carried out in the departments of Econometrics & OR and Marketing at the Faculty of Economics and Business Administration, for example, and likewise in numerous other departments of various faculties at VU University Amsterdam. As to whether Business Analytics and Big Data offer opportunities for VU University Amsterdam, the provisional answer is a definite ‘yes’. Since Business Analytics and Big Data are currently so pertinent, there is no need for us to take a modest stance, and indeed we are in a position to demonstrate our ability to perform extremely relevant and usable research. An important objective of ACBA is to make all of the relevant VU University Amsterdam research visible to industry, and thus to solicit collaboration. The interest is definitely there, and the number of companies working with ACBA in the field of Business Analytics, data science and Big Data is increasing significantly. This trend is not limited to research, but is also in evidence in education. For instance, together with the Tax and Customs Administration, ACBA has developed a ‘Business Analytics & Data Science’ course to allow tax authority staff to translate the latest insights in the field of Business Analytics and big data into their everyday working practice. In view of the high level of interest in this course, it has now been opened to outside parties.

For further inquiries about the Amsterdam Center for Business Analytics (www.acba.nl), please contact Dr. Frans Feldberg, f.feldberg@vu.nl