eThesis - School of Business electronic theses

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This study considers the topical subject of big data in the context of Finnish business environment. A need for clarifying the concept of big data is recognized. The first objective of the research is to untangle, introduce and analyse the concept of big data. Also a research gap in the area of big data utilization in Finnish companies is identified. Another objective is to empirically assess the state of big data in Finnish companies and the results that the companies have achieved by utilizing big data.

The research questions draw from the theoretical models of big data maturity and success factors of business intelligence implementations. The research questions include the following:

1. How big data mature are Finnish companies that are utilizing big data? 2. Is the big data maturity model applicable in Finnish business environment and does it succeed in differentiating the companies with different levels of maturity? 3. What kind of external factors and internal competences the companies recognize as defining their big data potential. 4. What are the factors that Finnish companies identify as contributing towards success in big data efforts? 5. Are the identified success factors aligned with the model of Yeoh and Koronios (2010)?

The method of multiple case study is applied in order to answer the research questions. The data consists of ten interviews with experts of large Finnish companies utilizing big data.

In the analysis of the interview data the maturity model is successfully applied in Finnish context. Interviewed companies are mostly on the early stages of big data maturity. However, they are using big data in versatile ways and in many different business functions.

SWOT-analysis is used as a tool to recognize external and internal factors defining the big data potential of the companies. A large share of the companies report access to large amounts of data and strong know-how in the analytics area as their strengths. Identified weaknesses include e.g. lack of organizational agility. Increasing availability of data and improving technological solutions are seen as the most predominant opportunities. Fast pace of change and fierce competition in the area are things that the companies find challenging. Other mentioned treats include crisis with privacy and changing privacy legislation.

Evidence of all other success factors of Yeoh's and Koronios' (2010) model is found in the interview data except the success factors in the technology dimension. This might indicate that the companies do not consider the technological factors as critical as factors related to the process and organization. The data also suggests that the success factor of openness to look for partners and solutions outside the company's own industry should be included in the organizational success factors.