The potential and utilisation of predictive business analytics
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
Linnanmaa, L2
Topic of the dissertation
The potential and utilisation of predictive business analytics
Doctoral candidate
Master of Business Administration (MBA) Maarit Matkaselkä
Faculty and unit
University of Oulu Graduate School, Oulu Business School, Martti Ahtisaari Institute
Subject of study
Business analytics
Opponent
Professor Nina Helander, Tampere University
Custos
Associate Professor Timo Koivumäki, University of Oulu
The potential and utilisation of predictive business analytics
The purpose of this study is to explore the potential, introduction and implementation of predictive business analytics in management and decision-making. The amount of data is increasing at an accelerating rate, and business analytics provides the means to refine data into knowledge and insights that generate business value. Business environments are also becoming more dynamic and complex, and data can be utilised to create scenarios, detect insights and anomalies, as well as predict and forecast, rather than merely react to what has already happened.
To create an understanding of the research phenomenon, this study relies on the literatures of predictive business analytics, business analytics, dynamic capabilities, analytics-enhanced dynamic capabilities, strategic management and data strategies. These theoretical foundations and key concepts highlight predictive business analytics from different perspectives: potential, capabilities and utilisation. The empirical part of this study has been conducted as a set of qualitative case studies. This study explores the resources and challenges faced when building predictive business analytics capabilities, and discusses the potential, introduction and implementation within wellbeing services.
The findings of the study highlight the potential of predictive business analytics to show trends, find correlations, create scenarios, conduct simulations, forecast the future, predict resources, and analyse markets. In wellbeing services, possibilities can be related to either services, resources and organisation, finding indicators and triggers, or patient care.
To build predictive business analytics capabilities an organisation needs an overall data culture, as well as appropriate skills, tools, and processes. A lack of data culture, data strategy and resources, issues related to data and legislation, as well as organisational change resistance and integration into daily operations are recognised challenges in building these capabilities.
Successful utilisation in wellbeing services includes collaboration involving business, data and technology, as well as between in-house and other partners. It also requires managerial and technical skills, as well as the data-oriented transformation of existing functions and organisational culture.
To create an understanding of the research phenomenon, this study relies on the literatures of predictive business analytics, business analytics, dynamic capabilities, analytics-enhanced dynamic capabilities, strategic management and data strategies. These theoretical foundations and key concepts highlight predictive business analytics from different perspectives: potential, capabilities and utilisation. The empirical part of this study has been conducted as a set of qualitative case studies. This study explores the resources and challenges faced when building predictive business analytics capabilities, and discusses the potential, introduction and implementation within wellbeing services.
The findings of the study highlight the potential of predictive business analytics to show trends, find correlations, create scenarios, conduct simulations, forecast the future, predict resources, and analyse markets. In wellbeing services, possibilities can be related to either services, resources and organisation, finding indicators and triggers, or patient care.
To build predictive business analytics capabilities an organisation needs an overall data culture, as well as appropriate skills, tools, and processes. A lack of data culture, data strategy and resources, issues related to data and legislation, as well as organisational change resistance and integration into daily operations are recognised challenges in building these capabilities.
Successful utilisation in wellbeing services includes collaboration involving business, data and technology, as well as between in-house and other partners. It also requires managerial and technical skills, as well as the data-oriented transformation of existing functions and organisational culture.
Last updated: 30.4.2025