‘When hard data is not enough – expert-driven models in strategy work’
‘Data and artificial intelligence are everywhere, but their benefits for long-term strategy work are limited. Imagining unprecedented events and ideating strategic choices requires creative and critical thinking by human experts,’ says Assistant Professor Eeva Vilkkumaa from Aalto University School of Business.‘But could mathematical foresight and strategy models be more than just hard data and optimisation – for example, a way to harness the creativity of a diverse group of experts to support participatory and systematic strategy work?
Eeva Vilkkumaa and her guests at the Better Business – Better Society seminar on Thursday 3 December discuss (in Finnish) how they perceive the role of qualitative analyses, creative methods, mathematical modelling and data analytics to develop in the strategy work of the future.
‘At best, different approaches support each other. Information produced using qualitative and creative methods can be refined into justified recommendations for decisions by means of mathematical modelling. Artificial intelligence and data analytics, on the other hand, make it possible to continuously monitor the operating environment, which enables rapid responses to significant changes.’
Eeva Vilkkumaa works as an assistant professor at the Department of Information and Service Management at the Aalto University School of Business. She leads the Prescriptive analytics for data-informed decision-making project, funded by the Foundation for Economic Education for four years (2019–2022), which develops mathematical decision support models to support scenario-based strategy work and cost-effective allocation of health care resources. Three professors and five doctoral students from the Department of Information and Service Management work in the project.
Better Business — Better Society Seminar Series
The Seminar Series discusses the current and societally important topics at the School of Business. The seminars will be arranged monthly, generally on the first Thursday of the month, excluding holiday seasons.