Public defence in Industrial Engineering and Management, M.Sc. (Tech) Jane Seppälä

Title of the thesis: On the Strategic Importance of Building and Using Complex, Algorithmic Systems

Doctoral student: Jane Seppälä
Opponent: Assistant Prof. Stella Pachidi, University of Cambridge, UK
Custos: Prof. Timo Vuori, Aalto University School of Science, Department of Industrial Engineering and Management

Building and using powerful algorithmic systems is a strategic activity

Jane Seppälä from Aalto University is defending one of the first doctoral dissertations on the role of AI in strategic management.

In the vanguard of business strategy and operational efficiency, the deployment of advanced algorithmic systems, such as cutting-edge AI technologies, marks a paradigm shift in the realm of organizational decision-making. Recently, this has been demonstrated by the wide spread of generative AI models, underscoring the pivotal role of algorithms in translating organizational blueprints into action. This research delves into the nexus between complex algorithmic systems and strategy, offering a groundbreaking analysis of their confluence.

Powerful algorithmic systems, much like employees, continuously implement organizational strategy through daily decisions, and building and using these systems should thus be considered a strategic activity. Managers must address this in strategy work, technology development and use, and data practices. 

First, implementing strategic goals into algorithmic systems require making assumptions, which necessitate sufficient strategic and technical understanding. Employees using the system also need to appreciate uncertainties inherent in these systems to avoid losing sight of ambiguity.

Second, the nature of algorithmic, and especially, learning technologies calls to consider their development and use of as a continuous process. These systems are rarely ‘ready’, but their use fuels further development. This should be considered when developing and using such tools.

Finally, as many algorithmic systems require large amounts of high-quality data, effective data practices become crucial for optimal technology utilization. This should be addressed as a part of a wider data-driven culture, and taken into consideration in designing data-producing business processes.

This work builds on three qualitative case studies. The first explores how technological complexity affects strategic decision-making in the context of a merger. The second studies how a large retail organization develops and uses strategically important algorithmic tools, describing how strategy is encoded into the tools. The third analyzes how a start-up organization develops and uses advanced speech recognition technology to provide transcription services, illustrating how the organization maintained and improved system performance as the system's scope was extended.

Keywords: strategy-as-practice, algorithmic systems, technological complexity

Thesis available for public display 10 days prior to the defence at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/ 

Contact information: 

Doctoral theses of the School of Science: https://aaltodoc.aalto.fi/handle/123456789/52