Author: Benjamin Schaefer

Benjamin supports the CC Ecosystems as a PhD student in the field of blockchain and DLT. After his training at one of the largest regional credit institutions in Germany, Benjamin worked for several years at a renowned management consultancy. There, he dealt with the transformation and digitalization of nationally as well as internationally operating companies from the finance, automotive, logistics and consumer goods sectors. Benjamin is passionate about digital innovations, tennis and road cycling.

Data strategy in connected business models

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From 2019 to 2024, the global volume of digital data generated or replicated annually almost quadrupled – a trend expected to persist (Tenzer, 2024). Technology companies are demonstrating how data is being used to generate revenue that often dwarfs physical assets. Neglecting data can put companies at a significant disad-vantage in the future, leaving them behind data-driven competitors. However, many companies do not utilize the majority of their data and face issues such as data breaches and data silos (DalleMule & Davenport, 2017). The key is to develop and implement data strategies. This blog post presents a categorization for data strategies and their relevance for digital companies and banks in particular.

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Are our jobs at risk?

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The first part of this blog series described different ways in which AI can affect individual professions. To analyze the impact of AI on the Swiss economic sector, a comprehensive qualitative and quantitative study on the exposure of individual professions to AI was conducted using a task-based view. The second part of this article series summarizes the results of this study and presents implications for policy and management.

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Are Our Jobs at Risk?

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As a result of recent developments in the field of AI, the impact of automation on the labor market has begun to be reassessed. Non-routine cognitive or manual jobs, long considered unaffected by previous technologies, are increasingly under threat from self-learning algorithms, leading many economists to argue that this time the impact on the labor market is fundamentally different from other technologies. This blog post describes different ways in which AI can influence the tasks of a profession.

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Research Area Distributed Ledger Technology

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The Competence Center Ecosystems of the Business Engineering Institute St. Gallen develops solutions for relevant problems from practice. In the context of this blog post, the overall research goal of the re-search area Distributed Ledger Technology (DLT) is presented. This research goal is to develop a frame-work that demonstrates and supports the methodological approach of DLT implementations to enable companies to adequately address relevant requirements of the implementation process of a DLT.

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