Benjamin Mosig

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Ensuring adequate information provision continues to be a key challenge of corporate decision making and the usage of business intelligence systems. As a matter of fact, the situation becomes increasingly paradox: Whereas decision makers struggle to specify their information requirements and spend much time on obtaining the information they believe to(More)
While it is common practice to use value based decision models for decisions whether to invest in certain projects or not, there is scarce value based decision support for the selection of the most promising project management methodology to be applied in a specific Business Intelligence project. Addressing the lack of a formal yet practical decision model,(More)
Lacking a formal yet practical decision model, nowadays decision makers mostly follow corporate guidelines or their intuition when it comes to the decision between agile and plan-driven project management in Business Intelligence projects. As one size does not fit all, using management methods hyped by temporary fashion or other management methods not(More)
Project risk management has been proposed as an important topic to prevent the failure of large IT projects. But while literature intensively deals with the risk management process, surprisingly little effort has been put into “the last mile”, namely the precise, concise, and unambiguous communication of risks to decision makers. Popular misinterpretations(More)
In dynamic business contexts where knowledge is continually evolving and thus critical for better organizational performance, not only knowledge re-use but also knowledge re-creation becomes more and more important. One of these contexts is the use of non-renewable resources in innovative hightech products. Since media recently spread – often contradictory(More)
Despite valuable related work, identifying relevant information requirements of decision makers is still a key issue in developing analytical information systems. Since measures build a major basis for managerial decision making, discovering the objectively most important measures is crucial to reduce information overload and improve decision quality.(More)
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