@article{PetruchTammStantchev2012, author = {Petruch, Konstantin and Tamm, Gerrit and Stantchev, Vladimir}, title = {Deriving In-Depth Knowledge from IT-Performance Data Simulations}, series = {International Journal of Knowledge Society Research (IJKSR)}, volume = {3}, journal = {International Journal of Knowledge Society Research (IJKSR)}, number = {2}, pages = {13 -- 29}, year = {2012}, abstract = {Knowledge of behavioral patterns of a system can contribute to an optimized management and governance of the same system, or of similar systems. While human experience often manifests itself as intuition, intuition can be notoriously misleading, particularly in the case of quantitative data and subtle relations between different data sets. This article augments managerial intuition with knowledge derived from a specific byproduct of automated transaction processing performance and log data of the processing software. More specifically, the authors consider data generated by incident management and ticketing systems within IT support departments. The authors' approach utilizes a rigorous analysis methodology based on System Dynamics. This allows for identifying real causalities and hidden dependencies between different datasets. The authors can then use them to derive and assemble knowledge bases for improved management and governance in this context. This approach is able to provide more in depth insights as compared to typical data visualization and dashboard techniques. In the experimental results section, the authors demonstrate the feasibility of the approach. It is applied on real life datasets and log files from an international telecommunication provider and considered different improvements in management and governance that result from it.}, language = {en} } @article{StantchevTammPetruch2012, author = {Stantchev, Vladimir and Tamm, Gerrit and Petruch, Konstantin}, title = {Assessing and governing IT-staff behavior by performance-based simulation}, series = {Computers in Human Behavior}, volume = {29}, journal = {Computers in Human Behavior}, number = {2}, pages = {473 -- 485}, year = {2012}, abstract = {When optimizing IT operations organizations typically aim to optimize resource usage. In general, there are two kinds of IT resources - IT infrastructures and IT staff. An optimized utilization of these resources requires both quantitative and qualitative analysis. While IT infrastructures can offer raw data for such analyses, data about IT staff often requires additional preparation and augmentation. One source for IT staff-related data can be provided by incident management and ticketing systems. While performance data from such systems is often stored in logfiles it is rarely evaluated extensively. In this article we propose the usage of such data sources for IT staff behavior evaluation and also present the relevant augmentation techniques. We claim that our approach is able to provide more in-depth insights as compared to typical data visualization and dashboard techniques. Our modeling methodology is based on the approach of system dynamics. We also provide formal models and simulation results where we demonstrate the feasibility of the approach using real-life logfiles from an international telecommunication provider.}, language = {en} }