Authors: Sai Venkatesh Balasubramanian
Globalization, international trade and technology development have largely increased the complexity of management of large organizations such as IBM. As IBM faces a major restructuring phase in early 2014, a clear shift of paradigm is essential to frame policies and management decisions more effectively. This is when contemporary management theories such as systems theories and chaos theories lend a helping hand. They provide concepts and visualizations that can be effectively used for the modeling and understanding of the complexity, growth and dynamic evolution of such large organizations. The present project purports to the formulation of an effective analysis methodology based in systems theory and chaos theory that will help the management make effective and informed decisions. As a starting step, the basic concepts of signals and systems are reviewed, and special attention is devoted to special systems such as chaotic systems. Following this, a signals and systems based model of a large organization such as IBM is proposed. This model takes into account the primary source of assets, the primary source of revenue and finance, and the interrelations between them. Using this model as a platform, the formulation of an analysis method is attempted. To this end, a thorough study of the various standards and metrics used in systems theory and chaos theory are considered. Based on this an analysis method is formulated. This analysis method enables analyzing the output signal such as the share revenue data and understanding the patterns and trends occurring therein. The analysis formulation comprises of three categories: 1. Temporal Analysis: Time Series, Phase Portrait and Multiscale Analysis. 2. Spectral Analysis: Magnitude Spectrum, Polar Plot and Spatial Distribution. 3. Nonlinear Analysis: Lyapunov Exponent, Fractal Dimension and Kolmogorov Entropy. To evaluate and validate the analysis methodology formulated, four case studies are considered, These case studies correspond to significant events in the recent policy making history of IBM. The case studies are as follows: 1. Acquisition of Cognos BI in 2007. 2. Announcement of hikes of around 20% in IBM India in 2011. 3. Layoffs and Global Restructuring Program, Q1 2014. 4. Declaration of Dividends, 2013. For each of the above cases, two suitable timeframes are selected: one before the event and one after. For both timeframes, the formulated analysis is conducted. The analysis results are mapped with the decisions and policies in each case, and suitable interpretations are obtained. These interpretations indicate how the share market responded to the decisions and declarations. Based on the analysis formulation and the case studies, the major inferences and the contributions of the analysis to the company management process are enumerated. The project enables the application of the contemporary systems and chaos theory to modeling an organization using the signals and systems approach, and formulation of analysis techniques to identify patterns and market response trends to company decisions and declarations. The minimal requirement of data and tools required for the analysis proposed form the major highlight of the present project. Thus, the present project is a testimony to the phrase “Transformation through Information”.
Comments: 106 Pages.
[v1] 2016-01-12 21:46:39
Unique-IP document downloads: 306 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.