A Visualization Approach for Reducing the Perceived Complexity of COBIT 5 Yannick Bartens1, Steven de Haes2, Linda Eggert3, Leonard Heilig1, Kim Maes2, Frederik Schulte1, and Stefan Voß1 1
Institute of Information Systems, University of Hamburg, Hamburg, Germany {yannick.bartens,leonard.heilig, frederik.schulte,stefan.voss}@uni-hamburg.de 2 Information Technology Alignment and Governance Research Institute, University of Antwerp – Antwerp Management School, Antwerp, Belgium {steven.dehaes,kim.maes}@uantwerpen.be 3 Institute for Risk and Insurance, University of Hamburg, Hamburg, Germany
[email protected]
Abstract. COBIT 5 is positioned in the market as a de-facto standard for enterprise governance of IT. Relevant literature and management experience, however, indicate that the adoption of the framework is challenging due to its perceived complexity. In this paper we present a software prototype aiming to promote the understanding of COBIT 5, its components and their relationships by means of information visualization, thus facilitating its usage and adoption in scientific and practical context. The current state of evaluating the prototype is outlined. Keywords: COBIT 5, IT governance, information visualization, prototype.
1
Introduction
IT governance, recently rebranded as “enterprise governance of information technology” (EGIT), can be considered as a key concept in pursuing the creation of business value through suitable application of information technology (IT) [1]. The adoption of COBIT 5 has been ascertained as a measure for the application of EGIT in practical environments [2]. However, this adoption in organizations is widely described as challenging due to the high perceived complexity of COBIT 5 [2, 3]. In contrast to objectively measureable complexity, perceived complexity results from the distinctions made by a subjective observer [4]. Moreover, the academic knowledge base to analyze and leverage COBIT 5 from a research perspective is limited and needs to be extended to facilitate adoption in academia [2]. In this paper we present a prototype leveraging the utilization of COBIT 5 by means of information visualization. To address these problem statements, and building on the work of Ware [5] and Keller & Tergan [6], we present a software prototype as an information visualization tool. Different from the current textual representation of COBIT 5, visual information depicts a more comprehensible way of representation, assisting in “coping M.C. Tremblay et al. (Eds.): DESRIST 2014, LNCS 8463, pp. 403–407, 2014. © Springer International Publishing Switzerland 2014
404
Y. Bartens et al.
with subject-matter complexity and ill-structuredness” [6], making knowledge and information explicit and allowing to generate, retrieve, elicit, (re-)structure, evaluate, locate and access information. Hence, our goal is to derive design requirements on information visualization [6] in order to develop an artifact addressing the above mentioned problems. The software prototype represents an artifact in the sense of design science research [7] aiming to be valuable for application in practice and science, especially in supporting the understanding of the components of COBIT 5 and their relationships and in building an instrument usable for research. Our research applies the methodology outlined by Gregor and Hevner [8], albeit due to space limitations only an abbreviated synopsis of the conducted literature review can be provided.
2
Design of the Artifact
We address insight generation through the adaption of certain design principles [9], which are outlined in Table 1. They are to be implemented by the prototype together with other more generic requirements for information visualization. Table 1. Aggregated design requirements as derived from literature Design Requirements
Sources
D.1: Provide Overview
[9–12]
The provision of an abstracted overview helps understanding the overall picture of a dataset and promotes further exploration. In addition, it allows the differentiation of known and unknown information, therefore enabling the exploration and generation of new knowledge. D.2: Adjust
[9, 11, 12]
Adjustment of the level of abstraction and/or range of selection serves the purpose of sensemaking and test of hypothesis. This way of filtering helps to explore a large amount of data and enables the selection of demand-specific information. Reducing the amount of the search and working memory load needing more detailed facts can be extracted. D.3: Detect Pattern
[9, 10]
Pattern detection refers to accessing specific distributions, trends, frequencies or structures within a dataset. This also enables both finding demand-specific information and the discovery of new knowledge as well as the test of hypothesis and development of new questions. D.4: Match Mental Model
[9, 11]
Through visualization the gap between data and a user’s mental model of it can be decreased, thus reducing the cognitive load in understanding, increasing perceived familiarity and linkage of information to real-world knowledge. A visual representation transforms information into a physical space for effective exploration.
Resembling a specific instantiation of our artifact, the COBIT 5 Visualization Prototype is developed on a strict transformation of the COBIT 5 enabling processes
A Visualization Approach for Reducing the Perceived Complexity of COBIT 5
405
publication [13], specifically designed to address the elicited requirements. The used technologies include HTML5, a tailored JavaScript (GoJS) library, and PHP5/MySQL for the dynamic components. The visualization is generated via GoJS with the assistance of an HTML5 canvas [14]. By this, we reduce barriers such as location dependencies for accessibility, plugin usage, and high resource requirements. Thus, the platform independent usage on mobile devices like smartphones and tablets is possible. Fig. 1 illustrates the graphical user interface (D.1, D.3, D.4) with an already applied filter for demand-specific display (D.2, D.3). Our prototype visualizes the practices of the COBIT 5 process reference model in a graph-like structure, projecting practices as vertices and their interfaces as edges. The in- and outputs between those interfaces are presented as textual descriptions, similar to edge weights in graph theory. Functionalities of our instantiation include a recurring layout of the visualization (D.1, D.3, D.4) as well as navigation functions like zoom, pan and move (D.1, D.2, D.3). The practices are clustered in their respective domains and color-coded accordingly (D.1, D.3, D.4). When selecting one or more practices their in- and outputs as well as the connected first-degree vertices will be highlighted (D.2, D.3, D.4). The data of the selected elements will be given to the user in a table to the right hand side (D.3, D.4) in order to ensure the provision of the completeness of data (D.2 and D.3). In addition filters for selection and display limitation on processes, domains and superior goals levels are available, in future versions complemented by a search function for the aforementioned options plus the in- and outputs (D.1, D.2, D.3).
Fig. 1. Graphical representation of the prototype
3
Significance to Research and Practice
COBIT 5 and its associated suite of products is a large, multifaceted and complex set of guidance. The framework is systematically designed to encompass the complete
406
Y. Bartens et al.
investment life-cycle, with both governance and management aspects. The perceived complexity gives rise to the need for research on COBIT 5 as an artifact. As indicated by De Haes et al. [2], there is a need to investigate the design and internal consistency of COBIT 5, or lack thereof. The COBIT 5 Visualization Prototype developed in the context of this paper can be leveraged in more analytical research programs to check for internal consistency and embedded design patterns in COBIT 5. Furthermore, the prototype is estimated to leverage the adoption of COBIT 5 in practice. Specifically, we seek to address the difficulty of the implementation and transformation of existing environments, which already have implemented COBIT 5. The potential of our idea and its implementation was approved by experienced network members, from academia and practice, of the institutions involved in this paper. It has to be noted that comparable approaches on visualization of the COBIT 5 knowledge base have not been made yet. A reconfirmation was obtained by direct correspondence with ISACA. In conclusion, our artifact and its instantiation can be truly considered a novelty and highly innovative from a practical point of view.
4
Evaluation of the Artifact
As envisaged in the design science research paradigm, the evaluation of an artifact is divided into qualitative and quantitative phases. To align with this approach our artifact will undergo two separate but consecutive evaluation rounds (e.g., as in [15]): In a first step multiple explorative focus groups [16] are used to evaluate the perceived utility and actual usability of the developed prototype as well as the collection of feedback on possible tasks for the upcoming experimental studies. The conduction of the explorative focus groups is currently in progress. Secondly, laboratory experiments will be carried out to quantitatively measure the effectiveness of our prototype. The research goal is to validate if the usage of the proposed prototype will reduce the perceived complexity of COBIT 5. For this purpose, we derived a testable set of hypotheses from the pursued goals on improving COBIT 5 with our prototype. The experiment investigates if the application of a visualization tool can reduce the time needed for retrieval of information. In addition, the quality and quantity of retrieved information is assessed. The shape of the provided data out of which demand-specific information is to be generated represents the independent variable. We differentiate into three different configurations; the control group will be provided the COBIT 5 framework in an unaltered version as currently available, while another group will use a version of our prototype with a full set of functionalities. The remaining group will be provided with a modified version, only featuring the functionalities based on the design requirements D.1, D.3 and D.4. We seek to consult the procedures outlined by North [17] and Carpendale [18] for the advanced measurement of the dependent variables. Acknowledgments. The presented prototype is not yet available for distribution as the content of the referenced COBIT 5 knowledge base is copyrighted material of ISACA and was used for demonstration and proof of concept purposes only.
A Visualization Approach for Reducing the Perceived Complexity of COBIT 5
407
References 1. De Haes, S., Van Grembergen, W.: Moving From IT Governance to Enterprise Governance of IT. ISACA Journal 3, 21 (2009) 2. De Haes, S., Van Grembergen, W., Debreceny, R.S.: COBIT 5 and Enterprise Governance of Information Technology: Building Blocks and Research Opportunities. Journal of Information Systems 27, 307–324 (2013) 3. Williams, P.: A Helping Hand with IT Governance, http://www.computerweekly.com/opinion/ A-helping-hand-with-IT-governance (2006) (last access February 27, 2014) 4. Schlindwein, S.L., Ison, R.: Human Knowing and Perceived Complexity: Implications for Systems Practice. Emergence: Complexity & Organization 6(3), 27–32 (2004) 5. Ware, C.: Information Visualization: Perception for Design. Elsevier, Amsterdam (2012) 6. Keller, T., Tergan, S.-O.: Visualizing Knowledge and Information: An Introduction. In: Tergan, S.-O., Keller, T. (eds.) Knowledge and Information Visualization. LNCS, vol. 3426, pp. 1–23. Springer, Heidelberg (2005) 7. Hevner, A.R., March, S.T., Park, J., Ram, S.: Design Science in Information Systems Research. MIS Quarterly 28(1), 75–105 (2004) 8. Gregor, S., Hevner, A.R.: Positioning and Presenting Design Science Research for Maximum Impact. MIS Quarterly 37(2), 337–355 (2013) 9. Yi, J.S., Kang, Y., Stasko, J.T., Jacko, J.A.: Understanding and Characterizing Insights: How Do People Gain Insights Using Information Visualization? In: Proceedings of the BELIV 2008, pp. 4:1–4:6. ACM, New York (2008) 10. Dang, Y., Zhang, Y., Hu, P.J.-H., Brown, S.A., Chen, H.: Knowledge Mapping for Rapidly Evolving Domains: A Design Science Approach. Decision Support Systems 50, 415–427 (2011) 11. Börner, K., Chen, C., Boyack, K.W.: Visualizing knowledge domains. Annual Review of Information Science and Technology 37(1), 179–255 (2003) 12. Shneiderman, B.: The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. In: Proceedings of the 1996 IEEE Symposium on Visual Languages, pp. 336–343 (1996) 13. ISACA (ed.): COBIT 5: Enabling processes. ISACA, Rolling Meadows (2012) 14. Grady, M.: Functional Programming Using JavaScript and the HTML5 Canvas Element. Journal of Computing Sciences in Colleges 26(2), 97–105 (2010) 15. Müller, O., Debortoli, S., Seidel, S.: MUSE: Implementation of a Design Theory for Systems that Support Convergent and Divergent Thinking. In: vom Brocke, J., Hekkala, R., Ram, S., Rossi, M. (eds.) Design Science at the Intersection of Physical and Virtual Design, pp. 438–445. Springer, Heidelberg (2013) 16. Tremblay, M.C., Hevner, A.R., Berndt, D.J.: Focus Groups for Artifact Refinement and Evaluation in Design Research. Communications of the Association for Information Systems 26, 599–618 (2010) 17. North, C.: Toward measuring Visualization Insight. IEEE Computer Graphics and Applications 26(3), 6–9 (2006) 18. Carpendale, S.: Evaluating Information Visualizations. In: Kerren, A., Stasko, J.T., Fekete, J.-D., North, C. (eds.) Information Visualization. LNCS, vol. 4950, pp. 19–45. Springer, Heidelberg (2008)
