Many organizations apply EA as part of their IT management and planning activities. From their perspective, it would seem that EA should play an important role in strategic planning, alignment and prioritization. They might see that right decisions means decision driven or guided by EA, and that right results mean using EA to assure that projects do improve IT’s bottom line impact (Benson, Bugnitz & Walton 2004). Today we know the four top EA frameworks, which are often used in preparing the EA. The four top EA frameworks are the Zachman, Gartner, TOGAF and FEA. But in reality we have to be sure whether the four top EA frameworks can be directly adopted into organizations (Session 2007). To answer these questions, we conducted a study of the basic functions and staging in the development of EA in order to obtain certainty on the indicators and requirements in main components of EA methodology development.
We divide the research stage into 5 phases, where each phase will contribute in the form of research methods that will produce main components of indicators and requirements in EA methodology development. Our main research focus is as follows; find out the basic functions of an EA by using theoretical perspectives; find out what stage in EA development; find out the main components for the EA methodology development; perform gap analysis on EA methodology; find out the IT values in the EA methodology development; obtain the indicators and requirements in main components of EA methodology development. In this study we will use qualitative methods with a strategy of inquiry using grounded theory (Creswell 2007; Blessing & Chakrabarti 2009; Oates 2007). This process involves using multiple stages of data collection and refinements and finding interrelationship of categories of information. Two primary characteristics of this method are the constant comparison of data with emerging categories and theoretical sampling of different perspective to maximize the similarities and the differences of information (Creswell 2007).
Overview of the “strategy of inquiry” by using grounded theory in qualitative research methods will have a flow as follows:
Characteristics of Qualitative Methods
In this study we will use qualitative methods with a strategy of inquiry using grounded theory, with the characteristics of qualitative methods as follows:
- Fundamentally interpretive; this means that this research will make an interpretation of the data. This includes developing a description of theory or best practice, analyzing data for themes or categories, and finally making an interpretation or drawing conclusions about its meaning, stating the lessons learned, and offering further questions to be asked. It also means that this research filters the data through a researcher lens that is situated in a specific ontology and epistemology moment; one cannot escape the personal interpretation brought to qualitative data analysis (Creswell 2007; Blessing & Chakrabarti 2009; Oates 2007).
- Complex reasoning; this means that this research is multi-faceted, iterative, and simultaneous. Although reasoning is largely inductive, both inductive and deductive processes are at work. The thinking process is also iterative, with a cycling back and forth room data collection and analysis to problem reformulation and back. Added to this are the simultaneous activities of collection, analyzing, and writing up data (Creswell 2007; Blessing & Chakrabarti 2009; Oates 2007).
Data Collections Type
Data collections type in this research will use type of documents (Creswell 2007; Blessing & Chakrabarti 2009; Oates 2007), this document will base on:
- Expert Judgments; Expertise in EA, Book Author (theoretical perspective), Professional Experience and International Keynote Speaker in EA
- International Journal; Journal of Enterprise Architecture (a publications of the professional association for enterprise architects)
- International Conference Paper; IEEE, ACM, BUSITAL, International Conference on System Science, and ACIS International Conference
- Best Practice; Information Systems Audit and Control Association, IT Governance Institute, and Institute for Enterprise Architecture Development.
Data Analysis and Interpretation Steps
The idea of data analysis and interpretation steps is to blend the steps with the strategy of inquiry. These steps will involve the following of the specific strategy of inquiry. The steps are as follows (Creswell 2007):
- Organize and prepare the EA data’s for analysis, which aims to find out the basic functions of an EA by using theoretical perspectives (Ontology)
- Obtain a general sense of the EA information’s and to reflect on its overall meaning, which aims to find out what stage in EA development and to find out the main components for the EA methodology development (Epistemology).
- Detailed analysis with a coding process through a general sense of the EA information’s and rendering of EA information’s, which aims to perform gap analysis on EA methodology (Axiology).
- Advance how the main components of indicators and requirements in EA methodology development will be represented, which aims to find out the IT values in the EA methodology development (Rhetoric).
- Making an interpretation or meaning of the main components of indicators and requirements in EA methodology development (Methodology).
Edi Triono Nuryatno
Publish in 2011 Society of Interdisciplinary Business Research Conference on Interdisciplinary Business & Economics Research: “Advancing Knowledge from Interdisciplinary Perspectives”, Proceeding available on http://www.ssrn.com/link/2011-SIBR-Conf.html
Publish in Journal Econometrics: Econometric & Statistical Methods – Special Topics e-Journal, Vol. 4, No. 48: July 1, 2011, available onhttp://papers.ssrn.com/sol3/JELJOUR_Results.cfm?form_name=journalBrowse&journal_id=1153610