Is Enterprise Architecture a Science? Part 2

@RSessions was in London this week, so I sat down with him to continue our previous discussion Is Enterprise Architecture a Science?

The first question to address is - which enterprise architecture are we talking about? I think we both agree that there are some activities within the EA world that look more like religion or mediaeval scholastic philosophy than empirically verifiable science.

For example, in his post What's Right with the Zachman Framework, Grant Czerepak states that "the architectural metaphor conceals what the six perspectives are actually about: Entities, Relationships, Attributes, Constraints, Definitions and Manipulations". And referring to the Kipling-Zachman lens, Grant claims that "the interrogatives have a foundation that goes back over three thousand years across every human culture". In a separate post, he says It's not Aristotle's fault, it's your fault. See my post Arguing with Mendeleev (March 2013).

Lots of EA frameworks are essentially abstract classification schemes that start from an abstract ontological argument ("obviously all businesses are made of objects" or "obviously all processes are made up of nouns and verbs") and make assertions that are not amenable to empirical verification.

Roger's SIP methodology is at least based on an empirically testable (and quantified) hypothesis. That a system of systems with such-and-such measurable structural qualities (in terms of Roger's definition of complexity) will have such-and-such predictable costs. So this provides the basis for a scientifically-grounded engineering practice. I think SIP methodology has a reasonable claim to be scientifically grounded: it can be evaluated not just on whether its prescriptions are practical, cost-effective and useful, but also whether its predictions are true. (Incidentally, I think it would be interesting to compare SIP with Christopher Alexander's early book Notes on the Synthesis of Form. This contains detailed and mathematically grounded work on architectural complexity: although the software gurus who developed structured methods in the 1970s were aware of Alexander's book, they left out most of the difficult detail.)


I think there is a further step before EA could ever dream of becoming a fully empirical science, and this would involve large-scale collection and analysis of empirical data, so that there would be a closed loop between theory and practice, connecting structure and value. In order to achieve this, we should need the active participation of some of the more powerful players in the EA game - the large consultancies and above all the key government agencies that govern IT expenditure. (You know who you are.) At the moment, there is little sign that these organizations are seriously interested in any game-changing innovation. (Roger and I should be delighted to talk to representatives of these organizations, please contact us.)