Driving Enterprise Architecture (EA) With BPM - Part I

Before we can even begin to discuss the why and how to drive Enterprise Architecture (EA) with BPM (Business Process Management), we need to first define what EA is and how it is useful for an organization.
In short, EA is a conceptual blueprint describing the structure and operations of an organization. Elaborating on this slightly more, this conceptual blueprint describes how various enterprise components, be it people, process, data, or technology are organized logically and physically throughout the organization and how they are inter-related, for example, how a person is involved in certain tasks in a process or how certain technologies are being utilized when carrying out a certain task, et cetera.
There are a lot of frameworks and methodologies supporting EA to provide a standard for the classification and taxonomy of people, processes, and technologies. Amongst the most popular are the Zachman framework, FEAF (Federal Enterprise Architecture Framework), DoDAF (Department of Defence Architecture Framework), and TOGAF (The Open Group Architecture Framework), all of which center on architectural descriptions across people, processes, and technologies. Insofar as provisioning tangible value to an organization apart from being a taxonomy for enterprise artifacts, EA is often geared solely toward justifying IT investments. The strength of EA is the ability to provide an in-depth impact assessment for change, which is usually why most view EA purely from the light of reconciling a system change. However, significant time and effort usually need to invest in order to create the mapping of enterprise artifacts, such as defining which process ties in to which person, which system is used by which process, which person has access to which system, et cetera. Maintaining the currency of these relationships is yet another challenge, without which the architectural blueprint would rapidly descend to becoming a white elephant.
This is where BPM plays the most significant role. Due to the abundance of process monitoring and process mining technologies, the ability to maintain a process framework is usually the most effective and efficient. If we can simplify our taxonomy of EA to people, processes, data, and systems, we find that almost all of this information can be quickly retrieved if we can monitor or mine our daily processes.
Simply put, BPM describes each task by defining the action, the actor, the input information required, the output to be generated along with the medium or system upon which the action is performed. This is the value that any process monitoring or process mining tool adds simply because they can gather and record these information sets for each transaction made in real-time. Under the granularity at which the process information is being captured, BPM can act as the natural stepping stone towards EA since in essence, to build up the architectural blueprint of any organization simply means collating the granular details of each transaction to establish the inter-dependencies and thereto the relationships between people, process, data and systems (i.e. the bedrock to any EA framework).
More importantly, because the effort to configure a process monitoring or process mining tool is usually one-off, the future maintenance of the monitoring or mining system would be greatly reduced, directly implying that if the architectural blueprint is a derivative of BPM, it too will be automatically maintained and updated in a timely and accurate fashion. This transforms EA from being just a snapshot of the enterprise’s architectural framework to becoming a living blueprint representative of the actual activities being performed at any moment over the lifecycle of the organization. This transition from static to transformative allows EA practitioners and consumers alike to improve the reliability of their analysis and assessments of any change proposed.
That being said, it is important to note here that process monitoring and mining prescribed by BPM are most effective for people, processes, data, and systems. Other artifacts such as strategy and vision tie-ins along with manual taskings where the medium of data exchange is through physical manual documents or interactions are still not mineable so these gaps would still need to be mitigated by specifying and maintaining the relationships manually. Nonetheless, with the continued push towards digitalization of operations, manual activities and actions would soon become a thing of the past and increasing the value of process monitoring and mining as the go-to solution toward a sustainable EA blueprint.
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