Agility is the ability to react quickly and effectively to changes in environments. Taking cue from people, agility is conditioned by the resilience and plasticity of a backbone and the accuracy and reactivity of sensory motor connections.
On that account, the digital transformation of enterprise architectures calls into question the relevance of a flat information layer, and more generally of the traditional distinction between business and IT systems.
VALUE CHAINS & Digital Flows
To begin with connections, the generalization of digital flows is to affect the meaning of value chains, a concept introduced by Porter in 1985 as a way to chart the sequences of activities contributing to the delivery of a valuable product or service to market.
From a digital point of view value chains can be likened to nerves carrying signals between operations and organization; from a business point of view they are meant to track down the path of added value across contributing resources and assets.
But digital transformation and the ensuing pervasiveness of software components in business processes blur the boundaries between primary and supporting activities, calling for a redefinition of the relationships between business processes and supporting systems.
In return, the generalization of homogeneous digital flows within and without enterprises could also support the exchange of combined actual and symbolic contents between business environment and operations; hence the benefits of redefining supporting activities in terms of generic capabilities binding systems to enterprises organization:
- Who could use the systems: interfaces, security, confidentiality, numbers, latency, synchronization, …
- What kind of objects could be managed: storage, volumes, encryption, …
- How activities could be supported: representation, and management of business logic.
- When processes could be executed: events, control, orchestration, choreography…
- Where processes could be executed : locations, assets, communication channels.
The immediate benefit of that shift is to bring transparency to the overlaps between business processes and supporting systems. Concomitantly, it paves the way to a tighter integration of enterprise systems and knowledge architectures.
Information Layer vs Digital Backbone
Using digital flows to anchor business processes to architecture capabilities makes redundant the indiscriminate information layer often introduced between business and applications ones. Instead, a digital backbone can be set across the whole of enterprise architectures, with conceptual, logical, and digital data descriptions aligned respectively with computation independent, platform independent, and platform specific models.
The alignment of architecture layers with differentiated information processing capabilities is to become a critical asset for enterprises immersed in digital environment. To deal with changes and competitors enterprises have to combine long-term objectives relative to their business environment with direct observations from the digital one. That cannot be achieved without a distinctive management of data, information, and knowledge:
- At digital level data inputs from environments are to be sorted out as observations or managed information, the former to be fed into analytic models, recorded, or deleted, the latter used to update business surrogates in line with systems models.
- At business level knowledge is managed with thesauruses and semantic graphs; it is at the source of business models and objectives as well as organization, and consequently of the architecture of information systems; knowledge is also updated through analytic tools.
Enterprise architects could then manage changes with regard to business intelligence (business models and observed and managed data) and existing systems, with ontologies securing the semantic interoperability of the different representations.
- Agile Architectures: Versatility meets Plasticity
- Digital Transformation & Homeostasis
- Entropy & Homeostasis
- Knowledge-based Models Transformation
- Focus: Data vs Information
- Modeling Paradigm
- Views, Models, & Architectures
- Abstraction Based Systems Engineering
- EA & MDA
- EA: The Matter of Layers
- EA: Maps & Territories
- EA: Work Units & Workflows
- Ontologies & Enterprise Architecture
- Ontologies as Productive Assets
- Models Transformation & Agile Development