Enterprise Interoperability (EI) is a term introduced to describe a field of activity aiming at improving the way with which enterprises internally operate, interoperate with each other, and with other organisations. Information and Communications Technologies (ICT) represent an important enabler of EI.
Today, EI is becoming a strategic feature for building the future business fabric of all innovation ecosystems. As such, interoperability is no longer just about basic interconnectivity and interoperability at the level of technology, or just about information exchange between two entities but it is becoming closely related with the dynamics nature of future business needs, at the level of both the single enterprise and the ecosystems of enterprises. As a matter of fact there are several technology-based solutions that claim to support interoperability for enterprises, with several commercial solutions. Nevertheless innovative approaches are needed to make EI combining both technology and business to catalyze and sustain new models and value networks. Enterprises, both big and small, should be able to do their business seamlessly, to adapt dynamically to changes in the environment and to exploit new emerging opportunities rapidly. This can be achieved by harnessing the full potential of ICT services, which should become an invisible part of business ecosystems.
Brain, like an ecosystem, is highly complex, non-linear, and self-organizing: it is the most beautiful and (probably) effective architecture invented by Nature. Understanding its functioning is one of the grand challenges of Science: many methods have been applied to analyze and study brain structure and functions. Interest is clearly motivated by the fact that the some general principles of brain functioning seem to govern also other complex networks, including social, biological and communications networks.
As such, I believe it would be interesting investigating also the possibility to exploit some of the principles governing brain for enterprise self-organization and eventually to enable EI.
As a matter of fact, ICT for Enterprise is already beginning to borrow some inspiration from biological models: model of an organisation can be seen as a complex ecosystem, rather than a rigid hierarchical structure, disconnected from its environment.
The use of bio-mimetic interaction and communication primitives and algorithms, neutral networks, genetic computation are becoming more and more popular. Moreover, we see that networks are evolving towards pervasive environments of link, processing and storage resources and services. It is also known that virtualization is enabling multiple logical networks to co-exist on top of a same physical infrastructure: on one side this will offer new business opportunities but on the other hand it will increase management tasks. Indeed, understanding the brain would mean taking inspiration for designing future network from the most efficient networking and processing paradigms in Nature; for example autonomics, self-organization, are being studied, developed and assessed. Think about open worldwide infrastructures creating a new fabric for EI based on these principles.
On the other hand, enterprise management modelling towards an efficient, self-regulating, self-organising, self-evolving framework is still in its infancy. It should be noted that this approach is very critical for enterprise sustainability in a highly dynamic and unpredictable socio-economic environment.
Adopting this metaphor, Enterprise should be capable of monitoring itself in relation to its internal functions and to the external environment; assessing its performance against its predictions and requirements. Real-time efficient feedback mechanisms should improve performance and productivity by self-optimising its functions and self-correcting its (internal and external) actions. All of this constantly built on a shared knowledge.
Let’s consider for example “Theory of mind”: this theory concerns the human capability to explain and predict other people’s behaviour by attributing to them certain mental states (see my previous post). Actually the effectiveness of an animal’s relationships with its key coalition/competitor partners is a function in part of its ability to integrate them into its mental social world (so it is a cognitive problem) and the time it can afford to invest in grouping with these individuals (which is an ecological problem).
Another interesting example is the application of the free energy principle to brain functioning (see my previous post). The free-energy principle says that any self-organizing system that is at equilibrium with its environment must minimize its free energy. Brain would be like an inference machine that actively predicts and explains its sensations; furthermore it continuously tries to optimize probabilistic representations of what caused its sensory input. Then it is easy to show that value is inversely proportional to surprise, in the sense that the probability of a phenotype being in a particular state increases with the value of that state. Acting to optimize value and perception are two aspects of the same principle; namely the minimization of a quantity (free energy) that bounds the probability of sensory input, given a particular agent or phenotype.
Indeed, as Roberto suggested in a previous comment, it would be fascinating designing Enterprises’ genomes and let the interplay of their phenotypes in the ever growing complexity of the EI determine their success in terms of biz and therefore their overall evolution.