The most amazing part of the legacy of IT innovation in 2007 to 2015 is the number of different ways that individuals had to initiate action. The vast expansion of options had an unprecedented reliance on underlying support mechanisms that were heterogeneous, spontaneous, or ungoverned in their availability and presence.

In particular, conventional controls on interaction such as policies (permission) or configurations (structures) faced conditions so diverse or even ephemeral that achieving operational predictability was possible only on fundamentally new terms.

Today and going forward, the new normal environment of operations for users is even more heterogeneous and “open”. Managing production in that environment requires insight into what the environment already wants to support and do systemically, which can then be exploited under management.

The driving metaphors for that environment’s state of affairs are “organic” and “Darwinian”. Native elements coincide, combine, and compete.

As an overall ecosystem, the complex set of relations in this new state pose a big challenge to discovering the regularity of its dynamics — the probabilities showing  a “natural” set of priorities, and the most common attributes of “natural” constructions. Without that information, imposing practical preferences and mitigating risks is far more difficult.

This throws us into a scientific mode of achieving a practical familiarity. The ability to “look into the system” and recognize its behavior is the insight that matters.

In general, we first maintain continuous observations from which events, transactions and outcomes are revealed.

Then we aggressively analyze those observations, to identify any significantly persistent correlations.

Finally, the most useful logical modeling of those correlations will characterize and reveal co-operative agents and brokers in the system.

The Evolution of Insight