Monday, May 4, 2015

Managing & Coordinating Change with Big Data

Dynamic and swarming processes are a difficult to accept when not knowing how the dynamics will be managed. Enter big data, accessible in a global fashion for processes, process snippets, APIs, embedded code, and swarming agents. Big data acts a bit different in this case as it contains definitions of the controls for all process resources to access (aka Meta Data). These controls might be on a secured file or secured in cloud memory. With the controls accessible to all components, negotiations for the proper resources to swam and behave as desired can be enabled. For emergent processes that are aimed at business differentiation for which there is a level of complexity and heterogeneity, this approach is appealing. The figure below shows where big data access can help manage swarm dynamics and the five key components that will reside in big meta data.


Swarming processes will seek goals that can change dynamically. These goals can be singular in nature or a set of goals that are weighted and managed by analytics, events or shifting balances of goal sets. Sophisticated organizations may have sets jump start goals associated with business scenarios to deal with black swans.


When we don't want processes or swarming processes to violate certain boundaries, rules or policies, constraints can be established and shared. If process components access these constraints, they can avoid violations


There are so many algorithms and combinations/sequences of algorithms, that the algorithms to select and leverage need to be cataloged and associated with processes and portions of process.


Dynamic and swarming processes can behave differently in different contexts. Like a car that can convert to a boat, the moving parts behave differently in different contexts


Patterns of interest that are known ahead of time can be cataloged and stored, Also triggers of interest can be noted for emerging patterns that might be of interest may also be stored. 

Net; Net: 

Swarming resources can be guided and controlled by big meta data that allows process managers and participants to trust these resources and combinations of resources to create desired results without violating governance policies and rules. 

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