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Do Borders and Boundaries Model Success Frames?


I’d like to put some ideas out there.  Then let’s see what folks would like to say.  Here we go…

Firms, agencies, non-profits, cooperatives, and self-employment interest clusters are places in which we work, explore, and deliver value.  In looking at recursive flows, combinations, and re-combinations leading to value creation, Stephen Wolfram’s work with cellular automata is intriguing, self-promoting, serious, and worth pursuing as we look at the idea of applying systemic frameworks to wicked problem topics such as healthcare or sustainable regional economics, where simple rules can generate complex structures and behaviors.

Regarding automata, let’s observe that boundary interactions can be defined across sets of objects to generate organized or chaotic patterns, depending on interaction rules and object geometries, i.e., the space in which the objects reside.  This reminds me of the framing applied in 2008 to border issues for two situations – in one case a town, and in the other case a multi-town area.  Each case had economic development challenges due to being either abutted or impacted by large neighbors within an overall multi-centric metro area.  Both cases shared the existence of borders as a critical factor – the town had to figure our how to work successfully with defined neighbors, and the multi-town area had to settle the basic issue of defining its border in the first instance.

More generally, it seems reasonable to suggest that boundary statements and cross-boundary interactions may be a basis from which to infer replicable (or even fractal) conceptual frames for a range of issues that manifest as border issues.  Examples might include abutting (or at least interacting) cities, regions, states, and countries.  Other examples could include intra-alliance stress lines between and among firms, politicians, or political territories aligning certain respective assets, as well as sets of inter-alliance stress lines running between and among sets of intra-alliance borders.

Think also of regional versus global trade alliances, or of coopetition across firms in R&D alliances or industry standards setting, or of cross-links connecting firms domiciled in different countries which themselves belong to multiple (and possibly conflicting) trade and defense alliances.  You see wheels within wheels, with shifting transmission belts of varying strength and durability connecting moving parts in changeable arrays.

This topic of borders, objects, and its many possible rules seems to connect with theories of behavior, including economics, insect colonies, and nervous systems as noted above regarding cellular automata.

Going a step further, does this thinking about borders, objects, and their rules have any utility in designing an approach to agent-based modeling–including economic systems and neurologically-based systems?  To the extent economics reflects neurologically-bounded behavior, is it reasonable to ask if both economic and neurological systems might turn out to be different facets of an overlapping modeling methodology?  At least one site seems to invite an overlap as it examines agent-based computational economics (ACE), although it’s not clear if that was intended by the site’s author.

These questions caused a friend of mine to write that automata “might not fit the culture” of a high-end precision manufacturing firm he knew well.  He also asked “whether a link could be established between codes (macro and micro interfaces) and parallel worlds (Hugh Everett).”  His citing Hugh Everett brought the decoherence process into the frame.

The decoherence process accounts for our perceiving a direct linear macro world within a micro universe that analytically can be inferred to have quantum characteristics and non-linear discontinuities.  In a world where the cellular automata discussed above operate within a decoherence framework, I’m thinking it’s the basic discontinuities inherent in boundaries that make boundary scenarios so powerfully interesting, be they geo-political structures on the ground, or policy-oriented analytics and polemics in entity course-setting and economic development, or regarding physics and biology–the framing is open-ended.

At a more operational level, I’m suggesting automata or agent modeling have practical utility as well as elegance to offer to business planning, technology, siting, logistics, strategy, and operations.  For example, it would seem there’s a direct relevance to inferring information on the direction(s) of advanced manufacturing evolution, given its path to date among forward industrial sector participants operating in their different ways to apply different physical, cultural, and knowledge assets in local, regional, national, and global markets within and across multiple economic and political alliances and borders.

Following this line of thought, it’s likely that firms demonstrating long-term success are grounded in the particular in order to work each day’s issues.  But in addition, when it comes to unbundling the elements and context making up future direction, it’s also likely that such firms recognize the highly practical value in assessing how emerging threads may try both to come together and pull apart, thereby affecting the wisdom and success of entity planning.

In effect, it would not be surprising that, if a viable firm or agency were to disassemble its information gathering and assessment process for connecting strategic and operational planning, there would be an important implied step.  This implied step is to manage practical decoherence in order to see concrete likelihoods (tangible probabilities) that could be derived from actions that are nested in a mass of events (quanta) ranging from possible to probable across some integration that yields a likely path forward from a set of strategic alternatives.

If the decoherence framework can be identified and bottled for given scenarios, there might be growth or survival benefits to a firm, or mission benefits to an agency or alliance.  Results include being able to model more fully specified environments, to see more clearly and act more effectively, versus simply projecting past paths forward as linear or nonlinear future possibilities.  The idea is deliberately to be alert to a range of forward boundary discontinuities within future possibilities, and to be more flexible about handling or leveraging them.

OK, clearly this took way to much ink.  But it’s always a pleasure to seek to unbundle things that may look straightforward, but have embedded complexity, especially if there’s a way to maintain connection (keep our balance) across alternative frames in our hourly-daily world.


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