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The Knowledge Swarms and Experiential Hives model consists of multiple stakeholders, bonded by a common societal belief and driven by the speed of need to address pressing national infrastructural needs – and even the mythical National Development Plan.

Essentially, the model works as follows:

·       The national urgency for major infrastructural projects (like the 18 Strategic Integrated Projects or SIPs Projects (10)), which will cover multiple national imperatives such as power, water, logistics, science, education, health and many others, cannot continue to be put on hold for political posturing…and other potentially more sinister reasons.

 ·       The only currently effective response capability to this massive Nation Building need will come from the well-established and highly capable Engineering and Construction sector – which includes all the players in the Built Environment space, such as the Building and Projects sectors as well. This sector unfortunately, currently has a more adversarial relationship than a collaborative one with government.

 ·       A Critical Success Factor in the conceptual Knowledge Swarms and Experiential Hives model will be the establishment, development and maintenance of between 100 to 200 Common Knowledge Hives, which contain the most common, predictable and repetitive engineering and construction competencies and capabilities required for the major infrastructural common knowledge Asset Classes (e.g. Dams, Nuclear, Railway, SKA  etc)

 ·       Each Common Knowledge Hive will contain the critical knowledge assets required to safely and cost effectively engineer, procure, construct and manage a specific common knowledge Asset Class, structured in a predictable pattern recognition model (17), which drives and supports optimum learning and memory formation.  (More about this brain sensitising learning and memory enhancing technique in further articles in this series – Ed. Note)

The increasing turbulence and changing nature of work (13) is shifting so rapidly that very soon the long-serving, matrix structures and the command and control like, Baby Boomer-led and managed corporations, will have no option but to transform into highly agile, de-materialised and dis-intermediated entities, optimising ubiquitously connected, cross-functional, expert sharing and quick response work teams – operating with new rules and a survival of the swarm urgency. The ability to rapidly Swarm to meet a need, and then just as effectively de-Swarm as the need abates, and then again re-Swarm, in different formations and configurations, energised and driven by the speed of need, is a critical attribute of Knowledge Swarms and Experiential Hives and the future of the intelligent workplace (14).

Swarms require an activated belief space (15), based on a mutually inclusive drive for both self and societal enhancement (be that survival or enrichment). This underlying philosophical Swarming construct, which will be so critically needed to attract full commitment and engagement by our Nation’s stakeholders, is embodied in the author’s Knowledge Mentoring™ 5C’s Holacratic Contribution Model – what do I know, what do I need and what can I share - with my Colleagues, with my Company, with my Community… for my Country and for my Continent.

 As with all swarms, a quorum sensor needs to manifest, which silently and without explicit rules, dictates the collective knowing, direction, speed and urgency of the swarm (16) – and it is highly likely that the recent and predictably on-going challenges with our power, water and logistics utilities, will act as a sufficient quorum sensor to mobilise an effective step-change in our national belief space. The highly publicised concerns across all political spectrums, is sufficient proof that this critical component of effective swarming is already in place and that a communal quest for more effective, common knowledge sharing, would probably be very well accepted.

 The next step in the Knowledge Swarms and Experiential Hives model, is the establishment of the multi-stakeholder model itself.