Workspace goals--and targets

We define a task as wealth-creation by a set of collaborators a client doesn't own or control, adding resources to a place (.e.g., US County) a client selects, for a share of income (TRoI).

Our matched modeling for causal inference assesses the place of interest to a client relative to others with similar attributes, how that target group differs from a control group in attributes, and how the client's specific target is the best use of planned resources for creating wealth among stakeholders participating in a workspace.

Having clarified Where (and When) a client aims to allocate resources, the task becomes explaining Who & What more is required and How & Why those invited to participate are preferred collaborators. Since they will have other options for solicited resources, this stage of the task entails Changing Minds.

Finding matches

Mainstream economics is designed to validate the Bretton Woods' model where central authorities, national governments and corporations, are the only real decision-makers. OconEco views nations as agglomerations of places with own sources and uses of resources. Depending on causal inferences behind a task, some places will be better matches than others. M-LA filters them first by a dozen core sustainability indicators for  a global set of administrative units a level or two below nations, depending on population. Of 2000 higher level units, 300 have population about as high as the median nation so they are taken to the next administrative level. Exceptionally, all US Counties are detailed not only by core indicators but by about  100 indicators; including our detailed estimates of Gross Territorial Product (GTP) and Wealth, broadly defined.

Key M-LA indicators for US Counties are recast as M-LA Quintiles to inform the design stage of matched models of causal inferences. This puts Counties comprising about a fifth of the US population in each a five ordinally ranked groups, As explained here, matched modeling involves defining a target group of  "nearest neighbors", in more than a geographic dimension; and a control group of other Counties. The causal inference and hence composition of target and control group varies with each Task.

We expect to match our US County indicator set for EU nations in 2020; and other nations as and where clients request.

Changing minds

In our experience, workspace decisions are reached by consensus on verbal models. That entails exchanges of views about 'the facts' with  quantification as a means to that end. Theodore M. Porter argues, in Trust in Numbers, the alternative "technology of trust" is authority.

OconEco uses IT to create a blend or third technology of trust: weight of discussion or trust in process. Its common form is crowd-sourcing or online voting, with problems it entails. Our Procedures promote and track consensus among workspace participants about aspects of a task the collective trusts to external authority, which are trusted to number-oriented evidence and models, and which are trusted to the collective--subject to an agreed feedback procedure in due course. 

Our version of the Dashboard of Sustainability collects and aggregates participants' Value Signals recognize and value as wealth-creating attributes of the defined task. Participants send value signals about "the facts" but also about each other's perceptions of information in the workspace. That includes stakeholder assessments of how to match places, in terms of target and control group attributes. 

Done right, trust in process spills over between related tasks. This is clear in repeated games, where players (stakeholders) and pay-offs (assignment of FRoI) are unchanged. In our experience, players and pay-offs evolve, giving workspaces a whiff of Calvinball. This lets a specific task morph into a set of nested workspaces; with sibling, parent, and child tasks. This requires Procedures that also evolve.