I have so far encountered two general types of data . . .

Reductive Data

This is data that conforms to prescribed criteria.  I sometimes describe it has the metrics of criteria or measurements of conformity.  For instance, an organization might want to measure something potentially obscure like "efficiency."  It therefore becomes necessary to establish under what conditions or criteria something is efficient.  I describe "sales" as reductive because it literally just tells us about sales either in unitary or dollar terms.  If sales start to decline, we have essentially no information why or how to ameliorate conditions since such details are absent.  The focus is on function, process, and performance - details that have little value when an organization intends to abandon a declining market.  Some forms include orders, sales, and inventory.

Expansive Data

This is data that describes or informs us of phenomena.  I sometimes call it the metrics of phenomena.  There is conveyance of embodiment so often missing from reductive data.  We gain details of the underlying reality behind the management numbers.  For instance, an organization with a large number of disability claims might insulate itself from the reality of workplace conditions - such as employees being stationary and physically inactive for long periods of time.  Aspects of phenomena might include geography (spatial characteristics), scheduling (temporal considerations), and presence (physicality).  The focus is on setting, participation, and consequence - things that give guidance under deterministic conditions.  Some applications might include transit, siting, intelligence, and surveillance.

When something is perceived, it can be interpreted both in reductive and expansive terms.  However, it is important to note the power dynamics.  To identify something as inefficient - to add weight to this label - is to reduce it of attributes and characteristics that might create competing interpretations.  If this occurs on a pathological level, I call it instrumentalism.  From a management standpoint, a business case might be easier to establish if environmental destruction were dismissed as non-substantive.  It might make perfect sense - under an insulated and inebriated paradigm - to exploit uneducated female garment workers and their children in a foreign country to supply us with cheap clothing locally.

The power dynamics are systemically persistent.  The dichotomous metrics of criteria and phenomena affect the use and usefulness of organizational data.  The nature of the data is actually different from a structural standpoint.  There tends to be a fixed and relatively small number of reductive data fields.  Expansive data literally expands (possibly using special software) carrying not just the body of phenomena but the language of meaning that extends from the phenomena.

Any and all sorts of comments are warmly invited.

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Tags: analytics, construction, criteria, disablement, embodiment, epistemology, metrics, ontology, phenomenalism, prescriptive, More…social


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