New Research: When Organizational Representation Meets Operational Reality
A Decision-Bounded Study of Correspondence, Observability, and Transformation Decision Processes
By Emmanuelle DiGallo
Enterprise transformations are often judged by whether they succeed or fail. This research asks a different question: What did organizational decision-makers actually know about the operational reality of a transformation when consequential decisions were being made?
Organizational Representation and Operational Reality in Planned Enterprise Transformation examines the relationship between the operational conditions of transformation and the organizational representations available to decision-makers.
Drawing on four historical enterprise transformation cases, the research explores how operational information is selected, transformed, communicated, and represented; how transformation itself can alter organizational observability; and the conditions under which decision-level representations align with or diverge from the operational conditions they are intended to represent.
The study introduces a decision-bounded approach that separates operational condition, organizational representation, managerial interpretation, consequential decision, and subsequent operational condition, allowing correspondence to be examined without relying on hindsight or assuming that organizational information is either complete or objectively accurate.
Across the cases, the findings suggest that correspondence is not necessarily static. Organizational representations can be corrected, refined, and progressively constructed as operational evidence becomes observable and enters the decision process.
Why This Research Matters
Organizations make consequential transformation decisions based not on operational reality in its entirety, but on the representation of that reality available to decision-makers.
Understanding how those representations are constructed and how they can be corrected when operational evidence changes has implications for transformation leadership, governance, organizational decision-making, information systems, and the design of mechanisms through which organizations observe themselves.
Author: Emmanuelle DiGallo
Publication: Independent Research Thesis
Published: September 4, 2026
DOI: 10.5281/zenodo.22312805
Abstract ID: 7413659/SSRN
Copyright: © 2026 Emmanuelle DiGallo. All rights reserved.
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