When infrastructure transition and work practice redesign collide
Bibliographic record
Abstract
Purpose – As management innovations become more complex, infrastructure needs to change in order to accommodate new work practices. Different challenges are associated with work practice redesign and infrastructure change however; combining these presents a dual challenge and additional challenges associated with this interaction. The purpose of this paper is to ask: what are the challenges which arise from work practice redesign, infrastructure change and simultaneously attempting both in a single transformation? Design/methodology/approach – The authors present a longitudinal study of three hospitals in three different countries (UK, USA and Canada) transforming both their infrastructure and work practices. Data consists of 155 ethnographic interviews complemented by 205 documents and 36 hours of observations collected over two phases for each case study. Findings – This paper identifies that work practice redesign challenges the cognitive load of organizational members whilst infrastructure change challenges the project management and structure of the organization. Simultaneous transformation represents a disconnect between the two aspects of change resulting in a failure to understand the relationship between work and design. Practical implications – These challenges suggest that organizations need to make a distinction between the two aspects of transformation and understand the unique tensions of simultaneously tackling these dual challenges. They must ensure that they have adequate skills and resources with which to build this distinction into their change planning. Originality/value – This paper unpacks two different aspects of complex change and considers the neglected challenges associated with modern change management objectives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.109 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.021 | 0.023 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".