Task Architecture and Learning from Coarse Performance

Ekaterina Korotkova and Georgy Lukyanov
Additional contact information
Ekaterina Korotkova: HSE - Vysšaja škola èkonomiki = National Research University Higher School of Economics [Moscow]
Georgy Lukyanov: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

Working Papers from HAL

Abstract: Organizations often learn about competence only from project-level success or failure, even when a project contains several complementary tasks. We compare task architectures by the Blackwell order. An expert of unknown fixed competence can perform all tasks in one bundled project, one task in a project completed by an outside technology, or the same number of tasks across separate projects. Bundling dominates a single narrow assignment below an outside-reliability threshold and is otherwise incomparable with it. Holding the expert's workload fixed strictly lowers this threshold but does not overturn the result: bundling still dominates when the outside technology is sufficiently unreliable, separate projects dominate only when that technology is perfect, and the experiments are otherwise incomparable. We derive the thresholds for any number of tasks and show that the fixed-workload threshold decreases to zero as task scope grows. Explicit posterior-variance formulas measure the cost of coarse aggregation for particular decisions. Finally, in the two-task case, occasional stage-level audits expand the bundling-dominance region according to an exact frontier.

Keywords: task assignment; coarse information; competence; Blackwell order; auditing (search for similar items in EconPapers)
Date: 2026-10
Note: View the original document on HAL open archive server: https://hal.science/hal-05805816v1
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hal.science/hal-05805816v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-05805816

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().