Organizational Resilience in the Times of Algorithmic Decision Support

Abstract

This paper examines how the growing integration of algorithmic decision-support systems into core organizational functions as forecasting, workforce scheduling, credit scoring, and pricing, affects an organization's capacity for resilience. Drawing on comparative illustrations from supply chain forecasting, workforce scheduling, and credit underwriting, the paper further argues that sector-wide standardization of algorithmic architectures risks correlating fragility across organizations, echoing concerns from financial stability research. To counteract these tendencies, the paper proposes three deliberate structural interventions: actively rehearsed manual-override capacity, systematic monitoring for distributional drift, and institutionalized diversity of oversight, positioning resilience-preserving redundancy as a necessary long-run investment rather than a short-run inefficiency. The paper is conceptual, synthesizing resilience theory with organizational and information systems literature on algorithmic management, and outlines directions for future empirical testing of the proposed mechanisms and interventions.