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Exploring organizational learning and experimental logistics development at the global fashion retailer H&M
Author(s) -
Sandberg Erik,
Abrahamsson Mats
Publication year - 2021
Publication title -
global business and organizational excellence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.227
H-Index - 16
eISSN - 1932-2062
pISSN - 1932-2054
DOI - 10.1002/joe.22143
Subject(s) - process (computing) , business , process management , test (biology) , key (lock) , development (topology) , knowledge management , computer science , operations management , marketing , economics , paleontology , mathematical analysis , computer security , mathematics , biology , operating system
Abstract A logistics learning capability based on an experimental “test‐and‐learn” approach holds the key to unlock logistics operations as a major competitive weapon in the current landscape of retailing. The purpose of this study is to empirically explore the characteristics of such a logistics learning capability, and to describe the corresponding logistics development practices. The research is based on an action research approach conducted at the Swedish fashion retailer H&M. During a period of 18 months, data has been collected through observations, informal discussions and interviews, and findings have been refined in two major cycles. The case of H&M offers insights into real existing learning and development practices at a retail company that operates in a highly competitive and complex retail landscape, characterized in particular by its process towards improved omni‐channel practices. The findings elaborate the four logistics learning components of culture, structure, relationships, and speed. Furthermore, five of H&M's logistics development practices are described and defined as experimental logistics development. In contrast to traditional development processes in which analysis is followed by lengthy linear implementation and evaluation phases, these practices are characterized by an experimental, “test‐and‐learn” approach with short feedback loops and iterative development processes.