TY - JOUR
T1 - Process modularity over time: modelling process execution as an evolving activity network
AU - Parraguez Ruiz, Pedro
AU - Piccolo, Sebastiano
AU - Perišić, Marija Majda
AU - Štorga, Mario
AU - Maier, Anja
PY - 2021
Y1 - 2021
N2 - Process modularity describes the extent to which processes can be decomposed into modules to be executed in parallel. So far, research has approached process modularity from a static perspective, not accounting for its temporal evolution. As a result, the understanding of process modularity has been limited to inferences drawn from aggregated analyses that disregard process execution. This paper introduces and develops the notion of dynamic process modularity considering the evolving activity network structure as executed by people. Drawing on network science, the paper quantifies process modularity over time using archival data from an engineering design process of a biomass power plant. This paper shows how studying the temporal evolution of process modularity enables a more complete understanding of activity networks, facilitates the comparison of actual process modularity patterns against formal engineering design stages, and provides data-driven decision-support for process planning and interventions. Finally, managerial recommendations for interface management, resource allocation, and process decomposition are proposed, to help practitioners better to understand and manage dynamic processes.
AB - Process modularity describes the extent to which processes can be decomposed into modules to be executed in parallel. So far, research has approached process modularity from a static perspective, not accounting for its temporal evolution. As a result, the understanding of process modularity has been limited to inferences drawn from aggregated analyses that disregard process execution. This paper introduces and develops the notion of dynamic process modularity considering the evolving activity network structure as executed by people. Drawing on network science, the paper quantifies process modularity over time using archival data from an engineering design process of a biomass power plant. This paper shows how studying the temporal evolution of process modularity enables a more complete understanding of activity networks, facilitates the comparison of actual process modularity patterns against formal engineering design stages, and provides data-driven decision-support for process planning and interventions. Finally, managerial recommendations for interface management, resource allocation, and process decomposition are proposed, to help practitioners better to understand and manage dynamic processes.
U2 - 10.1109/TEM.2019.2935932
DO - 10.1109/TEM.2019.2935932
M3 - Journal article
SN - 0018-9391
VL - 88
SP - 1867
EP - 1879
JO - I E E E Transactions on Engineering Management
JF - I E E E Transactions on Engineering Management
IS - 6
ER -