Category
Three-Minute Thesis
Description
Service organizations rely on operational metrics to evaluate performance. Yet, traditional measures prioritize speed over value, often concealing variables that hide inefficiencies. This project introduces Notification Efficiency (NE) as a construct that utilizes a composite percentage value reflecting the resources used to achieve full operational status. In the proposed framework, a notification is defined as an artifact documenting evidence of a service recovery event. NE is designed to relate directly to resources involved in service recovery—as travel, labor, shipping, and escalation—with an extended goal of triggering early intervention opportunities. As a natural extension to field service, NE can also reside in call center environments, decomposed into relevant call center metrics. When appropriate operational data points are selected, higher efficiency reflects lower levels of effort and costs. The key research question becomes: How does NE both identify operational waste beyond what is captured in traditional speed-based metrics alone and surface service factors that drive costs—notification churn, repeat site visits, parts replaced? The outcomes of NE visibility prescribe pathways of managerial investigation and intervention based on data-driven insights. Integrating NE into operationally focused, action-based dashboards can reduce recovery costs by inviting opportunities for root cause analysis; process and equipment training; or resource evaluation. Drawing on service operations management and Lean waste (Converso et al., 2025), this study aims to provide a new framework that operationalizes service recovery into a single quantification metric. Future research directions include using NE as an early intervention signal, supporting more proactively designed service operation systems in field service, indicating a shift from firefighting to holistic support.
Reference
Converso, G., Guizzi, G., Salatiello, E., & Vespoli, S. (2025). Lean service waste classification and methodological application in a case study. Journal of Manufacturing and Materials Processing, 9(4), 121. https://doi.org/10.3390/jmmp9040121
Notification Efficiency
Three-Minute Thesis
Service organizations rely on operational metrics to evaluate performance. Yet, traditional measures prioritize speed over value, often concealing variables that hide inefficiencies. This project introduces Notification Efficiency (NE) as a construct that utilizes a composite percentage value reflecting the resources used to achieve full operational status. In the proposed framework, a notification is defined as an artifact documenting evidence of a service recovery event. NE is designed to relate directly to resources involved in service recovery—as travel, labor, shipping, and escalation—with an extended goal of triggering early intervention opportunities. As a natural extension to field service, NE can also reside in call center environments, decomposed into relevant call center metrics. When appropriate operational data points are selected, higher efficiency reflects lower levels of effort and costs. The key research question becomes: How does NE both identify operational waste beyond what is captured in traditional speed-based metrics alone and surface service factors that drive costs—notification churn, repeat site visits, parts replaced? The outcomes of NE visibility prescribe pathways of managerial investigation and intervention based on data-driven insights. Integrating NE into operationally focused, action-based dashboards can reduce recovery costs by inviting opportunities for root cause analysis; process and equipment training; or resource evaluation. Drawing on service operations management and Lean waste (Converso et al., 2025), this study aims to provide a new framework that operationalizes service recovery into a single quantification metric. Future research directions include using NE as an early intervention signal, supporting more proactively designed service operation systems in field service, indicating a shift from firefighting to holistic support.
Reference
Converso, G., Guizzi, G., Salatiello, E., & Vespoli, S. (2025). Lean service waste classification and methodological application in a case study. Journal of Manufacturing and Materials Processing, 9(4), 121. https://doi.org/10.3390/jmmp9040121
