technical knowledge and time pressure, often relying on senior experts for root cause analysis.
Management temporarily shifted staff from innovation to operations to address issues post-release,
highlighting the need for a balance between innovation, QA, and operations.
The provided text outlines the challenges faced by TeleSP's Digital TV Services, including the impact
of increasing complexity, the sources of service incidents, staff preparedness issues, and the
adjustments made in performance measurement to address these challenges. It sheds light on the
dynamic nature of digital service supply chains and the importance of balancing innovation, QA, and
operations for effective service delivery.
Causal loop diagram and simulation model
The text explains how resolving or managing incidents leads to an increase in service reliability. It
also highlights the impact of service innovativeness and service reliability on the overall market
performance as perceived by customers. The document further delves into software bugs in a digital
service supply chain, illustrating the modeled processes of innovation, QA, and operations through a
stocks and flows diagram. The diagram maps relevant variables, interrelationships, and delays within
these processes. Additionally, it mentions that the model's structure and equations are based on
literature and empirical data, ensuring a medium level of evidence for the model's validity.
Results
The simulation started with a stable system in equilibrium, showing no change in behavior until
Week 50. At Week 50, the target service innovativeness was increased by 33%, leading to a
proportional increase in work and staffing levels. Initially, QA required the largest proportion of total
staff, with 26 out of 38.2 people allocated to it.
An efficient hill-climbing algorithm was utilized to optimize the allocation of 33% extra staff over 250
weeks to maximize average market performance. The results indicated the need for increased staff
in innovation (31%), QA (28%), operations (70%), and condition monitoring (343%) to ensure service
reliability and enhance market performance. Incident management staff allocation decreased by
17% to achieve an average market performance increase to 0.62.
As bug discovery potential decreases, the simulation results highlighted the importance of
reallocating resources. Innovation staff size remained stable, while QA staff decreased gradually for
lower bug discovery potential values. In contrast, investments in operations, especially condition
monitoring, became crucial. The relative importance of activities shifted with decreasing bug
discovery potential, impacting team sizes accordingly.
(2002) Repenning, Stermann – Capability
traps in the dynamic process improvement
Introduction
The document discusses the factors influencing internally focused change within organizations
through an inductive study of a firm's attempt to improve core business processes. It highlights the
critical role of managers' attributions about poor performance causes and the workplace structure in
determining success. The proposed dynamic model captures the evolution of attributions, actions,
and technology, showing how beliefs and physical environment interactions can hinder useful
change. The text also touches on the central idea in organizational theory that organizations improve
Management temporarily shifted staff from innovation to operations to address issues post-release,
highlighting the need for a balance between innovation, QA, and operations.
The provided text outlines the challenges faced by TeleSP's Digital TV Services, including the impact
of increasing complexity, the sources of service incidents, staff preparedness issues, and the
adjustments made in performance measurement to address these challenges. It sheds light on the
dynamic nature of digital service supply chains and the importance of balancing innovation, QA, and
operations for effective service delivery.
Causal loop diagram and simulation model
The text explains how resolving or managing incidents leads to an increase in service reliability. It
also highlights the impact of service innovativeness and service reliability on the overall market
performance as perceived by customers. The document further delves into software bugs in a digital
service supply chain, illustrating the modeled processes of innovation, QA, and operations through a
stocks and flows diagram. The diagram maps relevant variables, interrelationships, and delays within
these processes. Additionally, it mentions that the model's structure and equations are based on
literature and empirical data, ensuring a medium level of evidence for the model's validity.
Results
The simulation started with a stable system in equilibrium, showing no change in behavior until
Week 50. At Week 50, the target service innovativeness was increased by 33%, leading to a
proportional increase in work and staffing levels. Initially, QA required the largest proportion of total
staff, with 26 out of 38.2 people allocated to it.
An efficient hill-climbing algorithm was utilized to optimize the allocation of 33% extra staff over 250
weeks to maximize average market performance. The results indicated the need for increased staff
in innovation (31%), QA (28%), operations (70%), and condition monitoring (343%) to ensure service
reliability and enhance market performance. Incident management staff allocation decreased by
17% to achieve an average market performance increase to 0.62.
As bug discovery potential decreases, the simulation results highlighted the importance of
reallocating resources. Innovation staff size remained stable, while QA staff decreased gradually for
lower bug discovery potential values. In contrast, investments in operations, especially condition
monitoring, became crucial. The relative importance of activities shifted with decreasing bug
discovery potential, impacting team sizes accordingly.
(2002) Repenning, Stermann – Capability
traps in the dynamic process improvement
Introduction
The document discusses the factors influencing internally focused change within organizations
through an inductive study of a firm's attempt to improve core business processes. It highlights the
critical role of managers' attributions about poor performance causes and the workplace structure in
determining success. The proposed dynamic model captures the evolution of attributions, actions,
and technology, showing how beliefs and physical environment interactions can hinder useful
change. The text also touches on the central idea in organizational theory that organizations improve
