This paper describes the development of a new computational model to predict the desirability of decision consequences in an organization, and the development of a prototype tool to enable real-time interaction and decision support when changes occur simultaneously. A tool, called Decision Propagation System, is developed in response to the needs of BT Group plc in understanding the most effective set of interventions in the organization where the high degree of connectivity between system components and the uncertainty in connectivity data are two critical issues. Designed on a case study of the Fields Operations Engineering, this research demonstrates that a knowledge of overlapping decision propagation paths can direct the organizational decisions towards mitigating the risk of unintended consequences.

This paper proposes a model that integrates information from product, process and organisation domains with a view to help manage these complex interrelationships with multiple layers of interaction. This model incorporates an integrated mechanism that simulates change effects during the design of complex manufacturing system by populating a Multi-layered Domain Matrix (MDM) and applying a Change Prediction Model (CPM) propagation mechanism to interconnected elements.

The term Integrated Product Development (IPD) has been introduced as a focus for cross-disciplinary research and can have several forms, or manifestations, with regard to the existing disciplines such as concurrent engineering and design for manufacturing. Of central importance to IPD is the interpretation of the term "integration", particularly with regard to internal and external elements. However, there is not yet an explicit understanding of an appropriate degree of integration, or involvement, with respect to its different forms, that can assure successful implementation of IPD frameworks in practice. Through a review and clustering of the literature, this paper aims to address this challenge.

Today's market conditions such as globalisation and digitalisation have made it challenging to design an effective service system that can efficiently balance organisational service capacity and customer service quality, hence ensure achieving business growth. One key reason might be related to the complex structure of relationships within and across functional disciplines that in often cases are dynamic and uncertain while occurring in multiple layers. Therefore, effective understanding of these interrelationships might be a significant step towards understanding the dynamics of a complex service system. In response to this challenge, this paper presents development and application of a systematic modelling and analysis framework that uses functionality of Change Prediction Method and System Dynamics to integrate multiple levels of relationships. The objective is to help decision makers understand key influencing factors and their underlying risk and impact on the system behaviour, i.e., customer experience, thus making organisation more adaptive in responding to changes and uncertainties. The ideas are illustrated through an expanded case study in British Telecom company.