Optimal Strategy For Proactive Service Delivery Management Using Inter-Kpi Influence Relationships

Service interactions now account for major source of revenue and employment in many modern economies, and yet service operations management remains extremely complex. To lower risks, every Service Delivery (SD) environment needs to define its own key performance indicators (KPIs) to evaluate the present state of operations and its business outcomes. Due to the over-use of performance measurement systems, a large number of KPIs have been defined, but their influence on each other is unknown. It is thus important to adopt data-driven approaches to demystify the service delivery KPIs inter-relationships and establish the critical ones that have a stronger influence on the business outcomes. Given a set of operational KPIs and SD outcomes, we focus on the problem of (a) extracting inter-relationships and impact delays among KPIs and outcomes, and building a regression-based KPI influence model to estimate the SD outcomes as functions of KPIs. (b) Based on the model we propose a schedule of action plans to transform the current service delivery system state. (c) We also build a visualization tool that enables validation of extracted KPIs influence model, and perform what-if analysis.