Decision Analytics Journal is a forum for exchange of research findings, analysis, information, and knowledge in areas that include but are not limited to: Predictive Modelling - Decision Analytics encourages research endeavours that identify organizational risks and opportunities by exploiting patterns found in historical and transactional data. Simulation Modelling - Decision Analytics promotes application of simulation in enterprise and organizational context for examining and comparing options and scenarios prior to implementation. Optimization Modelling - Decision Analytics promotes research that can help decision-makers make the best choice by means of various optimization models. Prescriptive Methods - Decision Analytics invites research that supports the joint application of predictive models and optimization technology to create better solutions for decision-makers. Business Intelligence - Decision Analytics invites research that utilizes the latest techniques in data mining, analysis, and performance management to help decision-makers gain and sustain a competitive edge. The journal is subdivided into four Departments Descriptive Analytics Department handles manuscripts and studies answering the question of what happened by analyzing historical data and extracting hindsight about the past, without explaining why. Diagnostic Analytics Department handles manuscripts and studies answering the question of why something happened by measuring historical data against other data (i.e., benchmarks) and extracting insight into the present. Predictive Analytics Department handles manuscripts and studies answering the question of what will happen by using the findings of descriptive and diagnostic analytics and giving the foresight for the future. Prescriptive Analytics Department handles manuscripts and studies answering the question of what to do by using the findings of descriptive and diagnostic analytics and giving the prescription for the future to eliminate a problem or take advantage of a promising trend.