Synthesis of Decision Making: From Data to Business Execution

Digital Data is everywhere - from massive amounts of single sourced to huge conglomerations of smaller multi-sourced data. Organizations have long been collecting repositories of data, yet continue to struggle to create valuable information. In this paper, we propose a Data to Decisions Framework (D2D) to outline the course of action needed to procure the information required by organizations. D2D not only relies on data collection and process analysis, but upon human interaction as well. The study addresses the following problem: Data is obtained and stored from the perspective of the design of the application - not from the customer's point of view. The paper considers anomaly detection and cluster analysis to assist in the process of identifying and classifying Information Technology System Outages with the objective of providing the appropriate view for analysis. The paper also reveals how transparency and collaboration with key stakeholders then influence the process rules and properties to drive selection of target measures and definitions. The human touch, combined with rich data sets, is unique to the D2D Framework and is the driver in bringing real and desired results across the organization.