Recently, the petroleum industry has capitalized on remarkable information and collaboration technologies that bring vast amount of real-time data to the decision-makers. The goal is to improve their decision-making processes by integrating technology, people, work processes, and organizations. However, complexity of drilling operations and investment costs put industry in quest for a feasible method to valuate benefits. The prevailing evaluation methods are usually restricted to qualitative approaches, and thus are inefficient as decision aids. The paper presents a decision analytic approach to quantitative valuation of integrated operations.The proposed valuation method is illustrated by a case from improving decisions' quality in drilling operations in the North Sea. Improving the quality of operational decisions requires the drilling team to have access to the relevant information in a timely manner. The relevant information needs to be filtered, aggregated, and fused into decisions; and correspondingly represented to the decision-maker. Availability of new information allows making new decisions, and changing work processes. Adoption of a new tool, conformance to a new work process and trust in aggregated and shared information are typically critical success factors. The method is designed to qualitatively analyze changes in intangible capital and assess technology adoption under conditions of operational and economical uncertainties.The method accounts for information quality improvements and related uncertainties management. In turn, decision analytical part of the method provides a means to relate observable improvements in Key Performance Indicators (KPIs) and uncertainties. Operational decisions are formalized using influence diagram, a.k.a. Bayesian decision network.Implementation of digital fields and integrated operations is technologically and organizationally challenging. The functional steps of the established methodology and the decision analytic approach are significant contributions to understanding the quantitative value of these projects.