Automated monitoring software only adds value when end users take the information and knowledge derived from software, and follow it up with actions. Within the drilling process, this is highly dependent on a few individuals on and off the rig. The objective is to reduce the dependence on those few individuals to create action, by designing and deploying a data aggregation and distribution system that inherently promotes proper action and leads to better performance. The key to the development of this system was a process of methodically determining the "who", the "what', the "when", the "why", the "where" and the "how" of disseminating the results of a real-time data analysis module. The analysis engine itself is an interchange-able modular unit running in the back ground, and does not disturb the human machine interface created on top of it. This effort was focused on understanding how the human computer boundary works, and aims towards maximizing the probability that the human (driller, company man, drilling engineer, etc.) will relate to computer generated information, understand and take action. Given that people are generally resistant to sudden changes, we followed a process of first building interfaces very similar to what they are used to, and then slowly modifying them as their confidence in the system increased. The need to modify displays in steps, necessitated a platform that allowed for easy modification and creation of displays. In the design of alerts, attention was given to data overload, salience, end user attention, interruptibility, and data visualization. The analysis engine needs be validated thoroughly, before the results are exposed to the end user. This is essential to achieving low false or missed alarm rates. The system is currently in operation on six rigs in North America. The paper details the various learnings as we have transitioned from our starting point to where we are now. Just as every well is different, every enterprise and the culture within is different, and this needs to be accounted for in setting up the human-computer interface. While multiple iterations may be needed before the enterprise workflow reaches a stable equilibrium, one does not have to wait until the end to reap the benefits.

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