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Feeder reliability has been receiving increased attention. Substantial industry efforts have defined standardized indices for quantifying reliability. Utility commissions and municipalities are requiring utilities to use these indices to identify and make improvements to poorly performing feeders. Reliability indices generally equate to the number and length of outages, and to the number of customers affected. While some outages are unavoidable, others are the result of incipient failures or apparatus malfunction. This paper illustrates how reliability can be improved through real-time situational awareness of faults and events. Emphasis is given to providing actionable information with little or no human intervention. The paper describes how Texas A&M's Distribution Fault Anticipation (DFA) project documented naturally occurring faults and outages on 60 feeders, and examines how those events could be avoided with intelligent monitoring. Reliability improvements are projected through condition-based maintenance and quick response to outages using previously unavailable information on faults and events.