Email Analytics for Activity Management and Insight Discovery

Emails constitute the bulk of all official communications in any organization. Email repositories are tacit store-houses of knowledge about people, projects and processes. Mining one´s own email repository can also provide interesting and valuable insights about his or her engagements and contacts along different dimensions. In this paper, we propose an email analytics framework that combines text-mining, network analysis and data analytics principles to mine email repositories for useful insights. While individuals are more attuned to looking at emails as individual items along with a history that is embedded in the trail, mining the whole collection can also lead to knowledge-discovery about similarities and dissimilarities of different engagements. This in turn can lead to valuable information like comparative status reports on various projects or deeper insights about why certain projects succeed while others don´t. Given the volumes, diversity and noisy nature of e-mails, it becomes impossible for human beings to comprehend the impact of all of it unless the task is automated and approached in a structured fashion. We show that combination of text and network analytics along with temporal reasoning can provide valuable insights about task-states, actionable items, recommendations and forecasts. These insights can be exploited very effectively for project-management tasks like automated identification of bottlenecks or their causes, elimination of inefficiencies, early-warnings and suggestions about proactive measures to avoid problems. It is possible to extend the framework quite easily to analyze multiple email repositories of different users, though this work does not address the privacy or security concerns that might exist.