A Knowledge-Intensive Process (KiP) is specified as a composition of a set of prospective activities (events) whose execution contributes to achieving a goal and whose control-flow, at the instance level, typically presents a high degree of variability among its several past executions. Variability is a consequence of a combination of decision points and informal interactions among participants on collaborative and innovative activities. These interactions may occur through message exchange, thus understanding the interplay of illocutionary acts within messages may bring insights on how participants make decisions. In this paper, we propose mechanisms that identify speech acts in the set of messages that mostly lead to decision points in a KiP providing an understanding of conversational patterns. We empirically evaluate our proposal considering data from a company that provides IT services to several customers.