In organizations where agents face cognitive costs, communication patterns should reflect the relative value of their members to the organization. We propose to measure the impact factor of an agent by applying the Invariant Method — also known as Google's PageRank algorithm — to electronic communication data. To explore the validity of this measure, we analyze email exchanges among the top executives of a large retail company. We construct their individual impact factors based only on email patterns and we compare them to standard economic measures of organizational importance. We find that: (i) The impact-factor ranking of executives mirrors perfectly their hierarchical ranking; (ii) Impact factor variability is significantly correlated with salary differences; (iii) Subsequent promotions (dismissals) affect executives with unusually high (low) impact factors. We conclude that simple communication-based impact factors may be a useful tool to measure the relative importance of agents in organizations. We also apply our measure to a publicly available email corpus (Enron): individual impact factors are significantly correlated with rank.