  Knowledge silos emerge when structural properties of organizational
interaction networks limit the diffusion of information. These structural
barriers are known to take many forms at different scales - hubs in otherwise
sparse organisations, large dense teams, or global core-periphery structure -
but we lack an understanding of how these different structures interact. Here
we bridge the gap between the mathematical literature on localization of
spreading dynamics and the more applied literature on knowledge silos in
organizational interaction networks. To do so, we introduce a new model that
considers a layered structure of teams to unveil a new form of hierarchical
localization (i.e., the localization of information at the top or center of an
organization) and study its interplay with known phenomena of mesoscopic
localization (i.e., the localization of information in large groups), $k$-core
localization (i.e., around denser $k$-cores) and hub localization (i.e., around
high degree stars). We also include a complex contagion mechanism by
considering a general infection kernel which can depend on hierarchical level
(influence), degree (popularity), infectious neighbors (social reinforcement)
or team size (importance). This general model allows us to study the
multifaceted phenomenon of information siloing in complex organizational
interaction networks and opens the door to new optimization problems to promote
or hinder the emergence of different localization regimes.
