A method for identifying automatically an inner node within a hierarchical network causing an outage of a group of leaf nodes at the lowest hierarchical level of said hierarchical network , said method comprising the steps of: providing (S1) an outage state matrix (X) representing an outage state of leaf nodes at the lowest hierarchical level of said hierarchical network ; decomposing (S2) the state matrix (X) into a first probability matrix ( Ŵ ) indicating for each inner node of said hierarchical network the probability that the respective inner node forms the origin of an outage at the lowest hierarchical level of said hierarchical network and into a second probability matrix ( Ĥ ) indicating for each leaf node at the lowest hierarchical level of said hierarchical network the probability that an inner node forms a hierarchical superordinate node of the respective leaf node at the lowest hierarchical level of said hierarchical network ; and evaluating (S3) the first probability matrix ( Ŵ ) to identify the inner node having caused the outage of said group of leaf nodes; wherein the hierarchical network is a hierarchical power supply network, wherein the hierarchical power supply network comprises at its lowest hierarchy level leaf nodes formed by smart meters generating event data streams (EDS) indicating a current outage state of the leaf nodes of said power supply network , wherein the outage state matrix (X) derived from the event data streams is a two-dimensional matrix, wherein the first dimension of said outage state matrix (X) represents time, wherein the second dimension of said outage state matrix (X) represents smart meters forming leaf nodes at the lowest hierarchical level of said power supply network , wherein each column of said two-dimensional outage state matrix (X) represents the state of a respective smart meter at particular points in time, and wherein each row of said outage state matrix (X) represents the states of all smart meters at a particular point in time. providing (S1) an outage state matrix (X) representing an outage state of leaf nodes at the lowest hierarchical level of said hierarchical network ; decomposing (S2) the state matrix (X) into a first probability matrix ( Ŵ ) indicating for each inner node of said hierarchical network the probability that the respective inner node forms the origin of an outage at the lowest hierarchical level of said hierarchical network and into a second probability matrix ( Ĥ ) indicating for each leaf node at the lowest hierarchical level of said hierarchical network the probability that an inner node forms a hierarchical superordinate node of the respective leaf node at the lowest hierarchical level of said hierarchical network ; and evaluating (S3) the first probability matrix ( Ŵ ) to identify the inner node having caused the outage of said group of leaf nodes; wherein the hierarchical network is a hierarchical power supply network, wherein the hierarchical power supply network comprises at its lowest hierarchy level leaf nodes formed by smart meters generating event data streams (EDS) indicating a current outage state of the leaf nodes of said power supply network , wherein the outage state matrix (X) derived from the event data streams is a two-dimensional matrix, wherein the first dimension of said outage state matrix (X) represents time, wherein the second dimension of said outage state matrix (X) represents smart meters forming leaf nodes at the lowest hierarchical level of said power supply network , wherein each column of said two-dimensional outage state matrix (X) represents the state of a respective smart meter at particular points in time, and wherein each row of said outage state matrix (X) represents the states of all smart meters at a particular point in time. <EOS>