In this paper, the use of orthogonal factorizations, more precisely the Q-R decomposition, to analyze, decompose and solve the linear and bilinear data reconciliation problem is further investigated. It is shown that the decomposition provides additional insight in identifying structural singularities in the system topology, allowing the problem to decompose into lower dimension subproblems. Energy balances are explicitly considered. Two examples of application are presented.