We give a polynomial time, $(1+ε)$-approximation algorithm for the traveling repairman problem (TRP) in the Euclidean plane and on weighted trees. This improves on the known quasi-polynomial time approximation schemes for these problems. The algorithm is based on a simple technique that reduces the TRP to what we call the \emph{segmented TSP}. Here, we are given numbers $l_1,\dots,l_K$ and $n_1,\dots,n_K$ and we need to find a path that visits at least $n_h$ points within path distance $l_h$ from the starting point for all $h\in\{1,\dots,K\}$. A solution is $α$-approximate if at least $n_h$ points are visited within distance $αl_h$. It is shown that any algorithm that is $α$-approximate for \emph{every constant} $K$ in some metric space, gives an $α(1+ε)$-approximation for the TRP in the same metric space. Subsequently, approximation schemes are given for this segmented TSP problem in the plane and on weighted trees. The segmented TSP with only one segment ($K=1$) is equivalent to the $k$-TSP for which a $(2+ε)$-approximation is known for a general metric space. Hence, this approach through the segmented TSP gives new impulse for improving on the 3.59-approximation for TRP in a general metric space. A similar reduction applies to many other minimum latency problems. To illustrate the strength of this approach we apply it to the well-studied scheduling problem of minimizing total weighted completion time under precedence constraints, $1|prec|\sum w_{j}C_{j}$, and present a polynomial time approximation scheme for the case of interval order precedence constraints. This improves on the known $3/2$-approximation for this problem. Both approximation schemes apply as well if release dates are added to the problem.