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Quantum computers can efficiently simulate the dynamics of quantum systems. In this paper, we study the cost of digitally simulating the dynamics of several physically relevant systems using the first-order product formula algorithm. We show that the errors from different Trotterization steps in the algorithm can interfere destructively, yielding a much smaller error than previously estimated. In particular, we prove that the total error in simulating a nearest-neighbor interacting system of $n$ sites for time $t$ using the first-order product formula with $r$ time slices is $O({nt}/{r}+{nt^3}/{r^2})$ when $nt^2/r$ is less than a small constant. Given an error tolerance $\epsilon$, the error bound yields an estimate of $\max\{O({n^2t}/{\epsilon}),O({n^2 t^{3/2}}/{\epsilon^{1/2}})\}$ for the total gate count of the simulation. The estimate is tighter than previous bounds and matches the empirical performance observed in Childs et al. [PNAS 115, 9456-9461 (2018)]. We also provide numerical evidence for potential improvements and conjecture an even tighter estimate for the gate count.