Just a note, the only reason I posted was the title of the thread. It mentions workflow.
I'll refer you to Cuthbert Daniel (Daniel Plots aka normal and half normal plots) and G.E.P. Box (also adds Bayes plots) for methods of analyzing saturated models. Pareto plots where you indicate practical significance on the Y axis are also quite useful. Just leaving terms out of the model biases the MSE estimate and can lead to misinterpretation of the data.
Daniel, Cuthbert (1959), Using Half-Normal Plots in Interpreting Factorial Two-level Experiments, Technometrics, November, Vol. 1, No. 4
Box, G.E.P., Daniel Meyer, (1993), “Finding the Active Factors in Fractionated Screening Experiments”, Journal of Quality Technology, Vol. 25, No. 2, April
See how Dr. Box analyzes experiments this paper:
Box, G.E.P., Stephen Jones (1992), “Split-plot designs for robust product experimentation”, Journal of Applied Statistics, Vol. 19, No. 1
"All models are wrong, some are useful" G.E.P. Box