Cleaning Equipment and Supplies: For a professional house cleaning company, the costs of labor is so overwhelmingly important that the per assignment costs of cleaning equipment and supplies is simply lost in rounding. We're not saying that it is not worthwhile to carefully manage such costs, but rather that we have chosen not to attempt to allocate them by assignment.
Bedrooms, Common Rooms, and Laundry Rooms: these areas of a house are highly correlated with square feet. Including statistics for these areas of a house provides almost no meaningful predictive value to the model.
Clutter Factor: measures the extent and orderliness of clothes, toys, and paper, and the impact such items have on Clean Times. A home cluttered with clothes, toys or paper can take significantly more time to clean than an uncluttered home. While the concept seems to have merit based on our experience, we found it very difficult to apply because users invariably mixed clutter factor with Lifestyle Factor. Indeed, this was clearly demonstrated during the statistical analysis - the factors proved to be highly correlated and the clutter factor was shown to have a low predictive value, and has been removed from the equation.
Decoration Factor: measures the extent and intricacy of a Household's decoration and the impact the household's decoration has on Clean Times. An ornately decorated home takes longer to clean, particularly to dust, than an undecorated home. A minimalist would have a negative Decoration Factor, while an art collector might have a high Decoration Factor. While the concept seems to have merit based on our experience, the factor was shown to have an unacceptably low predictive value, so it has been removed from the equation.