The House Cleaning Alliance (HCA) has developed statistical models to predict the number of man-minutes required for a team of professional house cleaners to clean an occupied single family home on a recurring basis. The pricing models have been derived based on multivariable linear regressions. The factors which were found to be significant in predicting cleaning time can be categorized as: House Attributes Usage Factors Execution Factors
House Attributes include physical characteristics which could affect man-minutes, including the size of the residence measured in square feet, any basement area which requires cleaning, number of toilets, and the number of showers in use. These factors are objective and are generally relatively easy to quantify for any house or apartment.
Usage Factors include those which can significantly affect the time required to clean a home. Some, like number of inhabitants, can be counted, while others are more subjective in nature and relatively more difficult to measure. These include Lifestyle factor, Floor factor, and Pet factor. The precise definitions of these are discussed below.
Execution Factors include quantifiable attributes associated with a house cleaning company's unique operating profile, like standard team size, as well as psychological factors which were found to impact cleaning times, like whether or not the workers have more or less work than they would like that day, time of day for the cleaning assignment, and whether, for a specific service date, the client is present during the cleaning process. The analysis has also considered the effect of variability among the efficiency of distinct Team Leaders.