Fine Tuning Your Cleaning Costs
Using specialized data, workloading schedules can be tweaked to maximize efficiency and profit.
At the recent Building Owners and Managers Association International (BOMA) show in Seattle, facility data compilation reached a new milestone.
BOMA released its online Experience Exchange Report (EER), meaning users can now generate custom reports to compare and match property profiles.
The new EER program allows sorting by commercial office buildings, corporate facilities, government, financial and medical buildings and by location.
At the show, Tracy Glink, BOMA research manager, was willing to put the database to the test.
She sorted 5,000 U.S. and Canadian buildings to locate the cost per square foot for janitorial services and, within seconds, the answer came back.
Larger buildings in a particular city can be compared by the price per square foot with certain exceptions.
The variables that must be considered include such things as: Are we using full-time union workers or part-time non-union staffs; does the building experience light, medium or heavy use; is the workstation density and occupancy above or below the BOMA average; etc.
Shrinking Government Expenditures
Government austerity programs are imposing reduced cleaning frequencies in certain regions.
Cleaning schedules might include anything from seven days per week down to one day per week frequencies.
Of course, the exact cleaning schedules must be considered when calculating the bidding costs.
Some government bid requests include five or more different levels of cleaning for the same building or campus of buildings.
And, some include increased cleaning frequencies for physical fitness centers and child care centers.
Cleaning standards for high touch areas, where cross-contamination is a heightened concern, remains strict.
Building managers prefer to avoid an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) or norovirus.
Proper workloading requires breaking down each area for use and cleaning frequency and then assigning corresponding production rates.
Of course, the cleaning times for labor-intensive fitness centers and daycares will be greater than those for standard office cleaning.
The specifications might also require increased frequencies for carpet and floor care project work.
Building Use And Size
Traffic and building use is another workloading consideration.
For example, APPA's Operational Guidelines for Educational Facilities — Third Edition shows slower cleaning times for heavily trafficked areas.
The cleaning time for heavily used restroom facilities is almost twice that of average or light use restrooms.
Along the same lines, cleaning of heavily used classrooms takes almost twice as long as a regular classroom setting.
Years ago, cleaning pioneer, contractor and editor Don Aslett first proposed three measurements for cleaning.
By analyzing cleaning times, Aslett suggested an average cleaning time that would be adjusted according to density, traffic and difficulty.
His average cleaning times for various areas showed an estimated time, with a plus 10 percent for light areas and a minus 10 percent for difficult areas.
Actually, within the same building, different floors and company departments might vary in use and workstation density.
For example, if a large marketing department consists of outside sales representatives who spend 90 percent of their time out of the office, cleaning times for that department can be trimmed.
Another area of consideration is the size of a building.
The amount of setup and put away time for a large building is a smaller percentage of the total time, compared to that of a small building.
Additionally, large buildings allow for economies of efficiency including utilization of more efficient cleaning equipment.
On the other hand, a Class-A office building that is close to one million square feet may clean slower than a 20,000-square-foot Class-B building.
Make sure all of the bases are covered when calculating cleaning labor numbers.
Bidding software with built-in settings for the different bidding cleaning variables can help pinpoint an accurate cumulative production rate.
When it comes to assigning workload schedules, there is often more than meets the eye.
That is why it is difficult to predict how much square footage a cleaner should cover in a night or shift; it all depends upon what they are cleaning.