Posts

How You Can Use Data to Reduce the Threat of Outsourcing

Like it or not, we live in an age where data rules. So much, in fact, that the term “big data” has become more than just a buzzword, it’s central to the way businesses operate. Each day, billions of data bytes are collected as businesses track what we’re buying, where we’re going, what we’re watching and how we’re using the internet. Businesses use this data to better target their advertising and products with the ultimate goal of growing sales.

On the operational side, organizations also amass vast data banks related to all aspects of their business. This includes information about their supply chain, logistics, inventory and labor. This data is regularly analyzed to increase efficiencies, identify opportunities and improve margins.

Organizations that fail to produce data related to their cleaning operation run the risk of being outsourced.

That’s why when cleaning professionals neglect to collect and track data related to their operations, they ultimately fail. This failure can result in significant downsizing—or outsourcing.

Here’s a scenario we see too often:

Jim has managed a cleaning department for more than 15 years. Over this period, much of the cleanable square footage has remained the same, so Jim has maintained the same number employees to clean that space. While he’s had a few cuts, his budget has also remained largely unchanged over the years. He makes purchases based on recommendations from his distributor sales rep and previous purchase histories.

Enter Robert. Robert is the new CEO of the business where Jim works. In his first two weeks on the job, Robert meets with all the department managers to get a better understanding of the business. He asks Jim questions like, “How much time and chemical does it take for your team to clean the cafeteria?” and, “How would changing cleaning frequencies impact cleanliness?”

Jim broadly answers the questions, providing estimations based on his experience. But Jim can’t tell Robert that it takes two people on his team 42 minutes to clean the cafeteria using .5 ounces of all purpose cleaner concentrate. Jim doesn’t have this data. 

We all know how the scenario plays out. Not long after the meeting ends, Jim’s department is outsourced to a contract cleaning company who promises more for less. While the quality of cleaning plummets, it takes Robert and his executive team to realize the impact cleanliness has on both their customers’ experience and the productivity of the workers in their headquarter offices.

Developing Data through Workloading

Workloading your operations can product significant data related to your cleaning program, and it doesn’t require assistance from a consultant or someone who claims to know a secret formula. You can do it yourself. In fact, we’ve just wrapped up a crowd-sourced workloading project that includes 99 common (and benchmarked!) workloading times along with formulas you can use to workload your operations. Feel free to check out the booklet here, which will soon be released in a comprehensive do-it-yourself kit. But more on that later.

Really, the key to workloading is just understanding and working through a few relatively simple steps:

  1. Complete a thorough inventory of the space to be cleaned. Rather than using the gross square footage of the building, it’s best to walkthrough the building and manually calculate the cleanable square footage. This will help ensure the accuracy of the data and avoid skewed figures.
  2. List the cleaning tasks to take place. You should break down tasks into three categories, including daily, detail and project. Sample tasks may include empty trash, dust all horizontal surfaces, vacuuming, spot clean glass, etc.
  3. Calculate the time necessary to perform the tasks. There are thousands of variables that can impact cleaning times, but unless plan on conducting your own time and motion study, you can start with the times provided in the 612 Cleaning Times Booklet.
  4. Begin workloading the data. Begin by developing a chart that identifies the frequencies, tasks and the time performed for each task. For example, a daily task, such as dusting, may be performed 260 times per year where scrubbing flowers may be done once a month, or 12 times a year.

Next, allocate the amount of time for each task to the appropriate square footage. Then, add non-surface items per unit to be cleaned. In your final step, you should calculate the time for each task and multiply multiply that by the frequency. This number should offer a clear picture of the amount of time and labor required to clean your facility.

Ultimately, the formula is to take the task and multiply it by the time (required to perform the task), then multiply that number by the frequency. The final calculated number is your basic workload.

TASK x TIME x FREQUENCY = WORKLOAD

This piece of data is just one of several you should have in your pocket should “Robert” show up at your business and schedule a meeting.

Click here to receive your copy of our DIY Workloading Guide and stay tuned for more information our complete DIY Workloading Kit, coming soon!

SaveSave

Provo City Schools Research Part II: The Importance of Measuring Cleaning

In the first part of this series, we explored the definition of “clean.” Now that we know what “clean” is, how do we get there? Ah, the million dollar question.

Just as no single agreed-upon definition of “clean” exists, no single standard or process for cleaning exists. As a result, we measure janitorial productivity in a variety of ways, which is largely dependent on the type of facility being cleaned.

To understand the importance of measurement, we’ll first look ways cleaning programs are currently measured, and then we’ll review a few examples of the benefits of measurement through a standardized approach to cleaning.

Current Strategies for Measuring Productivity and Their Limitations:

Visual Inspections: A visual inspection may reveal if a surface looks clean (e.g. is free from dirt or dust), but it does not reveal what is invisible to the eye, such as bacteria or viruses. Visual inspections are most common in retail environments where the emphasis is on appearance.

Cost-Per-Square-Foot Method: Often cleaning professionals want to evaluate cleaning productivity by establishing the cost for cleaning their facility. This method can present obstacles because of different surfaces that may or may not be factored into the equation. For example, do you factor the tops of books on a shelf as cleanable square footage? Should table surfaces be included as well? Not all cost-per-square foot method evaluations are created equally.

ATP Meter Readings: One of the newer methods for measuring cleanliness is Adenosine Triphosphate (ATP) Testing. ATP is an enzyme present in all living cells; ATP meters detect the amount of organic mater that remains on a surface after cleaning. This method can lead to discrepancies between testers and not provide a true reflection of the cleanliness (or dirtiness) of a surface.

When we look at cleaning in an academic settings, the need for effective cleaning and cleaning measurement becomes most apparent.

Why Clean Schools Matter

In Dr. Campbell’s Provo City Schools research, he states:

Standards set a level of safety and performance for most industries. Therefore, a cleaning standard that ensures the building’s air quality, safety and health of the people therein should exist. Research shows that students in K-12 schools have improved capacity to learn when school environments are clean.

He identifies a survey conducted by the National Parent Teacher Association that revealed that cleanliness in schools was so insufficient that more than half of teachers (56 percent) purchase their own cleaning supplies to clean their classrooms.

While the immediate response might be to look at the school janitor, Dr. Campbell is quick to highlight research from the National Education Association that supports the need for better job descriptions for janitors:

* 38 percent of janitors have no job description

* 32 percent of those who do have a job description feel it does not match the scope of their work

64 percent of janitors often or sometimes perform work outside of their job description

YIKES. So teachers are taking it on themselves to clean their classrooms, but janitors are left with their hands in the air, because they aren’t clear on their responsibilities.

Why does this matter? Because the confusion surrounding the issue and the absence of a standardized approach and effective cleaning measurement tool to cleaning goes beyond issues of infection control and cross contamination.

Research shows that indoor air pollution (resulting from cleaning chemicals, dust and other particulates that can be breathed in) can result in lower work performance and higher rates of sickness.

Dr. Campbell cites multiple sources, including this research published in Indoor Air, Dr. Berry’s study at Charles Young Elementary School and this study published in Indoor Air Journal — all offering conclusive evidence that indoor pollutants negatively impact student health and performance.

Clean schools are healthier and more productive. But how can we make sure our schools are clean if there’s difficulty measuring janitorial productivity and cleanliness?

In the part three of this blog series, we’ll review how a standardized approach to cleaning establishes measures for janitorial productivity and positively impacts health and the indoor environment, as evidenced by the study at Dixon Middle School.