Equipment Manufacturing: Mike Diedling, Pellerin Milnor Corp., Kenner, La.
These variables include, but are not limited to, the size, shape and state of repair of the laundry space; equipment type, quantity and state of repair; labor force availability and training level achieved; type of goods to be processed and quality level required; chemical supplier’s technical capabilities; and the list goes on and on.
Given that achieving and maintaining high productivity is the goal, I would measure labor, utility consumption, chemical supplies and output. I target these items to measure because they represent those items we can control on a short-term basis. I may not be able to control depreciation costs short-term, but I can certainly change washing formulas to use less water and chemicals.
The metric I would use for labor would be pounds produced per productive labor hour. Productive labor hours include everyone in soil sort, wash, flatwork, dry fold, garment processing and packaging—essentially everyone who works in the laundry and touches the linen. The output used for the productivity metrics should be clean, dry pounds packed and shipped.
Similar metrics would measure each utility (power, fuel, water) and chemical supplies (alkali, detergent, bleach, sour, etc.) against the pounds packed. Timing of the availability of these metrics is critical. Ideally, these metrics are automated and available to you in real time so that you can react to exceptions in performance as your day evolves. The longer it takes to develop and make available the metric data, the less time you have to react and take corrective action.
I’ve seen plants have the metric data available on their supervisor’s cell phones in real time, and I have seen plants that have it available on a daily, weekly, or monthly basis in a printed report. Can you guess which one has the highest productivity?
Okay, so you have established the metrics you want and you have a way of gathering the information. This begs the question: What do I compare my metrics to in order to determine if I am achieving my goal of high productivity? We know that even if we grow up in the same family, each member has strengths and weaknesses that differ from other members of the family, even when there are twins or triplets.
In the laundry, the analogy is that every plant is different and will perform differently, even when built by the same company with the same or similar equipment. Why? Because even though they are physically the same (definitely not the usual case), they have different utility, labor and supply costs. They have different people, and they operate under different laws.
The answer to the question is to develop your own goals for each metric. You have co-workers, colleagues in other laundries, equipment manufacturers, consultants, chemical vendors, seminars, webinars—a whole community of sources you can tap to develop goals for each metric. These goals should be revised over time as you make process or equipment changes, develop new methods, train, etc.
Comparing your operating metrics against those of other plants can help you to understand where additional improvements can be made. To not set operating goals leaves you on the road to a destination without knowing where you are or when you have arrived.
Consulting Services: Chris Mayer, Performance Matters, Plymouth, Minn.
For the purpose of this broad topic, let’s focus on service and outside sales. The KPIs (key performance indicators) we focus on with our clients are both activity- and result-based. These are some examples.
- Quit item percent of rental revenue.
- Quit account percent of rental revenue.
- Route sales average—weekly revenue.
- Inventory net revenue (increase vs. decrease).
- Net price increase: “Net” is the core measurement. This means you measure the total revenue price increase minus exempt accounts (contractual commitments, municipalities, purchase order accounts, national contracts, accounts that are exempted due to retention risks, etc.)
- Charge and cash credit percent of revenue.
- Uniform stockroom requested and issued percent.
- Net merchandise cost: Percent of new merchandise input dollars compared to total product group revenue.
Accounts Receivables: Some companies define this KPI as an office responsibility. Other companies consider it as a service function.
- Past due accounts (current, 30, 60, 90-plus days).
- Write-off dollars.
Weekly rental sales sold.
Weekly catalog sales revenue sold.
- First-time appointments, follow-up appointments.
Activities/week: On-site cold calls, phone prospect calls, e-mails, direct mail, referrals, etc.
We focus on a number of other KPIs with our clients and benchmark these specific results versus the overall laundry industry. This helps our clients identify areas of opportunity. You have to keep score if you’re going to win the game.
Chemicals Supply: Scott Pariser, Pariser Industries Inc., Paterson, N.J.
Benchmarking and tracking operational data is key to proper laundry management.
National statistics, if not always best used as a definitive goal for each and every laundry operation, can serve at minimum as a guideline for managerial reference points in terms of laundry overview.
Even if national statistical benchmarks are unavailable to a laundry manager for comparison, tracking operational data from week to week, or longer period to period, enables one to establish a feel for individual operational production level norms, so that variations to the norm, up or down in the future, can be observed, evaluated and learned from (e.g., why have our resulting statistics changed negatively from period to another, or what happened, positively speaking, when we made what we hoped was a beneficial operational change over the most recent period?).
Specific data that has proven beneficial to operation management over time has included, but is not limited to, the following:
- Pounds of clean linen produced per period.
- Pounds of rewash as a percentage of total production.
- Rag-out (linen that is not reclaimable) as a percentage of clean linen produced.
- Pounds of linen processed per operator hour.
- Labor cost in dollars per operator hour.
- Utility costs (if able to be determined) as dollars per pound of clean linen produced.
- Linen replacement in dollars per pound.
- Total cost to produce a pound of clean linen.
- Hours worked without a lost-time accident.
By tracking these data, and either comparing these numbers to other “similar” operations, or simply monitoring same after operational modifications are made, the laundry manager can more effectively manage and direct the successful outcome of their individual operations.
Check back tomorrow to hear from distributor and textile experts.