Lean Supply Chain and Logistics Management, page 4
CHAPTER 3
The Eight Wastes: Waste Not, Want Not
What Is “Waste”?
Many people think they already know what “waste” in a process is as a result of always hearing about government waste. While there are some similarities, it is not really the same. In fact, waste in the way we mean is a different way of thinking to most people. The idea of thinking of a process in terms of value-added versus non-value-added or wasteful activities is easy to understand and definitely makes it easier to identify and eliminate waste.
The most common way to describe these non-value-added activities is by using the concept of the seven wastes, which we’ll get to shortly. Some like to add another waste (behavioral) when discussing the topic. In general, waste can be defined as anything that does not add value to a process. Typically, when a product or information is being stored, inspected, delayed, is waiting in line, or is defective, it is not adding value and is 100 percent waste.
The original “seven wastes” came from the Toyota Production System (TPS), discussed earlier. The seven wastes include unnecessary Transportation or movement, Inventory, excess Motion, Waiting, Overproduction, Overprocessing, and Defects or errors. A good way to remember this is the acronym TIM WOOD. You can also add the eighth waste of Behavior (or underutilized employees) to this as it can sometimes be the biggest waste of all.
These wastes are applicable to any process, whether it is manufacturing, administration, or supply chain and logistics. What follows are descriptions of each of the wastes, as well as some examples.
The Eight Wastes
Inventory Waste
It is best to go out of the Tim Wood order when reviewing the eight wastes, and start with inventory, as it is both the most visible and is actually an end result of the other wastes.
Inventory is a buffer between suppliers, manufacturers, and customers and is needed to compensate for lead times (e.g., in transportation, manufacturing, etc.) and variability in the system, such as forecast errors, late deliveries, setup times, scrap or rework, quality problems, and downtime.
In an office environment, inventory might refer to information, such as customer orders, or supplies, but is still just as important as it directly impacts the cycle time mentioned previously in Chap. 2.
There are four kinds of inventory:
1. Raw materials—Typically purchased materials and components.
2. Work-in-process (WIP)—The transformation process has started but has not yet been completed.
3. Finished goods—Finished, saleable products.
4. Materials, repairs, and operations (MRO)—Inventory for equipment spare parts and supplies.
All of these types of inventory cost money to maintain. This is called holding or carrying costs. These costs can range from 15 to 30 percent of the value of a product and include cost of capital (i.e., borrowing costs or opportunity cost lost if the money was invested elsewhere), taxes, storage, insurance, handling, labor, obsolescence, damage, and pilferage.
For example, if a business bought $100,000 of a raw material, had holding costs of 30 percent, and did not use the material for a year, it would have actually cost the business $130,000.
In reality, businesses need some inventory and typically have to balance the tradeoff between the cost of carrying inventory and customer service when determining how much.
There is the old analogy of a boat on the water, with the level of the water representing the amount of inventory and the jagged rocks below representing variability (Fig. 3.1).
Figure 3.1 Need to reduce variability.
Excess inventory is really a “symptom” of the problem. It is often said that the idea is to lower the water level until the “rocks” show above the water. In fact, in many companies, the finance department will pass an “edict” to lower inventories by x percent by year end, which may expose the rocks, but can also create significant customer service problems. It is perhaps more conservative, but more effective to take the opposite approach. Instead, identify the sources of variability and then, using analytical tools (described in more detail in Chap. 6), such as the Pareto principle (also known as the “80/20” rule), root cause analysis, and the “Five whys” (keep asking “why” until you get to the root cause), reduce or eliminate the variability and then reduce the inventory levels.
Transportation or Movement Waste
This type of waste can include transporting, temporarily locating, filing, stocking, stacking, or moving materials, people, tools, or information.
Ideally, when material is received, it should only be touched once to put it away and another time to pull it for consumption. However, the reality is that it rarely happens this way. Material may be moved from one place to another on the floor, put on a storage rack, pulled to remove some material, then returned to a different rack, etc. All of this excess movement is wasteful. Companies are not only paying a forklift driver to move the material, but each time it is moved, damages may occur, and each time material is moved, inventory accuracy may be affected. When material is returned to a different spot, there is the risk of losing it and accidentally ordering more (yes, that does happen).
In many cases, transportation waste can be something very obvious that you just learned to live with, like the copier being too far from your desk, paper and staplers kept too far away from the copier, no signs identifying areas or departments, or just simply poor office layout.
That is why the “foundation” concepts of layout and visual workplace are so important, and these will be described in more detail in Chap. 5. When looking at layout, think of “flow.” This is important whether we are talking about a manufacturing facility, office, or warehouse.
Motion Waste
The concept of motion waste is best described by the idea of having things you use more often closer to you (and at waist level) and things you use less often further away and higher up. Any motion that does not add value to the product or service is wasteful.
The Lean concept of point-of-use storage is applicable here. It basically means having just enough material or information nearby, which can be replenished when needed from further away (a kanban, which will be discussed in Chap. 6, is an excellent visual tool for this type of replenishment).
Some examples of motion waste are looking for tools, excessive bending or reaching, and materials placed too far away.
When thinking about motion waste, the term ergonomics should come to mind. Ergonomics is the science of how humans interact with equipment and the workplace. So in terms of motion, you don’t just want to consider efficiency, but safety as well (i.e., avoiding back injuries, carpal tunnel syndrome, etc.).
Waiting Waste
The waste of waiting is simply time spent waiting on materials, supplies, information, and people that are needed to finish a task. Everyone, whether on the shop floor, in a warehouse, or in an office can easily identify with this type of waste. It is both frustrating and counterproductive.
In most processes, a great deal of a product’s or service’s lead time is spent on waiting. In many cases, the waiting is caused by the next operation. This can be a result of long setup times, large batch sizes, and downtime. The result can be larger than needed amounts of WIP inventory.
In an office environment, time can be spent waiting on equipment to start up, printer or computer breakdown, signatures, employees on different work schedules, and even meeting attendees not showing up on time (which never happens, of course).
In many warehouses or distribution centers, products can sit “waiting” between different steps in the process (e.g., receiving, putting away, replenishing, picking, packing, and shipping).
Overproduction Waste
Overproduction, and its sinister sibling, overprocurement, is manufacturing, ordering, or processing something before it is actually needed. This typically results in an excess of another major waste already mentioned, inventory (raw, WIP, finished goods, and MRO). In addition, this can result in longer than necessary lead times, higher storage costs, and potentially a greater amount of defects (which may be harder to detect) because of larger-than-needed batch size.
Overproduction inhibits the smooth flow of materials, a basic tenet of Lean. Instead of Just in Time (JIT, discussed in Chap. 2), it ends up being Just in Case!
In the office environment, this may involve preparing or printing paperwork earlier in batches as a result of long setup times (yes, there are setups in the office as well as the shop floor!), preparing a report early, or in its entirety instead of online or as an exception report, and memos and e-mails that copy “the world.”
The warehouse may suffer from some of the office-type overproduction wastes, as well as others like pulling orders earlier than needed or ordering supplies and packaging materials in large batch sizes, for example.
Overprocessing Waste
Overprocessing happens when too much time or effort is put into processing material or information that is not viewed as adding value to the customer. This can also include using equipment that may be more expensive, complicated, or precise than is actually needed to perform the operation.
This may occur when there are unclear customer specifications, a product or service is continually refined beyond what the customer wants or needs, or a lengthy approval process is involved.
Examples of this can be overpackaging (ever open a Christmas toy for a child and wonder if all of the packaging materials were really necessary and what a “waste” they are from an environmental perspective?) and overchecking.
In the office, overprocessing can include things like sending the same information in multiple formats (fax, e-mail, and overnight delivery), repeating the same information on different forms, reentering data, and unnecessary information on a form.
Defect or Error Waste
In manufacturing, the waste of defects primarily refers to repairing, reworking, or scrapping materials. The further along that a defect gets, the more costly it is to the company as they may need to rework it into the system, scrap it and make it all over again, and in the worst case, have it returned from the customer (which can include safety and liability issues as in the Tylenol and Toyota recalls, for example). A lot of extra, non-value-added activities take place as a result, such as quarantining, reinspection, and rescheduling, possibly resulting in overtime and, ultimately, lost capacity.
In the office and warehouse, this can be errors such as those made during data entry, receiving, and picking and shipping the wrong product (or the right product, but to the wrong customer). This can be the result of a lack of standardized work and a lack of a visual workplace (to be discussed later, but can include no checklists, forms, or directions), poor lighting, and lack of training.
There are many causes for this type of defect, such as poor processes, too much variations, supply issues, insufficient or improper training, tools and equipment not properly calibrated or precise, bad layouts, excessive or unnecessary handling, and inventory levels that are too high (e.g., sits around longer so more potential for damage).
Behavioral Waste (or Underutilized Employees)
Some add an eighth waste of behavior. This is critical to consider, as you need employee creativity and participation to eliminate the other seven wastes. However, in some companies, there is a culture of not wanting to question things, not taking risk, or not rocking the boat. You might hear someone say, “This is how I was shown how to do it,” or “We’ve been doing things this way for years.” If you’re going to have a successful Lean journey, this type of behavior is unacceptable and must be changed. A company’s culture will be discussed later in more detail, but suffice it to say, a culture of team-based continuous improvement is a must.
You must fully utilize and leverage employee knowledge and skills, and offer proper training and opportunities for advancement to guarantee success.
Thinking Differently
As you can see, the concept of waste in Lean thinking is not really that complex. It is really just a different and easy way of looking at things. Once you start thinking this way as a team, it becomes easier to see where waste lies in your business. The next step is to take a step back and see where some of these wastes might exist in your supply chain.
CHAPTER 4
Lean Opportunities in Supply Chain and Logistics: Forest for the Trees
Sometimes we are all so busy “fighting fires” that we can’t see the inefficiencies in our own system that may cause the fires in the first place. Lean teaches us to take a step back, take a deep breath, and get to the root cause of the fires.
For the purposes of this book, the SCOR (Supply Chain Operations Reference) model discussed in Chap. 1 works best to organize our thoughts on the subject (i.e., Plan, Source, Make, Deliver, and Return). We will look at some of the areas of waste in the supply chain and logistics management function in this chapter and then in Chaps. 5 and 6 describe some of the tools that can be used in the battle against waste in the supply chain.
Plan
A good plan must include a good understanding of current and future demand. In many businesses, forecasts drive the entire business. Forecasting is actually a mix of art and science, and many companies have spent tens of millions of dollars on expensive, complex systems, and then later blamed the system itself for bad forecasts. The classic example as described in “Beware the Promises of Forecasting Systems” by Ben Worthen [www.cio.com, 2003] is the Nike disaster in 2000, in which the company ended up writing off $400 million of inventory because the system had been so inaccurate. The “state of the art” forecasting system did not communicate well with Nike’s existing systems, and in fact, some of the data had to be entered into the new system by hand, which increased the chance for data entry errors. The system was used as a kind of “black box,” generating automated forecast projections, which had high rates of error. Nike ended up ordering $90 million worth of shoes that were very poor sellers, as well as having an estimated $80 to $100 million shortfall on its more popular models.
As a result, Nike’s stock plummeted. Could this have been avoided? Of course. Many people like to just “press a button” and get results. The problem with having a black box that automatically generates forecasts is that no human input is involved.
Most, if not all, best-in-class companies know that the forecasting process is collaborative in nature. All forecasts are wrong—it’s just a question of how wrong. Targeting and minimizing variability is key. A good collaborative forecasting process typically uses solid but straightforward models like time series and linear regression to give a decent baseline statistical forecast, which then is reviewed by the planner (on an exception basis) and aggregated (in various forms such as family, class, etc. and different units of measure) and then shared and reviewed with different parts of the organization for further enhancement (e.g., Fig. 4.1). Feedback, including point-of-sales (POS) data and forecasts from customers, is critical in this process as well (and will be discussed later in Chap. 13, when thinking outside the “four walls” and discussing collaborative planning, forecasting, and replenishment or CPFR). Accurate and timely feedback can minimize or avoid some of the bullwhip effects mentioned in Chap. 1.
Figure 4.1 Forecasting screen.
It is also critical to set and measure forecast accuracy targets. As a result, it can be helpful set accuracy targets by ABC code. This uses the Pareto principle (or 80/20 rule), which states that a small number of items typically generate a large percentage of sales and/or profits (e.g., Burger King’s Whopper, fries, and Coke). The A items, as they are the biggest sellers, typically have a tighter band of forecast accuracy (target and actual), but also require more time spent in terms of developing forecasts as they are so important to the company. They have relatively small days of supply of inventory as a result of their high volume and inherent forecast accuracy, as well as the fact that they are manufactured or ordered more frequently. C items (and to a lesser degree, “B” items) typically sell in small amounts and are more volatile, so they require wider forecast bands of accuracy and less time spent on them (to partially make up for this, a company may decide to keep many days of supply of inventory, which might not really amount to much anyway as they are small sellers).
Wastes in Forecasting
Some wastes that can occur in the forecasting process are found in both the process itself, and as a result of the process (i.e., bad forecasts). They include:
Letting the system run on its own—A good example of this is HAL from the movie 2001: A Space Odyssey. As mentioned in the Nike case, this can result in disaster. Human training, collaboration, and intervention are critical.
Using budgeted forecasts for operations—Many companies use budgeted forecasts (usually from sales and/or marketing) for forecasting and do not even bother to update them during the year. The obvious problem with this is that:
The forecasts were developed manually and from a subjective viewpoint. A good rule of thumb in this case is to take forecasts supplied by the sales group and divide them in half, which may give you a reasonable forecast.
