Can you capture or even approximate the cost of quality defects? Is it possible to put a price on a true or potential product recall? For industrial organizations whose products can mean the difference between life and death, the costs can be staggering. The cost to prevent quality problems? It pales in comparison. No matter the product, the cost impact can not only be in real dollars, but reputation, market momentum, and shareholder value.
Companies invest in Quality to ensure that their product(s) and processes adhere to particular specifications and procedures. Straying from those requirements and standards frequently results in product defects, leading to wasted time, wasted materials, and multiple additional wasted resources (not to mention potential customer harm). As discussed in an earlier blog, The Pursuit of Zero Waste: Continuous Improvement to Drive Quality, waste creates non-value costs.
Introducing the 1-10-100 rule: This rule states that detecting quality problems early in the manufacturing process is less costly than catching a quality challenge later in the manufacturing process. Finding a mistake in product development costs less than in production; finding it in production costs the company less than once the product is out the door. Costs balloon by a factor of 10 each time a product problem escapes detection.
The 1-10-100 rule allows manufacturers to quickly guesstimate the impact of the cost of quality. It doesn’t make fiscal sense to wait until a product is heading out the door before conducting a quality inspection. Detecting a quality problem during raw materials inspection costs less than detecting a quality problem when the product arrives at the customers’ site. The rule implies that with each passing step, the cost of error rises exponentially.
For the sake of discussion, I argue that this rule must be extended to the 1-10-100-1,000-10,000 rule. Let me illustrate this principle in terms of hypothetical dollars and cents.
(Disclaimer: These figures do not represent real costs; the intent is to express that capturing a quality problem later in the manufacturing/distribution process increases cost by a factor of at least 10x.)
Let’s assume that detecting and resolving a quality problem with raw materials during the costsbusiness about $1.00. The bad incoming inventory from the supplier fails to enter the warehouse, and potential product processing challenges are averted. Catching a defect at the inspection phase typically has minimum overhead and labor costs.
If defective raw materials should errantly pass inspection and arrive on the shop floor, detecting and eliminating a potential resulting quality problem during the early stages of production will result in a nonconformance or deviation. When this occurs, a quality representative identifies and removes the non-conforming material from the manufacturing process. This will cost the business about $10.00. So catching a defect at the start of the manufacturing process still has fairly low machine and labor overhead costs.
If the defective materials are found to be impacting actual production, the manufacturer will initiate a CAPA (Corrective and Preventive Action). At this point, the quality issue costs the business about $100.00. For example, during the final production inspection, a quality representative discovers that sub-assembly deployed in several finished products fails to meet specifications. Since these sub-assemblies are used in several finished goods and the result of the nonconformance (NC) investigations determined a systemic concern, a CAPA is generated to corrective this problem and to prevent this problem from occurring again.
Catching a defect after the finish product has been produced has 100 percent machine and labor overhead costs. The cost of (poor) quality is rising further.
Assuming defective product makes its way through distribution and into the hands of the customer, the customer registers a complaint, and costs begin to hit the roof. Detecting and resolving a quality problem due to a complaint costs the business about $1,000. When the product fails at the customer site, it implies that all of the quality efforts employed to detect and resolve product problems failed for this customer. Allowing your customer to detect and report your product problems reflects poor quality.
Catching a defect at your customer’s site has 100 percent machine, labor, and delivery distribution costs. The customer may also replace your product with your competitor’s product and/or request that you lower your prices, resulting in future loss from the customer due to poor quality.
Failure to detect and resolve a quality problem that results in a recall costs the business about $10,000, at a minimum. Recalls are a manufacturer’s nightmare. Product recalls scream to the marketplace that the business created defective products and was imprudent in shipping them to its trusty customers. In short, those audiences may assume the manufacturer isn’t serious about quality. Recalls entail these costs: labor, machine overhead, distribution costs to the customers, distribution costs from the customer (returned product), and the intangible cost of market reputation.
Finally, you can’t even put a price on the ultimate cost: loss of life. This goes without saying.
If manufacturing budgets and operations are out of your scope and you’re more of an inventory control or distribution role player in your organization, here’s another perspective. Translate the 1-10-100-1,000-10,000 principle from dollars, for the sake of the manufacturer, into finished units, for the sake of the customer, and we can see why the cost of early-stage Quality is worth every penny.
This graphic represents the number of defective, and potentially dangerous products that could pass through each phase we’ve examined. Following the theory that detecting problems early in the quality process exponentially reduces impact by a factor of 10x, you can see how it’s possible to prevent mass quantities of bad product from entering the marketplace.
No matter how you slice it, the cost of poor quality is detrimental to the bottom line. But there are ways to swing the pendulum the other way. The cost of investing in an effective Quality Management Solution (QMS) to prevent poor quality, and instead, produce excellent quality, is just a fraction.
A truly effective, enterprise-wide quality management software solution will help maintain quality at each step of the manufacturing process: supplier quality, nonconformance management, CAPA management, complaint handling – and even support quality with related functions like documentation and SOP handling, employee training and certification, audits, and change control. Those capabilities will be enhanced through business intelligence tools so problems can be identified in advance by observing trends, and progress can be measured in real time.
With such support, the manufacturer can perform root cause analysis to deal with the real root cause of problems, thereby decreasing overhead and labor costs, and increasing productivity, process improvement, and ultimately, customer satisfaction.
In the long run, investing in a quality solution for the product lifecycle will generate immeasurable cost savings. Unlike the burdens of poor quality, uncovering the true cost of good quality is worth every cent!
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