Order Picking Error Rates: What’s Acceptable?
A balance between throughput and accuracy
It’s easy to say that you’re striving for 100% accurate pick rates, but how realistic is that goal? And should it be the actual number you shoot for? Mis-picked orders, any number of them, are expensive. Incorrect orders are expensive to re-pick. They’re expensive to return and restock. Shipping dollars are lost both directions. Most importantly, mistakes are expensive because they can cost you customers.
The 2013 WERC/DCVelocity annual distribution center measures report is one place to look in general. Its findings for 2013 (the survey asked over 500 companies to provide data on over 40 metrics, including order picking accuracy), stated that median performance for those who answered was 99.5%. This is an admirable goal, but if 100% is unattainable over time, is the median score the right one to pursue?
Should your warehouse aim for 100% order picking accuracy?
Given enough time and enough money, you could achieve 100% accuracy, but should you?
It’s all about relative costs and benefits. What does an incorrect order cost? What would it cost to completely remove all errors from your order picking operation? What do you give up to pursue this goal?
If you don’t already know the cost of a mis-pick, you probably should, and that number should include all the relevant costs.
Every operation should pursue 100% accuracy, but the reality is, no one can hit that number for an extended period of time. Most companies focus on a “high bar” number, but that number isn’t 100%. What you’re looking for is the net benefit of your current accuracy rate vs. the net benefit of adding people, technology, and processes to boost your accuracy. You must measure all the costs and benefits of such a program. Does it involve more quality control people? WMS or other technology investments? Automated equipment? Thoroughly analyze the additional costs vs. the overall benefits before you undertake any process to increase accuracy.
To determine the best accuracy rate for your operation, you must understand the cost-per-error number.
Some factors in cost-per-error calculations
- The cost of a lost or disgruntled customer
- The cost of re-shipping incorrect orders
- Returns or rework costs
- Administrative costs
- Additional handling costs
- Additional shipping costs
Then apply that dollar figure to the number of errors and build a cash flow model as you search for ways to reduce your error rate in a justifiable manner. New order picking equipment such as pick light systems, voice directed picking, RF guns, or goods to person pick systems may all make sense once you understand the cost of doing nothing. Process changes, incentive programs, or additional quality checking can have significant impacts as well. The key is that the benefits or boosting your accuracy rate must exceed the costs of doing so in a reasonable amount of time.
Be careful that a relentless focus on accuracy doesn’t reduce throughput
Late orders can be as damaging as incorrect ones. The trade-off between picking accuracy and throughput is always going to be more art than science to understand.
For some industries, accuracy is simply more important than in others. I was once shipped two laptops rather than one. I returned the extra, but if I hadn’t, the picking slip only had one computer on it. I could have kept that computer. Picking $2,000 laptops correctly is more important than picking $2 packages of candy, simply because the cost-per-error can be so much higher. That $2,000 mistake isn’t worth the extra speed, but in some operations, this isn’t true. This also goes for regulated industries such as pharmaceuticals or jewelry.
The bottom line is that you must know your costs, what kind of error rate you can tolerate, and what your particular market or operation should strive for.
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Scott Stone is Cisco-Eagle's Marketing Director with three decades of experience in material handling, warehousing and industrial operations. He writes on automation, warehousing, safety, manufacturing and other areas of concern for industrial operations.