What is the 1-10-100 Rule? The Hidden Cost of Supply Chain Data Errors
By Steve Hatajlo
Two business professionals (and active academics), George Labovitz and Yu Sang Chang, published the 1-10-100 rule in the book, Making Quality Work: A Leadership Guide for the Results-Driven Manager. The concept was that the cost of fixing defects escalates at different stages of a process.
The basic idea is:
- It costs roughly $1 to prevent a data entry or error.
- It costs $10 to correct an error once it’s inside your system.
- It costs $100 when bad data or errors travel far enough to cause real operational damage.
The numbers are a general framework. And after three and a half decades of building supply chain data systems, I can say the concept has pretty much held true.
What People Are Missing
A ton of publications, think pieces, and blog posts have been written in the last 20+ years that talk about the consequences of bad quality data for businesses. We’ll call that the $100 category, where everything goes through your system, and you only find out about the errors after everything is finished.
However, the $100 category is not the biggest problem. What people forget to focus on is the $10 category where their organization absorbs the cost. This often happens where error correction has quietly become normalized as part of the process. Many organizations we’ve worked with initially settled into the attitude that the $10 category for correction was the “cost of doing business,” but it’s a significant problem costing those businesses time and money.
What Ignoring That $10 Category Can Mean for Your Business
The $10 category catches errors or issues in the middle of your order-to-cash process. It’s things like the rejection of functional acknowledgements and invoices due to a manual entry error. The invoice had an invalid product code, the wrong distribution center, or the wrong units of measurement.
If you’re lucky, someone on the fulfillment team identifies the error quickly enough to correct the record and resubmit before the goods ship; or the accounts payable clerk identifies an error before the wrong amount is paid. If these daily errors aren’t caught, the business loses money.
According to APQC, the best-performing companies resolve invoice errors in three days or less. for everyone else, it’s closer to a week or more. That’s time you’re not getting paid.
Why don’t more people identify these problems? Because they’re hidden.
The reason this is hard for businesses to address directly is that the cost doesn’t concentrate in one place. It spreads across the organization in hours spent, IT work, and following up with vendors and trading partners.
For some suppliers, the costs don’t become real until they land their first major retail account. They’ve been sending invoices by email for years, their regional customers never complained, and the process worked well enough.
Then they get on board with a major retailer, ship their first big order, and 30 days later there’s a line item pulled from their payment, a compliance fee for a missing ASN, an invoice rejection penalty, or a chargeback for a unit-of-measure mismatch that nobody caught. By the time someone does the math, it’s usually too late. The business realizes they’ve left more money on the table in deductions, time, and labor.
It’s a hard lesson to learn but doing a root cause analysis to discover the hidden problems is useful, even when it stings. It makes the cost visible in a way that your internal metrics often don’t.
So, What Can You Do?
One way to fix the problem is implementing a solution that provides a safety net at the beginning of the process before you hit that $10 or $100 category.
If we look at invoices alone, fixing errors due to manual data entry can cost anywhere between $10 and $30 based on the industry. That’s without adding in time and labor your AP team needs to manage error and exception handling.
In terms of solutions, you have a couple of options:
If you’re transmitting data via EDI, that means you can implement data integration solutions that handle things like validating the fields that retailers reject: unit-of-measure mismatches between the purchase order and the advance ship notice, missing DUNS numbers on an invoice, distribution center codes that don’t match the retailer’s current location file. These validations run should be worked into the beginning of the process, not on the return trip after functional acknowledgement comes back as a rejection.
How I’ve used 1-10-100 to help control the downstream costs
At FSI, we automate the manual steps like inputting orders and invoices for our customers. We solve problems at the “1” stage of the process, helping trading partners interact digitally, or by extracting the data using technology where you might have input data by hand.
These processes put the work in up front, using machine learning combined with active “human-in-the-loop” monitoring to create a system for you that over time can help flag the wackiest errors and accommodate unique trading partner rules/formats. This prevents costly errors down the road.
If you don’t use electronic POs or Invoices today, you can still move your data accurately and effectively.
There’s a term called EDI, which stands for electronic data interchange—which refers to automated exchange of business documents between organizations’ computer systems in a standardized digital format. There are several ways to accomplish this, through a direct connection or network, and we see interchange moving toward API-based exchange between cloud-based systems.
FSI has solutions that fill in the gaps for all types of supply chain businesses. It’s very common to see a company that has adopted EDI workflows that trade with businesses that have not. For the non-EDI crowd, we’ve built custom web EDI portals for some, while others find that having our services team process inbound PDFs, faxes, Excel spreadsheets attached to an email and other formats…mapping and transforming them into clean, validated outbound transaction. You don’t have to change the way you work, and your data arrives at the retailer’s system correctly formatted, with the right fields, the first time.
Continuous Improvement is a Must
As technology changes, we continue to improve and modify the way we process data for our customers. FSI takes the promise of 99.95% accuracy seriously, and we know that the speed of your business is accelerating. When we take on the responsibility at the first phase of the 1-10-100 quality cycle, that means that we add machine learning and AI where it makes sense and keep the human in the loop.
If you’d like to take a look at the manual processes that might be quietly impacting your workflows and see if FSI can help improve the downstream results, we’d be happy to see if working together makes sense. Just because things seem to be working fine, doesn’t mean that there aren’t problems within your order-to-cash process that couldn’t be improved.
Implementing automation solutions can help catch errors at the source, where the cost is low, so you avoid the cost multipliers at each handoff.