The following guest posting has been submitted by supply chain and Lean-Sigma consultant Bruce Spurgeon. Bruce and I have been colleagues for many years through our mutual activities focused around the Supply Chain Council.
I just read of a recent APQC research summary document that was subtitled: What is the value of increasing inventory accuracy by one percent? The perspective provided addressed the benefits effect of increasing inventory accuracy from 98% to 99%.
I must admit that I was somewhat surprised at the findings, as 98%, in my view is a “good number”. The study outlined the following achieved results concerning this one percent accuracy improvement:
- 7.7% increase in supplier orders delivered on time
- Faster dock-to-stock cycle times (1.56 hours faster)
- 2.25% increase in the number of sales orders delivered on time
These operational results would be welcomed in any supply chain organization and it got me thinking about two things:
1. What is the typical inventory accuracy across all companies?
2. Have we moved our focus too much to the “major” metrics such as Perfect Order Fulfillment, Cost of Goods Sold, Up and Downside Supply Chain Flexibility, etc.?
To the first question, from my work as both a supply chain manager and consultant, I would surmise that the inventory accuracy average among many organizations is less than 98%, probably closer to 95% with a wide range of deviation.
If the effect of improving inventory accuracy from 98% to 99% improves OTD to customers by 2.25%, what would the effect be if it was from 95% to 99%? Would it be linear at 9%?
I believe that the effect would be different depending on the firm’s overall business or product strategy (or lack thereof). If a company carries “extra” inventory to offset one of the above problems it could have less effect on OTD but a larger effect on inventory reduction when the inventory accuracy improved.
Regarding my second question, is there too much focus on “major metrics” and not enough focus on the needs for consistent data accuracy? Are companies paying enough close attention to the overall accuracy of their data? There are many “basic” metrics, but I would class inventory accuracy in basic data accuracy. I would also include as basic data metrics; inventory masters, bills of material, routings, customer and supplier masters, testing required, lead times, payment terms, part masters and you probably have others you would add.
A good example of basic data issues is Tyco Electronics. Tyco did a great job of implementing Lean/Six Sigma, cutting inventory, slashing lead and cycle times, increasing on time delivery to customers and reducing overall costs. About 3 years after this “transformation” the finance people noticed a disturbing trend; obsolete/slow moving inventory had been growing at ~1-2% of revenue per year which was far higher than before the Lean/Six Sigma program. A Master Black Belt was assigned the project to find and correct the problem. To make a long story shorter, the cause was basic data accuracy.
In the Lean/Six Sigma program, kanbans and cells had been created and routings, bills of material, cycle times, lead times, inventory points, etc were changed. The problem was that there was not a robust process to change all the data everywhere. The ERP system was still used to provide mid and long term forecasts to suppliers and promise dates to customers. ERP also launched the bulk of the purchase orders. Since ERP had bad data (incorrect routings, bills of material, cycle times, lead times, inventory points, etc) bad things happened. Since most cycle times were drastically reduced, parts were bought before the “real” need date, with more exposure to the high level of engineering change in the electronics business. In addition, parts that were needed were not procured and some which were not needed were procured.
The solution? Change the processes to change all the data as updated and correct the existing data base. Within 3 months 90% of the data problems were resolved and the processes robustly corrected.
Are there more companies with the same experience as Tyco?
My recent consulting work has shown some of the same type of high level focus, low level errors. In one case inventory accuracy was described as “very good”, but no one in management could give me a percentage number with documentation. The real answer was a wide range depending on location/status. Some areas were at 99% or better, while others were under 90%. This was causing high levels of expedites, substitutions, overtime. All these increased cost, but the metrics addressing delivery to the customer were excellent!
Have supply chain organizations within companies provided an adequate focus on blocking and tackling metrics like data accuracy and consistency of process? Does a higher visibility focus on major metrics “hide” basic problems?
The Supply Chain Council has a Special interest Group that is focused on using SCOR/Six Sigma/Lean in a converged methodology that is one good method to find and attack such problems. APICS has long been educating and training on the basics and has great tools and methods to avoid and/or resolve these type of problems.