SCDigest editorial staff
The News: Preliminary Research out of Georgia Tech finds there’s a lot more variability on inbound deliveries than many companies may realize.
The Impact: Variability in lead time performance clearly leads to excess inventories, inventory shortages, or both, impacting the bottom line significantly in either case. Yet, evidence is most companies don’t really have a handle on lead-time variability, and that’s its wider than most companies might guess. Georgia Tech is now offering an opportunity to benchmark your lead time performance against others.
The Story: Professor Don Ratliff of Georgia Tech has been focusing research in the area of lead time variability – how long and with what consistency – it takes to receive goods or materials from suppliers. Always an important issue, it has taken n still greater importance with offshoring and longer supply chains.
At the most recent Georgia Tech Supply Chain Executive Forum, Dr. Ratliff provided attendees with some early research into lead time variability, and called for companies to participate in a benchmarking program in lead time variability being offered by The Logistics Institute at Georgia Tech.
Ratliff noted that not only does lead time variability impact a variety of supply chain cost and performance metrics, the impact of variability is actually greater the more efficient a company’s supply chain is.
“A company with low inventories and a high number of turns is at more risk from variability than one with high buffer stock,” he said.
Ratliff has been working with a small number of companies thus far to get data on lead time variability from the time a shipment leaves a supplier to when it arrives at the buyer. One company provided a significant amount of data, Ratliff said, and while it is only a single example, the level of variability was surprising. He believes more companies need to analyze lead time performance.
For one of the studied company’s international routes, for example, from Livorno, Italy into the port of Savannah, the minimum lead time for actual imports in this lane was 8 days, while the average was 15, and you had to go to 21 days to include 95% of all inbound deliveries. This represents substantial variability, Ratliff said, and included only logistics-related variability – not variability in the purchase order to shipment process, which would add further lead time uncertainty.
Surprisingly, Ratliff’s research example, which he said is from a “company with a well-run supply chain,” even had a reasonable amount of variability in shipments coming in through air cargo delivery, most likely due to issues in clearing customs and related problems in the origin port.
Ratliff identified several causes on inbound lead time variability:
- Transportation schedules
- Capacity limitations
- Equipment shortages (e.g. rail cars, especially for shipments into ports in the west that are moved via rail to the east)
- Data errors that delay processing
- Labor issues
Ratliff said he believed growing security processes and requirements are likely to only exacerbate the variability problem.
Ratliff announce a benchmarking program in which companies can submit lead time data across a variety of lanes and transportation modes, and receive comparisons and analysis back about how their supply chain is performing in terms of variability. The program is free, and all data will be completely confidential, Ratliff said.
For information, contact Don Ratliff at Georgia Tech. Send a note at the Feedback button below for Dr. Ratliff’s email address if you are interested.
Do most companies have a handle on lead time variability? What do you think are the biggest factors? What are the keys to reducing lead time variability? Let us know your thoughts.