sc digest
November 14, 2014 - Supply Chain Flagship Newsletter

This Week in SCDigest

bullet Lead Times, Out-of-Stocks and Inventory bullet SC Digest On-Target e-Magazine
bullet Supply Chain Graphic & By the Numbers for the Week bullet Holste's Blog/Distribution Digest
bullet Cartoon Caption Contest Continues bullet Trivia      bullet Feedback
bullet New Expert Insight, New Keep It Moving & Supply Chain by Design bullet New Videocast/On Demand Videocasts
FREE Calculator: Inbound Shipping Variability
Impact on Expensive Safety Stock


first thought


Supply Chain Graphic of the Week:

Levels of Distribution Center Complexity


Amazon Looking for Drone Engineers in Cambridge, UK

Google and Its Robotic Karate Kid
Nat Gas Truck Sales to Rise, but More Slowly
US-China Climate Accord Impact Overstated?


November 4, 2014 Contest

See The Full-Sized Cartoon and Send In Your Entry Today!

Holste's Blog: Maximizing DC System Performance


FREE Calculator: Inbound Shipping Variability Impact on Expensive Safety Stock


Weekly On-Target Newsletter:
November 12, 2014 Edition

Cartoon, Rail Q3 Review, India v China, Amazon Shipping, Gartner Study and more

Mexico Facilitates Trade Across Its U.S. Border Part 2

by James Giermanski,
Powers International, LLC

What Economic Impact Will the Amazon Sortation Network Have on UPS and FedEx?
by Marc Wulfraat
MWPVL International, Inc.

Three Supply Chain Lessons from the book Scaling Up Excellence

by Dr. Michael Watson


American Software, parent of today's Logility is generally recognized as having offered the first commercial version of this class of supply chain software in the late 1980s?

Answer Found at the
Bottom of the Page

Lead Times, Out-of-Stocks and Inventory

Well, I can go at this column a couple of different ways. My attempt is to connect lead-time variability, out-of-stocks, inventory performance and more.

I have been chasing this for awhile now, starting with my quest last year for a Unified Theory of Out-of-Stocks - a mission certainly not yet complete.

The term OOS usually is used in a retail context, though everyone has out-of-stock/service issues of one kind or another. But I am going to focus on the retail variety here.


"If you can quantify lead time variability, you can make more intelligent sourcing decisions, and if you can reduce that variability, you can lower inventories and keep the same service levels."


Send us your
Feedback here

The topic has been much studied in a sense in the retail sector, though the focus of the most well-known studies have primarily been related to grocery/mass merchants and the consumer packaged goods sector.

And that is one of the big issues here - the out-of-stock problem varies in many aspects - including the impact on lost sales - depending on what retail sector and product categories you are in. Not having a given size of a $50 pair of pants has a lot more financial impact than being temporarily out of a certain kind of canned soup.

And the factors causing OOSs are myriad and complex - which of course is why the problems persist.

Over the last couple of years, Walmart's former head of US store operations Bill Simon was rather famously heard complaining at store managers meetings about the OOS problem at the retail giant, saying one time there was an opportunity to increase revenues several billion dollars annually from improving the OOS situation.

Before that, he had said (paraphrasing): "We can't keep our shelves stocked and it's getting worse." Walmart was said to have created an executive level position and filled it with an outsider just to tackle the OOS challenge. All this was likely a factor in Simon's departure.

Factors impacting OOS include ordering patterns, volatile demand, safety stock and service policies, the plague of dealing with slow movers, in-store inventory accuracy, in-store logistics, lack of visibility - and vendor performance.

It is that last one I have been looking at of late. While a lot of the research has dealt with in-store execution issue, I feel like the vendor side of things - in terms of lead times and fill rates - has not been well enough examined.

Last year, the head of supply chain planning for a major US grocery chain did a presentation on the integrated inventory planning and execution process and tools the chain was rolling out - one of the most comprehensive efforts and visions I have seen.

At the end of the presentation, someone in the audience asked him: so where are the risks given this great program?

Without batting an eye, he shot back: "Vendor performance."

In other words, in the extremely leaned out, technology-driven new approach, the biggest risk now became vendor variability, not internal performance.

Of course, variability was one of Art Mesher's "3 Vs of Supply Chain," described in one of if not the most famous analyst research notes of all time back in the late 1990s. It is the bane of Lean supply chain performance, and accounts for all sorts of woes.

In consumer goods to retail, you have two primary areas of potential vendor variability: lead time and fill rates. Those two metrics are important both in absolute terms (how long is the lead time and what is the fill rate), but even more so with regard to variability, since mediocre but consistent vendor performance could be dealt with in other ways. It's why "slow steaming" in the ocean container shipping sector on its own is not such a big problem - slow but consistent.

I have also come to this basic but important realization (perhaps being the last to know):

For short lead-time supply chains, it is fill rate that matters - lead time variability is generally low

For long lead time supply chains, it is lead time variability that matters more, and in fact the lead time variability often is caused by vendors working later to fill the order completely.

These aren't universal statements, but largely accurate I believe.

One thing that has amazed me and many others as well over the past few years is how little information nearly all companies have about lead time variability. Chris Caplice and MIT had a devil of a time a couple of years ago getting data from just a few companies on their lead times and variance for a study on containers shipments into the US, as just one of many examples I have heard in the academic realm.

Also a couple of years ago, I was at a small conference where an international logistics manager for a very large retailer basically said they had little or no information on lead time variability in product coming from offshore. Merchants/buyers were given lead time ranges for specific vendor-DC combos - say 24-26 days - which they used as a guide for when to place POs.

But of course, such a range does not consider variability. So either you ignore it, and risk out-of-stocks, or you qualitatively recognize it, and order outside the state range - maybe 30 or 35 days - to protect against the variances from the average.

But if you can quantify lead time variability, you can make more intelligent sourcing decisions, and if you can reduce that variability, you can lower inventories and keep the same service levels.

On the manufacturing side, such lead time variance is often addressed through "six sigma" type programs, and possibly supplier segmentation strategies.

On the consumer goods to retail side, it is generally...less structured. The goal of reducing lead time (and fill rate) variance just isn't as pressing. Maybe it is because it is hard to quantify the opportunity.

On a videocast last year, Mark Krupnik of retail technology vendor Retalon demonstrated using actual data how a $3 billion dollar specialty retailer had the opportunity to reduce its current inventory levels by $150-300 million, based on reductions in lead time and fill rate variability it had already achieved working with Compliance Networks on vendor management, but had not yet really acted on from an inventory perspective. 

I then got the bright idea that beyond just this one-off analysis, we should create a tool that allows retailers and manufacturers to see for themselves what the impact can be.

And thus, the new "Lead-Time Variability and Inventory Calculator" was born and is released by SCDigest here today. You enter in some basic data about lead times, variance, on-hand inventory, etc., and it comes back and calculates how much inventory could potentially be reduced (if the right steps are taken) if lead time variance is reduced by increments of 10 to 50%.

Screen capture of page 1 of the calculator is below:

It is a fun tool, and shows the potential there is both to reduce vendor variability through proactive management and what that can be worth in terms of inventory reduction. It is interesting to do some "what iffing" work.

We plan to have a companion fill rate version of the tool in Q1, and might tackle also the impact on lost sales sometime in 2015.

One more step in the OOS quest. Calculator can be found here.

We covered a lot of ground here - any thoughts on Gilmore's perspectives - or the calculator? Let us know your thoughts at the Feedback button (email) or section (web form) below.

View Web/Printable Version of this Column

New Townhall Meeting:

Townhall Meeting! Is Flowcasting Really a Game Changer in the Consumer Goods to Retail Supply Chain?

Claim is that Store-Level DRP and New Approach to Forecasting Deliver Big Gains - Does It Stack Up?

Andre Martin , Flowcasting Inventor, JDA Software, Kevin Smith of DePaul University, Parag Jategaonkar of Accenture and Fred Baumann of JDA Software.

Tuesday, Dec. 16, 2014

Upcoming Videocast:

Why Now Is the Time to Close the 3PL "IT Gap"

How Leading Logistics Service Providers Can Move to the Next Level of Technology Enablement to Win New Business and Get More Strategic with Clients

Gene Tyndall, former VP of Supply Chain Solutions at Ryder, SCDigest's Dan Gilmore, and Todd Johnson of JDA Software.

Thursday, Dec. 4, 2014

On Demand Videocast:

The Impact of Vendor Lead Times and Variability on Inventory Levels

Introducing the New Lead Time/Inventory Level Calculator!

Mark Krupnik of Retalon, Kevin Harris of Compliance Networks and SCDigest editor Dan Gilmore.

Now Available On Demand


Catching up with some feedback from some First Thoughts columns over the past few weeks.

That includes an outstanding email that's our Feedback of the Week on our First Thought column on The Coming US Logistics Cost Crack-Up? from long-time transportation sector executive David Goodson.

It is detailed and long enough we will just let it stand on its own - good insight.

Feedback on Logistics Cost Crack-Up:


While I have no doubt logistics costs are going up, a 22 percent increase is doubtful. Any significant price increase will force shippers to change practices to help carrier mitigate cost increases. Also, if rates go up substantially, expect more capacity to enter the market to bring supply and demand in line. However, it takes 1-2 years for additional capacity to come into the market, so there could be some eye-popping rate increases in the short term, which will recede over time.

The article did raise some interesting points worth commenting on, and I will end with my own prediction of cost increases.

$70,000 pay for drivers is not needed to solve the truckload carrier driver shortage. This is the level of pay needed to attract the quality of driver carriers' wish they had. Moaning about how driver use to be is a staple of conversation in the trucking industry. If an average wage of $46,000 attracts enough drivers to result in at most a 5% shortage of drivers, than a 20% increase to $55,200 would surely produce enough additional drivers to fill all the trucks. We are probably looking at a 10-20% increase once demand heats up.

So far as I know, private fleets and local trucking operations don't have as much of a problem attracting drivers as truckload carriers. Still, if truckload wages go up, the increase will ripple into non-truckload carriers. So no fleet is immune.

Werner raising wages 14% means little as they have always lagged the industry in pay rates. A long time ago they adopted a high driver turnover model of training students and then paying them a low wage rate for the first few years. Most fleets used to require 3 years of over the road experience, so the students were somewhat stuck. Now carriers are only requiring six months experience, so I suspect that Werner was having trouble-keeping students long enough to make the cost of training worthwhile and is now seeking experienced driver hires.

The Teamsters are not going to organize any mega fleets in our lifetime with the exception of FedEx. After bankrupting almost all for-hire union carriers, the teamsters have never organized anyone of significance. Trucking companies who employ owner operators such as Swift, lease those drivers in states with the most favorable laws to minimize the risk of contractors ever being deemed employees. Long Beach is an exception to that rule, but drayage costs are a very small component of overall logistics costs.

The only healthy mega carrier where Teamster labor is the dominant force is UPS. So the Teamster dream of getting the other half of the small package duopoly organized. However, there have always been thousands of employees drivers at FedEx the Teamsters could have organized a long time ago, so I doubt their ability to do so now. Even if it occurred, UPS and FedEx are already jacking up rates as fast as the market will bear. So it is hard to make a case that rates will go up any faster if they both operate under the same labor contracts.

A carbon tax has no chance of passing congress. While Obama has pushed the limits of what a president can do through executive orders, he still cannot order new taxes. On the flip side, a president who promotes domestic oil production could dramatically bring down fuel costs. As most rates are still tied to a fuel surcharge, lower fuel costs will automatically result in logistics costs going down. This is one of the mitigating factors I mentioned, as a 22 percent increase in logistics costs would have shippers screaming to congress for relief, and fuel costs are the obvious place to start.

Electronic logging will have a much bigger impact that 2%. (I really don't know how any trucking company could detect a 2% change in productivity due to single factor.) Paper logging has always been the fudge factor that mitigates the loss in productivity of new regulations.

Example, if a driver sleeps overnight in a customer yard, an electronic logger starts the 11 hours driving cycle when he moves the truck to the dock. With a paper log, he probably wouldn't log driving until he leaves the shipper gate, a lost of at least a 1/2 hour of driving time. Fueling, a 20-minute activity is now counted against the 11 hours of driving time. If the driver is on an overnight run, he is going to want to bed down at least a 1/2 hour before the 11 hours are up as there is no wiggle room for error with an electronic logger. No matter how efficient shippers and carrier become, it is hard to mitigate productivity losses like these.

My guess is a 10% loss of for-hire capacity not currently electronically logging and not receiving a local terminal exception. If 1/2 of for-hire trucking capacity falls into this definition, than I expect a 5% capacity loss, which will lead to a short term spike in truckload rates. If you think I am overstating the case, you haven't been around enough over the road drivers.

As truckload drivers are paid per mile, lost miles due to the decrease in driving hours will force a 10% wage increase just to maintain a $46,000 average driver wage. Factor in another 10-20% to fill all trucks we are looking at wage increase of 20-30%. If driver labor represents 41% of logistics cost, we are looking at a 8-12% increase. That is probably the worse case, and only for heavy truckload shippers.

Even at the lowest level, I would not want to be one trying to justify an 8% increase to a CFO. When fuel drives logistics cost up, it is fairly easy to explain why to anyone who recently filled a car's tank. You cannot quickly explain to anyone why going to paperless logs has increase costs, not lower them.

David Goodson



Q: American Software, parent of today's Logility is generally recognized as having offered the first commercial version of this class of supply chain software in the late 1980s?

A: Distribution Requirements Planning (DRP).

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