Supply chain lessons from Japan

By Gerard Cachon, The Wharton School at the University of Pennsylvania. Source: Matching Supply with Demand.

Gérard Cachon

The devastating earthquake and tsunami in Japan have again raised the issue of supply chain robustness to disruption risk, and in particular, are they too fragile? FT.com (3/15/2011) asserts that  ”Strategies that look rational for individual manufacturing companies… can create big macro-level vulnerabilities…”

The reality is that it is too costly to source every component from multiple locations throughout the world just to hedge natural disaster risks. But that doesn’t mean that companies should turn their back to the problem. The best companies follow a few intuitive steps to make their supply chains more robust. I’ll offer two.

First, map your supply chain. If you know your Tier 1, Tier 2 and Tier 3 suppliers, then you won’t have to spend one week figuring out whether you will run out of a part. Most companies know their Tier 1 supply chain, but do they know the other tiers? Do they keep track of changes to the supply chain? This information is crucial because the company that is first to work the phone to find alternative  supplies is most likely to be able to secure those supplies.  This information also gives you information that you can use to make downstream adjustments to your production. For example, should you eliminate an overtime shift or not? Should you redirect scarce parts from one plant to another? Those are difficult decisions to make and are made much more complicated if you don’t even know if you have a problem – why shut down a plant for a potential part shortage that may not materialize?

Second, before disaster strikes, map out vulnerabilities. Some components can be sourced in many locations. Some components have several months of buffer inventory. You don’t need to worry about those. But if the amount of buffer inventory is limited and it is sourced in a few locations, especially a few locations that happen to be close to each other, then you need to consider finding alternative sources or alternative parts. Maybe the conclusion is that the company needs to bear the risk – there are no effective alternatives. But maybe the conclusion is that a substitution to a less risky part is actually feasible.  Finding this substitute is less costly before the disaster. There have been reports of companies that are scrambling to qualify additional suppliers, but that could have been done before disaster struck.

Finally, one risk that will hit many companies, even if they don’t have a shortage of parts, is the risk of exchange rate fluctuations – the Yen has just hit a post WWII high against the US dollar.

 

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Why China – cheap capital?

By Gerard Cachon, The Wharton School at the University of Pennsylvania. Source: Matching Supply with Demand.

Gérard Cachon

In 2008 Evergreen Solar opened up a solar panel factory in Devens,  Massachusetts, but they just announced that they will layoff their 800 workers and move production to China (NY Times 1/14/11). Why? Well, of course, it is too expensive to manufacturer in the U.S. And low cost production is critical – the price of solar panels has fallen from $3.39 per watt in 2008 to $1.90 per watt now. Evergreen Solar has reduced its cost to $2.00 per watt, but Chinese manufacturers are producing at $1.00 per watt.

But labor is NOT the reason for the high cost of production in the U.S. – labor is a small portion of the cost to make solar panels. Nor does it seem a lack of technical skills. Instead, the issue is the cost of capital – a solar panel plant can cost $400 million and Chinese manufacturers have access to low cost bank loans.

It it is likely that there will be more movement to China for reasons other than the cost of labor.



Robots or people?

By Gerard Cachon and Christian Terwiesch, The Wharton School at the University of Pennsylvania. Source: Matching Supply with Demand.

Christian Terwiesch

Gérard Cachon

Maybe the biggest challenge for e-commerce retailers is dealing with the huge surge in sales in the fourth quarter.  How can you build enough capacity cheaply enough to satisfy the rapid growth in demand during October, November and December, only to have most of that demand disappear by January? The traditional approach is to hire lots of seasonal workers. The trick with this is to be able to train them quickly enough for them to be productive in time for when they are actually needed. The Wall Street Journal reports that one company, Kiva Systems, has a different idea – instead of hiring workers, install robots (Dec 19, 2010).  To see these robots in action, check out the video (click here).

You might assume that these robots would “walk” around a warehouse picking products, putting them into a basket and bringing them to a place to be packaged. That is what humans do. Instead, these robots move shelves of inventory around. (See the photo – the robot is the orange contraption at the bottom of the shelf.) One advantage of this system is that you don’t need permanent aisles between the inventory – the shelves can be packed in tightly with the computer controlling the sequence (so that the one pink doll you need isn’t buried deep within a sea of shelves).

The next thing you may notice is that these robots are not particularly fast. It is not like the robots move product through the warehouse at twice the speed a human can walk. However, assuming these things are reliable (e.g., treads don’t need replacing every couple of days) they don’t need to take breaks, and they are instantly trained. One downside of this system is that the robot must move the entire shelf and not everything on the shelf may be needed at one time. Humans pushing a cart around a warehouse only put into their cart what is needed at the time.

But the point of the article is how to deal with the holiday surge in demand. While a robot might replace a human, it doesn’t eliminate the problem – the company simply needs a lot more capacity in the 4th quarter. If it buys these robots, then they are likely to be idle most of the rest of the year. Seasonal employees are just that – seasonal – that is, they go into the deal with the expectation that their work will be temporary.

The article ends with an idea for making the robots more cost effective for the retailer – Kiva Systems will rent the robots to the company for just the peak demand period. But I don’t see why this solves the problem – now Kiva Systems is sitting on expensive and idle capacity for most of the year (even in the Southern Hemisphere, Christmas falls in December).  Rental systems work well when potential customers need the product at different times. Given that the 4th quarter is the same for all retailers, I am not seeing this as an idea that works. Interestingly, the founders of Kiva Systems worked previously at Webvan. If there was ever a company that invested too much in replacing human workers with technology, it was Webvan – they may have survived if they didn’t blow all of their capital on hugely expensive warehouses. That said, I suspect there are surely applications of the Kiva Systems for some retailers. But as a solution to the 4th quarter demand surge, I am skeptical.

Do we need a Manufacturing Czar?

Gérard Cachon

By Gerard Cachon, The Wharton School at the University of Pennsylvania. Source: Matching Supply with Demand.

President Obama has named Ron Bloom as a special advisor to tackle the problem of declining manufacturing in the United States (see NY Times 9/10/10):

The President said “We’ve got to get back to making things.” Do we?

Here are the arguments why the decline in manufacturing is a problem:

  • Without manufacturing we won’t be able to take advantage of emerging markets in green technology “I don’t want to see new solar panels or electric cars or advanced batteries manufactured in Europe or in Asia. I want to see them made right here in the U.S. of A. by American workers” says President Obama.
  • Without manufacturing there will not be research and development in the U.S. (which are presumably higher paying).  The argument is that R&D and manufacturing have to be co-located.
  • If R&D declines because of a lack of manufacturing, then innovation will decline and innovation is the engine of productivity growth.

And what are the causes of the problem:

  • Unfair trade practices by China and others.
  • Private equity only invest in firms that manufacturer in China because the U.S. is not “where you make things”.
  • Large U.S. companies don’t want to promote domestic production because they now produce everywhere.

So what do they plan to do about the decline? Here the specifics are thin. They have ruled out subsidies. They will focus on trade diplomacy and improved export-import financing.

Unfortunately, for Mr. Bloom, I strongly suspect he will not be able to reverse the trend, nor do we want him too. But if he wanted to reverse the trend, he is not pulling the right lever.

To fix a problem requires identifying the cause. There are two reasons why manufacturing has declined in the U.S. First, although not mentioned in the article, transportation costs have declined.  If it costs a lot to move parts and finished good around, you need to do things locally. When you can start shipping and training and trucking things for cheap, your options as to where to manufacture expand. Second, things are much more modular than they use to be. Henry Ford’s designers had to be very close to the manufacturing process because I suspect design was an iterative process – design something, try to make it, redesign it, try to make that, etc. Now, computers, telecommunications and precision machinery means that for many things the design and the production can be decoupled – an Apple engineer can dream up the next Iphone in her office and send the specs over to China without fear that what she created will be costly to make.

So if the causes are cheaper transportation and let’s call it decoupled R&D, then what could be done to reverse the trend? We wouldn’t want to ban computers to prevent the former. But maybe we should make transportation more expensive. At least that would have an environmental benefit. But if it is expensive to move stuff from China to the U.S., then it is expensive to move it from the U.S. to Europe, i.e., it cuts both ways. Which brings me back to an earlier point – should we care? Our decline in manufacturing has also occurred during a period of increased productivity and standard of living. Where is the evidence that we have been hurt by the decline in domestic manufacturing?

And let’s consider the geo-politics of trying to break manufacturing ties with other countries. If we purchase nothing from China and China purchases nothing from us, will they be more or less inclined to use their military? (For that matter, how about the U.S.’ inclination to use its military.) The answer seems clear – as long as countries are linked together via trade, the world will be a safer place.

America should promote innovation and we should make things in America that make sense to make here (like cars). But we have better things to worry about than manufacturing’s declining percentage of the economy.

The Golden Hour

By Gerard Cachon and Christian Terwiesch, The Wharton School at the University of Pennsylvania. Source: Matching Supply with Demand.

Christian Terwiesch

Gérard Cachon

Sirens and speeding ambulances are the symbols of emergency care. The basic idea is that the sooner we get seriously injured trauma patients to the hospital, the bigger the chance of their survival. The first 60 minutes after an accident are known as the “golden hour”. Getting the patient to the hospital in this golden hour is claimed to be critical. This is intuitive. But, unfortunately, this claim is not really supported by a whole lot of empirical data. In fact, the authors (who are ER physicians) of a recent Slate story discuss the statistical evidence supporting the myth of the golden hour. They discuss a recent study published in the Annals of Emergency Medicine that finds no support for the importance of extra speed.

But why then, are the ambulances driving so fast? From an operations management perspective, two explanations come to mind. First, the fact that an extra couple of minutes do not matter much in predicting patient survival rate does, of course, not imply that the driver can stop at the next Starbucks… Second, there might be an alternative explanation for the speeding ambulance. Let’s call it the NY cab driver syndrome: The faster you drive, the sooner you will be available for the next trip. After all, it is all about productivity.