Editor’s Note: Today’s post is from Dick Locke, Sourcing Innovation’s resident expert on International Sourcing and Procurement. (His previous guest posts are still archived.)
In my last post I wrote about the loosening of the controls on the value of the yuan. Since then, the yuan has weakened about 1%. That’s one of two developments affecting China sourcing.
The other, which I think will have more immediate effect, is new labor militancy among the employees of export related industries. They are realizing they are in a very strong bargaining position, because they are working for first tier suppliers of consumer products, such as computers, telephones and cars. The Apples, Dells, HPs and Hondas of the world aren’t going to stay customers of companies who take (with or without government involvement) repressive measures against labor militants.
This is unlike the situation in Mexico, where the federales broke a miner’s strike a few weeks ago. Miners are about as far back up the supply chain as you can get, so it’s unlikely the mine’s customers are going to feel consumer pressures. The mine is in Cananea, and is more or less an historic site because there was another famous government-assisted strike breaking there about 100 years ago. In that 1906 incident, the US Army got involved, 60 miles inside Mexico.
In China, the suppliers are generally conceding to labor’s demands. Will that lead to a massive departure from China? Not in itself, particularly in the electronics industry. As a rule of thumb, electronics assembly costs are 80% material, 15% overhead and only 5% labor. A small increase in labor costs at the assembly level is unlikely to be a deal-killer. That’s helpful, because resourcing all that electronic assembly work out of China is going to take years. Foxconn alone has 800,000 employees in China. Resource that!
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The black swan has been on a rampage in recent times, taking down supply chains, companies, states, and even countries in his wrath, which seems to have no end. It’s foolish to assume that he’s not coming for you, because, even if you’re not on his list, it’s only a matter of time before you are. He’s as determined as robot santa claus, and just as indestructible. But if you’re ready for him, even if you can’t stop him, you can survive the encounter, and with the right blast shield, even minimize the damage. So how do yo do this?
Nassim Nicholas Taleb’s exceptional article on The Fourth Quadrant: A Map of the Limits of Statistics has some great advice for minimizing your chances of encountering the black swan, and even minimizing the damage if you can’t avoid him. And to make sure there’s no misunderstanding, I will use plain English, and not statistics (which most people, including the “experts”, don’t really understand), in my presentation of these tips.
You can over-optimize and over consolidate. You need multiple sources of supply, multiple products, and multiple channels.
- Avoid the Long Tail
Yes you can make money in the long tail, if you’re lucky, but the further you are from the norm, the harder it is to predict what will work.
- Don’t try to Numerically Model Atypical Events
You can’t predict future stock-outs based on past stock-outs or the degree of future demand surges based on historical demand surges. They could be the same, or be off by a factor of 10. That’s why they are atypical. Address them generally, and you’ll be better off.
- Take Your Time
Only time can reveal the true nature of a cycle. Depending on what you’re trying to model, that could be months, years, or even decades. If you avoid drawing conclusions too early, you’ll be better off.
- Don’t Reward Luck
Just because someone made a foolish bet and won doesn’t mean they should be rewarded. The more extreme the bet, the more likely you are to lose. Don’t encourage ridiculous behaviour.
- Don’t Measure What Can’t Be Managed
For example, the “average time” between stock-outs or demand surges is meaningless, and it will just increase the desire for your team to “model” the situation, which will give you the illusion that you understand something you don’t, and that you don’t need to have contingency plans for “unexpected” stock-outs or demand surges because you modelled them.
- What’s the Nature and Magnitude of the Uncertainty?
In NPI, the uncertainty is that the team might fail given the resources assigned to it. The nature of the uncertainty is positive (if they succeed, you win) and the magnitude is limited to the investment. But in chemical processing, the uncertainty is that a storage tank could rupture, contaminating the local environment. The nature of the uncertainty is negative (if it the tank ruptures, the environment gets damaged to some level) and the magnitude is large (if the chemicals reach a lake or the groundwater table, the local population is screwed). Put your efforts on creating emergency plans for large negative uncertainties first, as those are the events that can bankrupt the business.
- Do Not Confuse Absence of Volatility with Absence of Risks
For example, if you look at the graph of daily variations in a derivatives portfolio exposed to U.K. interest rates between 1988 and 2008, almost 99% of the variation occurs on 1 single day — when the EMS (European Monetary System) collapsed. On almost every other day, variation was less than 1/100th of a percent. This is not dissimilar to the eruption pattern of Mount Vesuvius (which buried Pompei and Herculaneum in 79 AD). If you plot a daily graph, it’s typically flat for 30 to 50 years, until one day a massive eruption wipes out the local area. Remember, the black swan will show up where you least expect him.
- Most Risk Probabilities are Lies
A rare event that happens once every 30 years does not have a 3% chance of occurring every year. The chance is typically dependent upon whether or not there is a confluence of initiating events and factors, and could be 0.03% or 99.3%, depending. Furthermore, the presentation of a risk statistic has a significant effect on it’s impact. People are unlikely to heed a warning for anything that only has a 3% chance of occurrence, but very likely to at least give serious thought to any event that will happen once every thirty years with 99% certainty.
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