This article takes issue with the Emissions Trading System (ETS) put in place by the EU. Pricing the emissions of various fuels into the equation will induce fuel users to use cleaner fuels in some cases. The argument goes that such process, based on greenhouse gas (GHG) emissions from the fuel, will be compromised by the lack of availability of cleaner fuels until sufficient supplies are readily available. And the process considers only greenhouse gases and not the lifecycle costs of certain fuels.
Perhaps the pricing scheme can be adjusted. Certainly there will be more investment in cleaner fuel capabilities. But the issues brought up are real. Just how significant they are is yet to be seen.
One real issue, however, is the fact that maritime operators can avoid fueling at EU ports and places where the ETS price is added. They can choose routes where dirty fuels can be burned, and minimize their time sailing where ETS is enforced. One way to reduce this is to create green corridors, where use of clean fuel is mandatory. An example is the Singapore to Rotterdam corridor backed by those governments.
Lora Cecere, the Supply Chain Shaman, has given us once again something to think about– big time. She goes off on some of the current fads in supply chain that she thinks are not worth pursuing.
It’s always wise to listen to Lora. She has a wealth of experience and many years of consulting with top companies to inform her thinking.
Here are some of her dead-end streets that you should be avoiding.
DDMRP (demand-driven material requirements planning)
She believes future applications are adaptive and distributed. Read the article to see what she means, and how those two keywords play out.
The SCOR methodology she claims is useful in devising a new approach to planning. Figure 3 shows an outside-in model of planning for a company.
I’m particularly intrigued by her comments on dashboards. I’ve felt they were more about visibility than improving processes. While some of that is necessary, the real value will be if you can make changes quickly. And most dashboards, I’m afraid, don’t let the operators do that. They look cool but don’t help making critical changes.
Her remarks about real-time planning are also on point. If you rerun too frequently, the plans thrash— they oscillate between one action and another completely different one. There is value in following a consistent pattern and making slow changes rather than swinging back and forth. We saw that in spades during the Covid epidemic. Look at the auto manufacturers who canceled their chip orders and then six months later could not place them again because the capacity had been diverted to other chips that were more profitable as it happened. Acting too quickly caused them anguish that has persisted for three years now. Reruns generate noise that affects partners and destroys relationships.
I also share her skepticism about DDMRP which bases an entire manufacturing progression on orders. It’s better than not looking at orders, but it fails to capture the richness of what might happen in the future. We can point to the same auto manufacturers and see that they have hundreds of cars in an ‘almost-complete’ state while they wait for certain electronics to be delivered.
And she provides some good references on checking how forecasting is improved by getting the customer’s forecast in advance. Statistical tests indicate that for the most part they are not helpful. What characterizes the few that are? That’s worth research.
And finally, salesmen are the worst forecasters. First of all, they’re liars. And the best ones are the worst liars. Why? Especially if they are paid on commission, or via a plan that pays for meeting targets or provides spiffs for beating them, they will try to get the target set low. And for commission sales often they are not guaranteed, as to size especially. So the salesman might predict low-ball, because he’s sure he will get that as a target. Then the big order comes as an extra. But for manufacturing planning, that is not reality. Often big orders do not come exactly when anticipated, so they might not fall at quarter end when the financials are due. Timing is harder to predict than size.
In the past at a mid-size manufacturer, we had better luck eyeballing a steady rate of production from history (moderated by some anticipation of the future market) and then trying to get salespeople to tell us about big orders and when they anticipated them. We laid the big order forecasts on top of the ‘run-rate’ forecast to determine the timing of production. A few days’ change in big order timing didn’t then blow our whole manufacturing plan.
Salespeople are a good source of info about products and customers, but as manufacturing forecasters they are awful. Yet you need to cultivate them to get that key information about their expectations which is valuable.