There is bound to be a bigger push on the Congress and the President to do something about the high oil prices. On an election year, the candidates wanting to show they care, get in the fray with their own recommendations like Gas Tax Holiday.
A common theme across all these plans is they either seek to increase supply or reduce total price.The supply increase is recommended through, more drilling in existing fields, open up new fields in protected areas, stop adding to strategic reserve.The price control methods are just that, seeking to introduce price control, windfall taxes and eliminate taxes.
The problem is the shock is demand induced and not a supply shock. The demand is global is nature and not limited to US. When the prices rose first, it was a shock. Now people, across the world, come to expect the higher prices are here to stay and are changing their behavior like using public transit, using cattle for plowing the field (India), or working from home one day a week.
Not everyone is doing this but enough to put a dent on the demand. If the lawmakers choose to address this demand side problem by increasing supply, the demand will only increase to absorb the added supply. The price of crude is at its market clearing price and not spiralling out of control because people can make behavioral adjustments.
Adding new supply will negate these and will keep the prices at their current levels or higher and not push them any further down.
Showing posts with label Demand. Show all posts
Showing posts with label Demand. Show all posts
Wednesday, July 16, 2008
Friday, April 18, 2008
Operations is Child's Play
I spent a fast semester learning Operations.
How do you maximize profit when the inventories have to scrapped at the end of each day?
How can you predict future demand?
How do you know how much to order?
News Vendor model to the rescue, if you know the past demand history.
Kids these days learn this just by watching Cyber Chase on PBS, particularly one specific episode, aptly titled as "Past Perfect Prediction". The kids run a some sort of oil change garage to raise money. They have to order Cryoxide, the raw material that costs $15 a can and expires at the end of the day. They charge $32.5 for the service. They place an order for Cryoxide the previous day and it gets delivered in the morning.
On the first day they order 66 cans based on one receipt they find in their father's files. As it turns out they could use only 30 of the cans, wasting the other 36 cans. They figure out that that was just one data point and it was also from a Saturday whereas they started work on Monday. Their initial search gives them one past receipt for each day of the week. Not satisfied with the dataset they search more and find the receipts for the whole month. They find the average demand for each day and place a order for each remaining day of the week.
Perfect. They end up using every can everyday and end up making a wheelbarrow load of money.
Now if only I had seen this.
How do you maximize profit when the inventories have to scrapped at the end of each day?
How can you predict future demand?
How do you know how much to order?
News Vendor model to the rescue, if you know the past demand history.
Kids these days learn this just by watching Cyber Chase on PBS, particularly one specific episode, aptly titled as "Past Perfect Prediction". The kids run a some sort of oil change garage to raise money. They have to order Cryoxide, the raw material that costs $15 a can and expires at the end of the day. They charge $32.5 for the service. They place an order for Cryoxide the previous day and it gets delivered in the morning.
Past Perfect PredictionConvinced that the last piece he needs to activate his powerful new machine is hidden in Slider's garage, Hacker threatens to evict the teen unless he pays up on an old debt. Enter the kids and Digit. As a way to raise the money, they convince Slider to open the garage for business – just like his dad did. They do, but quickly discover that there's more to it than meets the eye. Can they unlock the past to find the key to saving Slider's future?
On the first day they order 66 cans based on one receipt they find in their father's files. As it turns out they could use only 30 of the cans, wasting the other 36 cans. They figure out that that was just one data point and it was also from a Saturday whereas they started work on Monday. Their initial search gives them one past receipt for each day of the week. Not satisfied with the dataset they search more and find the receipts for the whole month. They find the average demand for each day and place a order for each remaining day of the week.
Perfect. They end up using every can everyday and end up making a wheelbarrow load of money.
Now if only I had seen this.
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