IT firms are turning to experimental economics
When does a manufacturing company need to reduce the cost of a new mobile phone model? What is the optimal time interval between the release of new HDD models? If earlier managers relied only on their intuition, now they are assisted by modeling economic processes.
For 15 years, economist Kay-Yut ​​Chen (Kay-Yut ​​Chen) has been conducting economic experiments for HP. With the help of his experiments, he tries to predict the demand for HP equipment, tests marketing programs even before they are launched, and determines the most advantageous pricing policy for certain goods. Although the experiences of Dr. Chen saved the employer millions of dollars, but until recently he was almost the only scientist who worked in this unique field.
Everything changed after 2002, when the Nobel Prize was received by another expert on experimental economics Vernon Smith “for laboratory experiments as a tool in empirical economic analysis, especially in the analysis of alternative market mechanisms”. It was a real breakthrough. After this event, many large companies, including those from the IT industry, opened their own departments for modeling economic processes. For example, teams of economists and computer scientists at Google and Yahoo optimize auctions for keywords. At eBay, experimental economists helped develop a new feedback system for the auction service, which allowed the site to increase its turnover by 25%.
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“When things get more complicated, it becomes difficult to manage a business only with slogans,” says Stanford professor Ozalp Ozer (Özalp Özer), who recently commissioned Hitachi to experiment on determining the optimal time between the release of HDD models from the point of view of R & D production and marketing.
Experimental economics allows solving such problems that are beyond the power of classical economics. A good example of this is the famous game "Ultimatum . " Under the terms of the task, player A has ten dollars and he must divide them in any way with player B. If he accepts the offer, then everything is fine, and if he does not, then no one gets anything. Question: how much will you offer on the spot of player A?
So, according to the laws of a rational classical economy, the best offer is 1 cent, because for player B it is better than nothing, and he must agree. However, conducting experiments showed that in practice people do not behave this way. The experiment showed that the average offer size is $ 4.27, and Player B refuses 33% of the time.
This is a clear example of the irrationality of human thinking. It is these factors that experimental economics takes into account in their models. Preliminary experiments are the cheapest way to avoid big mistakes. All of them are eliminated in the laboratory.
One of Chen’s recent projects was dedicated to optimizing supply volumes for HP distributors. Previously, the production of equipment was carried out on the basis of forecasts of distributors. Nine of the largest of them, who together sell goods to HP for $ 3 billion a year, sent their forecast for purchases. The problem was that this forecast did not coincide with reality sometimes by as much as 100%, which caused chaos in the planning. Dr. Chen proposed a special reward system for distributors whose forecasts are closest to reality. As a result, the coincidence between the forecast and real purchases was increased to 80%.
For 15 years, economist Kay-Yut ​​Chen (Kay-Yut ​​Chen) has been conducting economic experiments for HP. With the help of his experiments, he tries to predict the demand for HP equipment, tests marketing programs even before they are launched, and determines the most advantageous pricing policy for certain goods. Although the experiences of Dr. Chen saved the employer millions of dollars, but until recently he was almost the only scientist who worked in this unique field.
Everything changed after 2002, when the Nobel Prize was received by another expert on experimental economics Vernon Smith “for laboratory experiments as a tool in empirical economic analysis, especially in the analysis of alternative market mechanisms”. It was a real breakthrough. After this event, many large companies, including those from the IT industry, opened their own departments for modeling economic processes. For example, teams of economists and computer scientists at Google and Yahoo optimize auctions for keywords. At eBay, experimental economists helped develop a new feedback system for the auction service, which allowed the site to increase its turnover by 25%.
')
“When things get more complicated, it becomes difficult to manage a business only with slogans,” says Stanford professor Ozalp Ozer (Özalp Özer), who recently commissioned Hitachi to experiment on determining the optimal time between the release of HDD models from the point of view of R & D production and marketing.
Experimental economics allows solving such problems that are beyond the power of classical economics. A good example of this is the famous game "Ultimatum . " Under the terms of the task, player A has ten dollars and he must divide them in any way with player B. If he accepts the offer, then everything is fine, and if he does not, then no one gets anything. Question: how much will you offer on the spot of player A?
So, according to the laws of a rational classical economy, the best offer is 1 cent, because for player B it is better than nothing, and he must agree. However, conducting experiments showed that in practice people do not behave this way. The experiment showed that the average offer size is $ 4.27, and Player B refuses 33% of the time.
This is a clear example of the irrationality of human thinking. It is these factors that experimental economics takes into account in their models. Preliminary experiments are the cheapest way to avoid big mistakes. All of them are eliminated in the laboratory.
One of Chen’s recent projects was dedicated to optimizing supply volumes for HP distributors. Previously, the production of equipment was carried out on the basis of forecasts of distributors. Nine of the largest of them, who together sell goods to HP for $ 3 billion a year, sent their forecast for purchases. The problem was that this forecast did not coincide with reality sometimes by as much as 100%, which caused chaos in the planning. Dr. Chen proposed a special reward system for distributors whose forecasts are closest to reality. As a result, the coincidence between the forecast and real purchases was increased to 80%.
Source: https://habr.com/ru/post/31636/
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