How Opportunity Cost Is Applied in Life
Posted: Mon Jan 06, 2025 6:36 am
Another point, C, shows a situation where a larger volume of production is possible, but resources are currently underutilized.
D represents a point that cannot be reached because the company's current capacity does not allow it to achieve the stated values of products X and Y.
Plotting a production possibilities curve not only cambodia whatsapp phone number helps visualize the relationship between two products, but also allows a company to optimize its processes to find the balance that will allow it to use its available resources efficiently.
In life, as in economics, every decision we make has consequences that may not seem obvious at first glance.
Let's imagine a situation where you have to choose between learning a new profession through courses and continuing to work in your current position. This choice may seem simple. However, there are many factors to consider when making a decision.
If you decide to take courses, you will face the need to combine studies, household chores and work. Such a regime is unlikely to pass without consequences: you may face fatigue, stress and lack of sleep.
Losing your comfort zone, stability, and familiar surroundings is an example of the opportunity cost of your decision in real life.
On the one hand, getting a new specialization can open up prospects for career growth and increased income. On the other hand, you will have to sacrifice your comfort.
By staying in your current job, you will continue to enjoy the familiar environment, stability and peace, but you risk missing out on opportunities for personal and professional growth.
In this case, the cost of not growing is expressed in the unchanged level of income and limited career prospects.
To make a more informed decision, you need to analyze what exactly you are willing to lose or change for the sake of potential gain.
Understanding the cost of not growing will help you more clearly understand the pros and cons of each option and make the decision that will be best for you in the future.
At the same time, artificial intelligence is already capable of clearly determining what exactly the problem is. Moreover, AI can either solve it itself if it is a simple problem, or explain in plain language to the call center manager what the essence is and promptly suggest how it can help the user.
On the topic. The rules for issuing interest-free BNPL installments have been proposed to be changed
The second promising area of AI application is risk scoring. BNPL has a fairly low marginality — no more than 3-4% — which means that scoring is becoming an important part of the business model.
Since BNPL is not a credit product, players in this market are building their own alternative models to predict solvency.
Thus, based on alternative data, such as geolocations, purchases on marketplaces and taxi ratings, players such as Yandex can create scoring models at the level of traditional banking ones.
Creating such models requires analyzing thousands of parameters, and these are exactly the tasks that artificial intelligence can handle faster and more efficiently than we can. That is why banks are actively implementing artificial intelligence, which helps them work more efficiently with large volumes of data.
D represents a point that cannot be reached because the company's current capacity does not allow it to achieve the stated values of products X and Y.
Plotting a production possibilities curve not only cambodia whatsapp phone number helps visualize the relationship between two products, but also allows a company to optimize its processes to find the balance that will allow it to use its available resources efficiently.
In life, as in economics, every decision we make has consequences that may not seem obvious at first glance.
Let's imagine a situation where you have to choose between learning a new profession through courses and continuing to work in your current position. This choice may seem simple. However, there are many factors to consider when making a decision.
If you decide to take courses, you will face the need to combine studies, household chores and work. Such a regime is unlikely to pass without consequences: you may face fatigue, stress and lack of sleep.
Losing your comfort zone, stability, and familiar surroundings is an example of the opportunity cost of your decision in real life.
On the one hand, getting a new specialization can open up prospects for career growth and increased income. On the other hand, you will have to sacrifice your comfort.
By staying in your current job, you will continue to enjoy the familiar environment, stability and peace, but you risk missing out on opportunities for personal and professional growth.
In this case, the cost of not growing is expressed in the unchanged level of income and limited career prospects.
To make a more informed decision, you need to analyze what exactly you are willing to lose or change for the sake of potential gain.
Understanding the cost of not growing will help you more clearly understand the pros and cons of each option and make the decision that will be best for you in the future.
At the same time, artificial intelligence is already capable of clearly determining what exactly the problem is. Moreover, AI can either solve it itself if it is a simple problem, or explain in plain language to the call center manager what the essence is and promptly suggest how it can help the user.
On the topic. The rules for issuing interest-free BNPL installments have been proposed to be changed
The second promising area of AI application is risk scoring. BNPL has a fairly low marginality — no more than 3-4% — which means that scoring is becoming an important part of the business model.
Since BNPL is not a credit product, players in this market are building their own alternative models to predict solvency.
Thus, based on alternative data, such as geolocations, purchases on marketplaces and taxi ratings, players such as Yandex can create scoring models at the level of traditional banking ones.
Creating such models requires analyzing thousands of parameters, and these are exactly the tasks that artificial intelligence can handle faster and more efficiently than we can. That is why banks are actively implementing artificial intelligence, which helps them work more efficiently with large volumes of data.