# Making Business Decisions Using Probability Information & Economic Measures

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• 0:39 Expected Value
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

Probability information and economic measures create the foundation for quantitative analysis. This lesson will provide information about how to make business decisions using this probability information and economic measures.

Jessica owns a manufacturing business, and she's considering adding another plant in a second state. The expansion could allow her company to produce more product and make more profit, but it's a gamble because it could also cost her company dearly. Should she do it?

Companies face decisions, both large and small, every day. There are many ways that business decisions can be made. One type of decision-making analysis involves using probabilities and economic measures to make decisions. To help Jessica make her decision, let's see how this type of analysis works.

## Expected Value

Jessica is wondering how she should make her decision about opening a new plant. She thinks that crunching numbers will be better than just going with her gut or with what her company has always done, but there are so many possible outcomes: the new plant could make a ton of money, or it could tank and end up causing her company to go into bankruptcy. How can she figure out the best option?

One way to do that is to use the expected value of the different outcomes, which is the weighted payoff based on probabilities. For example, if Jessica believes that there's a 40% chance that the second plant will make a profit of \$100,000 in its first year, then the expected value of that plant is \$100,000 x .4, or \$40,000.

But, let's say that there's also a 30% chance that the second plant will only make \$10,000 in that first year. That expected value is \$3,000. And if there's a 20% chance that the plant will lose \$100,000 in the first year, then the expected value is -\$20,000.

So, which option should Jessica go with when trying to make her decision? One thing Jessica can do is to add up the different options. \$40,000 + \$3,000 + -\$20,000 = \$23,000. That's the total expected value of what might happen in the first year of the plant's opening.

How does Jessica figure out the probability of different outcomes? There are two ways to calculate expected value. The first is to calculate it based on objective probability, or using actual data to figure out probability. For example, if Jessica has data that shows that similar manufacturing plants made \$100,000 profit in their first year about 40% of the time, that's objective probability; she's using actual data to figure out the probability of her plant making \$100,000 profit in the first year.

But, what if she doesn't have data to use? The other way to calculate the expected value is with subjective probability, or using a rough estimate to figure out probability. If Jessica doesn't have data (or if she has only scant data), she can make a 'guestimate' about what she thinks the probability of each outcome is.

Ok, Jessica understands how she can use expected value to come up with an estimate of how profitable her new plant might be in the first year, but there are still so many things that she can't account for! For example, right now, the economy is good and lots of people are buying her product, but what happens if there's a recession right after she opens the new plant? Can she factor in the future health of the economy when she's analyzing the possible outcomes?

There's not a way for Jessica to accurately predict what the economy is going to do, especially in the short-term. But, there is a basic economic cycle that Jessica can remember and take into consideration when she's analyzing outcomes. The economy generally goes through a 4-step cycle. It is:

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