Unlocking the Power of Decision-Making with Expected Value of Perfect Information Formula

Making the right decision is always crucial, irrespective of one’s personal or professional life. In general, decision-makers analyze different scenarios and choose the one they believe to be best. However, oftentimes, even a well-calculated decision might lead to unfavorable results. The reason behind this could be incomplete information. Therefore, decision-makers must strive to gather as much information as possible before cementing their decisions. But, is it always possible to gather complete information? In this article, we will explore the Expected Value of Perfect Information (EVPI) formula that decision-makers can use to improve their decision-making process.

What is the Expected Value of Perfect Information Formula?

EVPI is defined as the maximum amount a decision-maker should be willing to pay to acquire perfect information before making a decision to ensure optimal results. To calculate EVPI, the decision-maker must first know the expected value of the decision without any additional information (EV) and the expected value of the decision provided with perfect information (EVP). Additionally, they must also take into account the cost of acquiring perfect information (CPI). The formula for calculating EVPI is:

EVPI = EVP – EV

Or,

EVPI = CPI * P(Perfect Information)

Where P(Perfect Information) is the probability of obtaining perfect information.

Why is EVPI Important?

EVPI is vital as it helps decision-makers determine the maximum cost they should incur to obtain additional information. In many cases, information comes at a cost, whether through research or consultation. Hence, decision-makers must evaluate if the cost of acquiring additional information justifies the potential benefits of having that information.

How to Use EVPI?

Suppose a company is deciding whether to launch a new product in a foreign market. The cost of launching the product is expected to be $500,000. The decision-makers evaluate that they have a 60% chance of making a profit of $1,000,000, and a 40% chance of making a loss of $300,000. However, they identify that if they had perfect information, their expected profit would either be $700,000 or $800,000, depending on the market’s demand. To acquire the market demand information, the company can conduct surveys, focus groups, or hire market research companies, with a cost of $100,000.

To calculate the EV, the company must multiply the probability of each outcome by its respective profit or loss and sum up the results.

EV = (0.6 * 1,000,000) + (0.4 * -300,000) = $420,000

To calculate the EVP, the company must determine the probability of each outcome if they had perfect information and the profit or loss associated with it.

EVP = (0.3 * 800,000) + (0.7 * 700,000) = $735,000

To calculate the EVPI, the company must subtract the EV from EVP and these results in:

EVPI = $735,000 – $420,000 = $315,000

As the cost of acquiring perfect information is $100,000, the company should go ahead and obtain additional information as the maximum value worth is greater than the cost of obtaining such information.

Conclusion

Decision-making is a crucial aspect of both personal and professional life. By understanding and using the Expected Value of Perfect Information formula, decision-makers can improve their decision-making process. The formula provides a framework for decision-makers to evaluate the potential value of acquiring additional information by comparing the potential gains from obtaining that information against the costs of acquiring it. By using the formula correctly, decision-makers can make better-informed decisions, leading to better outcomes for themselves, their teams, and their organizations.