# 7 Questions Designers Should Ask: When to Go with Your Assumptions vs. When to Test - Snapied

Designers are always making decisions. Some of those decisions are based on assumptions. Other times, designers need to test their assumptions to see if they hold true.

When should designers go with their assumptions? And when should they test them?

**Here are seven questions designers should ask themselves to help make the decision:**

1. What kind of assumption is it?

2. How important is it to the design?

3. How risky is it to go with the assumption?

4. What are the potential consequences of the assumption being wrong?

5. How expensive is it to test the assumption?

6. How much time do we have to test the assumption?

7. What is the likelihood that the assumption is wrong?

## 1. What kind of assumption is it?

There are two types of assumptions: those that can be verified and those that can't. Assumptions that can be verified are based on past experience or empirical evidence. They can be tested and proven right or wrong.

Assumptions that can't be verified are based on speculation or gut feeling. They can't be tested and proven right or wrong.

## 2. How important is it to the design?

The importance of an assumption depends on how central it is to the design. If the assumption is central to the design, then it's very important. If the assumption is peripheral to the design, then it's not as important.

## 3. How risky is it to go with the assumption?

The riskiness of an assumption depends on how likely it is to be wrong. If the assumption is likely to be wrong, then it's very risky. If the assumption is unlikely to be wrong, then it's not as risky.

## 4. What are the potential consequences of the assumption being wrong?

The consequences of an assumption being wrong depend on how important the assumption is to the design and how risky it is to go with the assumption.

If the assumption is important and risky, then the consequences of the assumption being wrong could be disastrous.

If the assumption is important but not risky, then the consequences of the assumption being wrong could be significant.

If the assumption is unimportant and not risky, then the consequences of the assumption being wrong could be minor.

## 5. How expensive is it to test the assumption?

The expense of testing an assumption depends on how important the assumption is to the design and how risky it is to go with the assumption.

If the assumption is important and risky, then the expense of testing the assumption could be high.

If the assumption is important but not risky, then the expense of testing the assumption could be moderate.

If the assumption is unimportant and not risky, then the expense of testing the assumption could be low.

## 6. How much time do we have to test the assumption?

The amount of time available to test an assumption depends on how important the assumption is to the design and how expensive it is to test the assumption.

If the assumption is important and expensive to test, then the amount of time available to test the assumption could be limited.

If the assumption is important but not expensive to test, then the amount of time available to test the assumption could be moderate.

If the assumption is unimportant and not expensive to test, then the amount of time available to test the assumption could be plenty.

## 7. What is the likelihood that the assumption is wrong?

The likelihood that an assumption is wrong depends on how risky it is to go with the assumption.

If the assumption is very risky, then the likelihood that the assumption is wrong could be high.

If the assumption is not very risky, then the likelihood that the assumption is wrong could be low.

Testing is essential when the results are important, the chances of different results are high, time and money are limited, and the risks of not testing are high. However, there are situations where going with your assumptions may be the better option. When the results are not as important, the chances of different results are low, time and money are not as limited, and the risks of not testing are low, then going with your assumptions may be the better option.

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