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Pugh Chart: Definition & Example

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  • 0:03 Making Choices with…
  • 1:04 The Empty Chart
  • 1:58 Example Set Up
  • 2:54 Example Choosing the Best
  • 4:50 Lesson Summary
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Lesson Transcript
Instructor: Laura Foist

Laura has a Masters of Science in Food Science and Human Nutrition and has taught college Science.

There are many different ways to compare options, but in science we often want a quantitative way to compare data. The Pugh chart gives a way to quantitatively compare qualitative data.

Making Choices with Information

Imagine you are with a group of friends, and you are trying to decide where to go out and eat for lunch. There are several things you need to take into account. The price, how good the food is, how close it is, and whether they have allergy-friendly foods. How can you balance each of these concerns and find the best place to eat?

Problems like this are common in the business and science world. We need ways to compare different qualitative options quantitatively. Qualitative information are things that are described using quality or the verbal description. Quantitative means we are measuring something based on a numerical number instead of describing it. One method that has been developed to quantitatively compare qualitative choices is the Pugh chart.

The Pugh chart was developed by Stuart Pugh. Stuart Pugh was a professor at the University of Strathclyde in Glasgow, Scotland. He was a professor of design, so originally the Pugh chart was applied to deciding between design choices. It has since been applied in many different industries.

The Empty Chart

In order to understand the Pugh chart let's first look at an empty chart:


Empty Pugh Chart


In the top row we have spots for four empty spaces. There can be as many empty spaces as we want, but in this example we have four. One of these options needs to be a control, or the option that will be '0' for every criteria.

The first column is criteria. Here we list off everything of interest that we need to compare, such as price, distance, etc.

The second column is weight. Some criteria is more important than other criteria. For example, if it is your friend Jen's birthday, then perhaps her favorite place to eat will carry a heavier weight than every other criteria.

At the bottom of the chart we add everything up. We add up how many pluses, zeroes, and minuses each option got. Then we multiply the pluses by 1, the zeroes by zero, and the minuses by -1. Each of these get added up for the total.

Example Set-Up

Now let's look at an example one for you and your friends to go out to lunch. Together you determine that the criteria for going out to eat is:

  • Price
  • Diversity of food available
  • Food quality
  • Distance from where you currently are
  • If there are allergen-friendly options
  • Sally's favorite restaurant
  • Ben's favorite restaurant
  • Mike's favorite restaurant
  • Jen's favorite restaurant

Then you determine the weight for each criteria. For example let's say that since none of your friends has a lot of money, the price is more important than the food quality and diversity. So price gets a weight of 2, while diversity and quality only get a weight of 1. Since no one has a car, distance is also an important factor. And since Ben won't be able to eat anything if there aren't any gluten-free options, allergens also gets a heavier weight. Each person's favorite only gets one weight, except for Jen, because it is her birthday; so we give that one a weight of 3.

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