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Using weights and values to determine an overall Business Value for an object is only really applicable to Single or Multiple choice questions. |
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Object questionnaires allow you to gather information from your users about individual objects, such as an application.
Evolve allows you to weight each question, and put value scores against the possible answers. When users complete the questionnaire, Evolve works out a Business Value score for the object which is based on the values assigned to the answers they provided, measured against the question weighting.
The Business Value is aggregated across all responses and is stored as a property of the object itself, for example you could call it 'User Assessment Score' so you can display is on your Object Page.
As a best practice, we recommend aiming to capture a Business Value of between 0 and 100 - so you can represent the value as a gauge on your Object Page.
Each question in the questionnaire can be given a weight of 0.0 to 1.0. The total of which must equal 1.0 in order for it to work. In addition, each answer to each question is given a score – according to your scale. If we are following the best practice guideline, this again would be between 0 and 100.
The formula for the Business Value is quite simple. The score for a given questionnaire response is (Question Weight * Answer Value)+(Question Weight * Answer Value) + .
Example
In this example we are using a questionnaire to ask users for their assessment of an application.
The application object has a numeric property called 'User Assessment Score' which will be used to store the Business Value.
In the example, let’s assume that the questionnaire has three questions and each question has five possible responses.
Following the best practice of aiming to create a score of 0 to 100, and remembering we need to make the combined weights add up to 1.0, I might set the weighting for Question 1 at .5, Question 2 at .3, and Question 3 at .2.
This means I judge that Question 1 should have more impact on the result than Questions 2 and 3.
Each question has the same possible answers, we're asking users how they rate the application, so the answers to all the questions are Very Poor (0), Below Average (25), Average (50), Above Average (75) and Superior (100). Following our best practice, they can only have a maximum value of 100.
Without weighting, or with equal weighting, scores of 100 for Question 1, 50 for Question 2, and 0 for Question 3 would average out to 50 without weighting or with equal weighting. But with our weighting of .5, .3 and .2, the weighted average score is 65 – a higher score because of the weighting.
The score is calculated using the formula (.5 * 100) + (.3 * 50) + (.2 * 0) = 65.
To determine the total score for that application, Evolve tracks the number of questionnaire responses for that application and comes up with a straight average score of all user responses. So if only one other person filled out the survey in our example and their weighted score was 75, the average score would be 70 ((65+75)/2=70).
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