Feature scoring helps determine which Features are most aligned with your product strategy and provide the best return on your investment of time.
Step 1 – Impact Scoring
Your impact is determined by assigning a score (0-5) for each of the objectives/goals that you’ve defined in your product strategy and doing a weighted sum to determine the overall impact. Let’s say for example that you’ve defined 3 objectives for your strategy:
- Order Completion (5)
- User Engagement (4)
- Customer Satisfaction(3)
When you defined those objectives/goals you also set importance for each of those. In the above example, the objectives have importance values of 5,4,3 respectively. This is used as a weight reflecting the importance of each criterion.
- Impact Sum = (obj1 * weight1) + (obj1 * weight1) + (obj1 * weight1)
And so if you score your Feature as a 2 for driving Order Completion, a 4 for User Engagement and 5 for Customer Satisfaction, then the calculation would look something like this: (2*5)+(4*4)+(3*5) = 41.
Step 2 – Normalizing the Score
The next step is to normalize your impact sum into a 0-5 value that can be compared to an effort score of 0-5 and displayed on an Impact vs Effort chart. To do this, we’ll take the highest value from all features being scored and set that as a 5.0 and adjust the others on a relative basis, down from that value.
- Value = (Max(range of 100 Features)/5)
For example, if a Feature has an impact sum of 50, and the highest impact score in the range is 90, then the calculation would be: 50 / (90/5) = 2.77. That is your weighted impact score (we’ll round it to 2.8).
Step 3 – Impact vs Effort
Finally, we have calculated our Impact score and we can compare it to our Effort score to determine overall value. Effort should reflect overall effort for your team, including UX and you’ll assign a value of 1 – 5 (it cannot be 0 or there’d be no Feature!). These values correspond to T-shirt size estimates that teams often to at the early stage of a feature:
- 1- XS
- 2 – S
- 3 – M
- 4 – L
- 5 – XL
Once you have a numeric effort score, it is simply deducted from the Impact Score:
- Value = Impact – Effort
And so if our Impact score was 2.8 and we determined an effort of 2, then the value score would be 0.8 (2.8 – 2 = 0.8).
Keep in mind that scoring is relative and a feature is not good just because it has a positive score, nor bad for having a negative score. The outcome is entirely dependent upon the scoring model you define (your objectives and weights) and how you score the impact and effort of a feature. For this reason, it is important to look at the scores as relative (not absolute) and use this as an input for prioritization, not gospel.