Prioritization frameworks can be helpful tools to determine which products, features, and projects should be focused on and placed on the roadmap.
In this article, we talk about three frameworks: RICE Scoring, the Weight Scoring Decision Matrix, and the Kano Model.
The RICE scoring model is a prioritization framework that determines the value of features or initiatives according to four factors: reach, impact, confidence, and effort.
- Reach — How many customers would directly be affected by this feature in a set amount of time?
- Impact — How much extra benefit would your customers get by adding this feature to your product? For example, does it improve conversion rates or ease of use?
- Confidence — How confident are you in the estimates you made?
- Effort — How much work is required from your team to build this feature or complete this project?
RICE Score = (Reach * Impact * Confidence) / Effort
For example, if your team wants to create a new sign up flow that improves the ease of use for the approximately 500 customers that join every month, your reach would be 500. If the new flow significantly improves conversion rates and usability, the impact of this project is likely 4/4. With interviews with customers, you’re able to validate and have the data to back these estimates up. Your confidence is 100%. And through conversations with your engineering team, you realize the effort to build the feature is minimal—just 8-10 days of effort. Therefore, you indicate that effort is 1/4. The RICE Score for this project is (500 * 4 * 100%)/1. Or 2,000.
Weighted Scoring Decision Matrix
There are two types of decision matrices: weighted and unweighted. When making a list of criteria to determine the prioritization of features, sometimes you might want to assign more weight to certain criteria. Not all criteria are built the same. A weighted scoring decision matrix brings more attention to certain categories.
For example, in the planning phase for a new project for a self-driving vehicle, we want to list out three criteria: business value, cost, and risk. One of the vectors we want to emphasize in our project is minimizing risk. Cost is not the focal point for this specific initiative. Therefore, we can reflect these goals in our matrix, assigning the following weights per category: business value: 4, cost: 2, and risk: 5.
Project #1 scores as 1 for business value (minimal impact), 2 for cost (significant cost), and 5 for risk (minimal risk). Unweighted, the aggregate score is 8.
Project #2 scores as 2 for business value (low impact), 3 for cost (moderate cost), and 3 for risk (moderate risk). Unweighted, the aggregate score is 8.
Project #1 scores as 1 for business value (minimal impact), 2 for cost (significant cost), and 5 for risk (minimal risk). Weighted, the aggregate score is weighted business value (4*1) + weighted cost (2*2) + weighted risk (5*5). The aggregate weighted score is 33.
Project #2 scores as 2 for business value (low impact), 3 for cost (moderate cost), and 3 for risk (moderate risk). Weighted, the aggregate score is weighted business value (4*2) + weighted cost (2*3) + weighted risk (5*3). The aggregate weighted score is 29.
With an unweighted decision matrix, it was difficult to determine which project to prioritize since all categories were valued—weighted—as equal. With a weighted decision matrix, it’s clear that Project #1 makes more sense to pursue in the context of our goals—risk minimization.
The Kano Model is a function of customer satisfaction and product functionality. It helps us understand how satisfied or delighted customers might be with a feature.
On the vertical dimension, the model represents customer satisfaction that may be gained from investing in building this feature.
On the horizontal dimension, the model tracks the level of functionality of the feature. How much have we invested in developing it? How much functionality does the customer get?
Kano categorizes features into four themes based on how customers might react to the given level of functionality:
- Must-Be — Expected features that may not satisfy users but are table-stakes. While including basic features may not delight users, not having them will certainly dissatisfy users or disqualify your product.
- Attractive — Unexpected features that pleasantly surprise users. Done compellingly, these could prove to be product differentiators.
- Performance — Features where more functionality equates to more satisfaction.
- Indifferent — Features that don’t make a difference to satisfaction. Their presence or lack thereof makes minimal impact to customer satisfaction.