Decoding ICE Scoring Prioritization Model
Prioritizations frameworks are used by organizations worldwide, especially by product teams and marketing teams to prioritize initiatives, ideas, and projects. Different frameworks consider different factors to determine a value and evaluate priority.
One of the popular prioritization frameworks is the ICE scoring model. It is an efficient framework great for speeding up the process of decision-making. It is a fairly simple process without involving complex calculations and analysis.
What is the ICE scoring prioritization model?
ICE is a prioritization technique and a combined evaluation of features of a product based on 3 important factors- impact, confidence, and ease. Product teams and managers worldwide use ICE prioritization frameworks to shortlist and surface ideas for developing the next product features. It helps the product managers to evaluate the priority of features of the product by generating scores so that tasks are developed accordingly.
Sean Ellis who coined the term Growth Hacking and is famous for helping companies grow developed the ICE scoring method. This method was originally developed to prioritize growth experiments but now this model is used for feature prioritization as well. The ICE scoring model is typically ideal for early-stage development when there is a pool of ideas flooding in, and you have to shortlist the most appropriate ones.
How does the ICE scoring model work?
The ICE scoring model revolves around 3 primary metrics i.e impact, confidence, and ease. These 3 metrics are weighted with scores to shortlist the importance and prioritization of a particular feature of a product.
Whenever a new feature, idea, or initiative is proposed, one of the important prioritizing criteria is the impact that it is going to have on its users and your business. In other words, it means how well the feature of the product will be received by the users and how much will it contribute to the end goal that you have. For example, getting more customers, increasing customer retention, increasing product revenue, etc.
While weighing the impact, values are attached to scores, which can be like the following.
1-2: Zero impact
3-4: Low impact
4-6: Medium impact
7-8: Good impact
9-10: High impact
As the term suggests, evaluating confidence in a particular feature or idea means how confident are you that this will work or how sure are you about the impact. Your confidence can come from anything, it can either be a gut feeling or from the data derived from analytics. You can also relate the reason for confidence to previous tasks or ideas with similar characteristics.
This is how you can evaluate confidence.
1-2: No confidence
3-4: low confidence
5-6: Medium confidence
7-8: Good confidence
9-10: High confidence.
Ease is the last important metric you have to determine. When you evaluate the ease of a feature or an idea, you try to find the answer to the question “how easily can you develop the feature” or “what is the ease of implementation”.
This metric can relate to a variety of factors. It is not solely from the point of view of the development team. You have to consider all the vital factors like cost of implementation, resources available, team expertise, etc.
This is how you can attach value to the numbers to evaluate the ease of implementation.
1-2: Extremely hard
9-10: Very easy
How to calculate Ice Scoring?
After you have attached scores to each category, you can finally calculate it by multiplying all the output to get the final score. The feature with the highest score wins.
ICE = Impact x Confidence x Ease
Let us understand it with the help of an example.
Suppose there are two ideas or features up for competition. Feature one has an impact of 5, confidence of 6, and ease of 4. Feature two has an impact of 3, confidence of 5, and ease of 7.
ICE score of feature 1 = 5 X 6 X 4 = 120
ICE score of feature 2 = 3 X 5 X 7 = 105
Feature 2 clearly wins here as its total score is higher than the total score of feature one.
How to use the ICE score model effectively?
Sometimes you can be torn between a number of factors and goals to consider, in the end leaving you confused and disorganized. Here are some best practices to use the rice score effectively.
1. Have a clearly defined goal and measurable metrics
When you focus on the 3 vital metrics of the ICE framework, it is very important to proceed with one clearly defined goal at a time. For example, if you are developing a new product feature that let users keep a track of the number of revisits on their websites. You must set clear objectives and develop metrics to give you an idea of the impact like
- Net promoter score (NPS)
- Churn rate
- New Qualified leads
- Client retention rate
2. Create a better quality testing backlog
To create more winning results, you have to ensure to create a better quality testing backlog that is backed with good data sources. You can also start by testing hypotheses to determine the validity and power of each feature.
3. Rank the list of features
Ranking will help you to prioritize the features that are most important and feasible. This will help you to determine the use of the remaining features and put them in the backlog, Ranking will also help you to arrange the features from high to low priority so that you can use the information while grading future ICE scores.
4. Document ICE scores
Documenting ICE scores and test results will help you keep track of all the records. Documentation is important since it can act as a reference point for grading future ICE scores. It will also help you stay organized and keep all the team members informed even if you accidentally forget them to keep them in the loop. They can always come and check the records later.
RICE Vs ICE prioritization frameworks
Both RICE and ICE prioritization frameworks are efficient prioritization strategies to evaluate and shortlist vital features of the product. However, there is a minor difference between the two. RICE differentiates between impact and reach but in the ICE scoring model, both the concepts are merged together.
The RICE model is used by organizations when teams want to differentiate between a feature that might have a big impact on small users vs a small impact on big users.
In the ICE prioritization framework, the final score is calculated by taking into account the 3 important factors i.e impact, confidence, and ease. While in the RICE prioritization framework the final score is calculated by multiplying reach, impact, and confidence and dividing the result by effort.
Pros and Cons of using an ICE prioritization framework
Like all frameworks, the ICE prioritization framework also comes with its own set of pros and cons. We have tried to list some of them.
- Speedy and simple approach.
- Easy to update. Since it is easy to update, you end up using it more resulting in better estimation.
- Accelerates the process of decision-making without involving complex and time-consuming analysis.
- Results are highly subjective depending on who and when you asked.
- Results can vary on different days or on the mood of the users.
- If a potential feature gets a lower score because of personal preferences, it is removed from the scoring process.
ICE scoring model is popular among organizations for the convenience of use. It is both easy and speedy, helping teams make quick decisions. However, its greatest strength can also be a reason for its drawback. Due to an accelerated process of scoring, the results may not always be accurate. Though not the most appropriate for every situation, the ICE scoring model is a great framework to use for the early stages of an organization where you want to keep things moving and prioritize initiates quickly.
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