Six product prioritization frameworks and how to pick the right one

Reach, impact, confidence, and effort (RICE) are the four factors used to evaluate a product idea: 

• Reach: Identify the number of people or events over time, such as transactions per quarter or conversions per month.
• Impact: Determine whether an idea achieves business goals or meets customer needs. 
• Confidence: Measure the team’s confidence level in executing ideas with a percentage scale of high (100%), medium (80%), and low (50%).

• Effort: Calculate the time it will take the team to execute the idea.

You can use the RICE method in Jira Product Discovery, a prioritization and roadmapping tool for your product team. As a project manager, you’ll be able to assess the impact of your projects with ease.

The RICE framework enables product managers to gauge whether items are feasible. Data gathered from this calculation helps justify decisions to stakeholders.

RICE can be time-consuming and cumbersome to apply, particularly if multiple items require data and validation from multiple sources. Methods for determining each evaluation factor can change, making this method subjective, inconsistent, and potentially misleading. 

The Kano Model is a customer satisfaction-based prioritization framework. Researcher Noraki Kano developed the model to help product managers prioritize features and updates based on customer needs. It has three parts:  

• Basic features: Customers expect these essential functions in your product’s performance, such as the ability to share a post on a social network. 
• Performance features: These features increase customer satisfaction and make your product more enjoyable to use, like faster load times.

• Delighters: Unexpected features make customers happy. Examples of delighters include whimsical in-app messaging or the ability to use GIFs in posts.

The Kano model prevents a team from building features that won’t appeal to customers. It also identifies areas where the product may need improvement. Increased customer engagement and satisfaction is the most significant advantage of this method because it puts customer needs first.

The model is highly quantitative and potentially time-consuming, requiring heavy data research and analysis. It can also be a very manual process with the use of surveys. Tools such as Jira Product Discovery can help you aggregate, process, and manage the required data.

The MosCow Method is a four-step process for prioritizing product requirements around their return on investment (ROI). It stands for “must haves,” “should haves,” “could haves,” and “will not haves.” Apply this method company-wide to help frame discussions around what will increase revenue.

Here’s a breakdown of the model: 

• Must Have (M): These are the requirements needed for the project's success.
• Should Have (S): These are important requirements for the project but not necessary.
• Could Have (C ):  These requirements are “nice to have.” But don’t have as much impact as the others. 

• Will Not Have (W): These requirements aren’t a priority for the project.

MoSCoW is easy to implement and practice. Project managers can use it to help resolve disputes with stakeholders. This method also ensures that the team builds a minimum viable product (MVP). It can help you prioritize your product roadmap as well (start with this product roadmap template). 

The lack of clarity in the “will not have” requirements is a flaw in the method, especially around whether they should be part of the backlog. Criteria for a “must have” or a “should have” can also be hard to determine. If there is no consensus among stakeholders, then prioritization becomes ineffective and subjective.

Value vs. effect, or the value vs. effort matrix, prioritizes features based on their probable value and the effort necessary to implement them. A 2x2 matrix, measuring value on one axis and effort on the other, helps with the decision-making process. 

To determine value, consider how it affects users and impacts the bottom line. Effort is the complexity of implementation. Jira Product Discovery keeps track of customer pain points and product ideas, which the team can use to create a value vs. effort matrix. You can use effort ratings to determine how much labor an idea requires. 

You can use a prioritization matrix where the vertical axis measures value (low to high). The horizontal axis measures effort (low to high). It’s then divided into four quadrants: 

• Do first (upper right quadrant): This is high value, low effort, and a guaranteed quick win. 
• Do second (upper left quadrant): High value, high effort. 
• Do last (lower right quadrant): This is low value, low effort. It’s best to wait until the value increases before tackling this. 

• Avoid (lower left quadrant): Low value, high effort. It’s not worth your team’s time.

This framework involves no complicated calculations, which makes decisions easier. The framework is clear and lets the team focus on customer value tasks. Because it’s visual, the team can quickly see which tasks bring high value for the lowest effort.

Values can be imprecise with this method, which primarily uses instinct. The same goes for estimates, where a team might think they have more resources than they do. Another drawback is effort-sizing, which will vary from team to team. That makes planning more difficult with cross-functional teams that have different resources.

Opportunity scoring identifies features that are important to customers but underperform. Customers rate both a feature's importance and their satisfaction.

Use the opportunity algorithm to calculate the score on a five or ten-point scale. This equation goes beyond normal gap analysis, giving twice as much weight to importance scores as satisfaction scores.

Here’s the weighted equation: 

Importance + Max (Importance - Satisfaction, 0) = Opportunity 

Here is the opportunity algorithm formula, where customers use a 1-to-10 to quantify the importance and satisfaction of an outcome:  

Importance + (Importance - Satisfaction) = Opportunity 

Features with high importance but low satisfaction are an opportunity for improvement. Opportunity scoring is great for backlog grooming, which you can do in Jira Software. Bonus: Jira Software has native integration with Jira Product Discovery, so everyone can work within the same platform throughout the entire process.

The ROI outweighs the development costs. This allows a project manager to identify accessible opportunities regarding customer satisfaction, helping teams be more strategic with resource allocation.

Scoring models aren’t perfect. They don’t always work for every situation because they only provide a limited view of each idea’s scope. Scoring can be rigid, especially when quantifying an abstract concept. But mostly, scoring can't forecast how the market will respond to any changes in the product.

Cost of delay is another calculation that prioritizes projects based on their economic value. This method determines the ongoing costs that result from postponing items on the backlog. 

To calculate: 

• Estimate a new project’s ROI in revenue per unit of time (monthly recurring revenue, for example).
• Estimate the time it will take to implement the project.

• Divide the profit number by the time estimate.

The final number is the cost to the company for not pursuing the project. 

Using the cost of delay method results in more accurate value and cost estimates. This is because it doesn’t focus on negative reasons for postponement. Knowing what has better ROI also eases the burden of resource allocation.

If a project manager underestimates the project size, the calculations could be inaccurate. Estimated time requirements may be incorrect as well.

Choosing the proper prioritization framework for a team depends on several factors. Consider the project’s goals, the complexity of the product, the team’s expertise, and the available data. 

For instance, if the project aims to improve customer satisfaction, opportunity scoring may work well. But if the team is relatively new and still building their skills, value vs. effort might be a better choice.

Whatever framework you choose, Jira Product Discovery can help with project prioritization and presenting project roadmaps. It can help you gather and organize your product ideas, opportunities, features, and solutions in one centralized tool. There’s even a product roadmap template and product requirements template to get you started.  

With Jira Product Discovery, you’ll bring structure to your product management. And that’ll keep your team and stakeholders aligned on strategic goals. You can also seamlessly connect your ideas to epics in Jira Software, which makes it easier to provide project context and visibility from discovery to delivery.

Prioritization frameworks help you and your team determine what to work on next. To do that, you need to follow a few general steps: 

• Identify tasks: Identify and prioritize tasks based on a few criteria, such as customer value and business needs. 
• Define criteria: These criteria will help you determine which tasks are feasible to pursue. 
• Assign scores: Scoring uncovers features that are underperforming but necessary for customers. 

• Rank items: Ranking lets you order tasks based on urgency and highest impact. 

All these make it easier to decide which tasks your team should tackle.

Your team should review its priorities regularly. The cadence of that review depends on your team’s needs. You should also re-evaluate your prioritization framework if business objectives change. A different framework might work better than the one you’ve been using.

Prioritization frameworks are great to get everyone on the same page. You and your team can work with stakeholders to clarify goals. You can also use prioritization frameworks to make more informed decisions on which tasks to prioritize.