The Prioritization Paradox: Balancing Customer Needs and Business Goals

Product Management, often described as the intersection of business, technology, and user experience, is a multifaceted role. One of its most challenging aspects, however, is prioritization. If you've transitioned from another discipline, you might assume prioritization is simply about determining which tasks to tackle first, which deadlines to meet, and which emails to answer. However, in product management, prioritization is a whole different ball game.

Imagine this scenario: Your engineers are excited about a new feature that they believe will revolutionize your product. Meanwhile, a key stakeholder gently suggests a different feature they think is essential for the initial release. And to top it off, your data analyst is convinced that neither of these features is what users truly want. Who decides how to prioritize these features? You do.

Prioritization is a cornerstone of successful product development. It's about making strategic decisions that align your team's efforts with your product's goals and the needs of your users. While it can be daunting, it's essential for launching a successful product. Fortunately, a wealth of resources and frameworks can guide you through this process.

In this article, we'll explore:

• The benefits and challenges of prioritization
• Popular prioritization frameworks and when to use them
• How real Product Leaders prioritize at companies (Still in Research)
• Common prioritization mistakes
• Frequently Asked Questions

Benefits of Effective Prioritization

• Enhanced focus on key objectives: Prioritization helps you concentrate on tasks that align closely with your product's core goals. For example, when Spotify prioritized personalized playlists, it significantly boosted user engagement, aligning perfectly with its goal of providing a unique user experience.
• Resource optimization: By focusing on the most impactful projects, you can allocate your team's time and your company's resources more efficiently.
• Improved decision-making: Prioritization forces you to make strategic decisions about where to focus your efforts, reducing the risk of cognitive biases like recency bias and the sunk cost fallacy.
• Strategic focus: Prioritization ensures that your day-to-day activities contribute to your company's broader strategic goals.
• Stress reduction: Effective prioritization can help you manage your workload and reduce stress, preventing burnout.

Challenges of Prioritization

• Competing demands: Stakeholders, engineers, and data analysts often have different priorities, making it challenging to reach a consensus.
• Uncertainty: The future is unpredictable, and it can be difficult to prioritize tasks based on uncertain outcomes.
• Managing Stakeholder Expectations: Different stakeholders, such as engineers, marketing teams, and executives, may have varying priorities. Engineers might prioritize feature development, while marketing may advocate for more customer-centric enhancements. Balancing these competing demands can be a significant challenge.
• Adapting to Changing Market Conditions: The market is constantly evolving, and priorities can shift unexpectedly. The COVID-19 pandemic, for example, forced many companies to rapidly reprioritize their product roadmaps to address the changing needs of their customers.
• Dealing with Limited Information: Even with a strong data-driven team, it's often impossible to have complete information about user needs and market trends. Amazon's decision to enter the cloud computing market with AWS was initially seen as a risky move, but their prioritization of this gamble ultimately paid off.
• Limited Resources: Smaller businesses and startups often have limited resources, which can constrain their ability to prioritize and execute on all desired features. They may need to focus on building a minimum viable product (MVP) and iterating based on user feedback.
• Bias: Personal biases and opinions can influence product prioritization. People may be reluctant to provide honest feedback, leading to biased data and misguided prioritization decisions.
• Lack of Alignment: Different teams within an organization may have varying opinions about what is important. When these differences are not addressed, it can lead to conflicts and hinder product prioritization.

Prioritization Frameworks: Choosing the Right Tool for the Job

With numerous prioritization models available, it's easy to feel overwhelmed. As a product manager, you may wonder which framework to prioritize. The key is to treat each framework as a specialized tool—just like how a hammer is better than a wrench for nails, each model works best for specific types of prioritization tasks. The first step is understanding the most trusted frameworks. Let’s dive in!

The MoSCoW Method

The MoSCoW Prioritization Technique, also known as MoSCoW Analysis, is a straightforward approach for categorizing what’s essential and what’s not. The acronym represents four categories: Must have, Should have, Could have, and Won’t have.

It’s particularly helpful for communicating with stakeholders about priorities and justifying what you're focusing on.

MoSCoW Categories:

• Must Have: These are non-negotiable features that are critical to the product's core functionality. Without them, the product wouldn’t be usable or valuable to users. Think of them as the "painkillers" that solve your users' key problems.
• Should Have: These are important, but not essential for the product to function. They often address common use cases and improve user experience without being critical.
• Could Have: Features that are nice-to-haves but not necessary. These are the “vitamins”—beneficial, but not urgent. They often include integrations or enhancements that streamline workflows.
• Won’t Have: These are the low-priority features that aren’t worth the time or resources, similar to the "money pit" category in the Impact–Effort matrix.

Pros: MoSCoW is ideal for simplifying complex decisions and ensuring non-technical stakeholders understand the priorities. It’s great for quick, clear categorization.

Cons: It can be tricky to limit the number of "Must Have" features, which can overload the product backlog and strain the development team.

RICE Scoring

Developed by Intercom, the RICE Scoring System compares features based on four key factors: Reach, Impact, Confidence, and Effort.

RICE Breakdown:

• Reach: Focuses on how many people will benefit from a feature within a given time period. For example, “How many customers will use this feature per month?”
• Impact: Measures how significantly the feature will affect users. You can use a scale:
• Confidence: Indicates how sure your team is about the accuracy of the Reach and Impact estimates. High-confidence scores (above 80%) prioritize features that seem less risky.
• Effort: Evaluates the work required from each team member. Ideally, high-impact/low-effort features are prioritized, though they’re rare.

How to Calculate RICE: Multiply Reach, Impact, and Confidence, then divide the result by Effort to get your RICE score.

Pros: The spreadsheet-friendly format makes it perfect for data-focused teams. The Confidence factor helps filter out risky features and balances out guesswork, while the structured approach makes it scalable for teams testing multiple hypotheses.

Cons: RICE can feel overwhelming for visual thinkers or teams working quickly. When managing dozens of features, the spreadsheet can become cumbersome and difficult to interpret.

Impact–Effort Matrix: Simplifying Prioritization for Visual Thinkers

The Impact–Effort Matrix is a simple, visual tool that helps teams prioritize tasks based on their value (impact) versus the complexity of implementing them (effort). It’s great for those who prefer visual representation, making it easier to identify which features will bring the most value with the least effort.

How It Works:

1. List all potential features or ideas.
2. Plot them on a 2D matrix where one axis represents impact (value to users) and the other represents effort (difficulty or time to develop).
3. Place each feature into one of four quadrants:

• Quick Wins: Low effort, high impact. These features provide great value with minimal effort. For example, fixing a UI bug that significantly improves user experience.
• Big Bets: High effort, high impact. These features have the potential to make a big difference but require significant resources. An example might be building a completely new feature, like adding a payment gateway to your app.
• Fill-ins: Low effort, low impact. These are minor tasks that don’t take much time but also don’t add significant value. These are great to work on when waiting for larger blockers to clear. For instance, cosmetic updates that don’t affect functionality.
• Money Pits: High effort, low impact. These are tasks that require a lot of resources but don’t offer much value. An example could be adding a rarely-used feature that only a small fraction of users would need. Avoid these!

Pros: This method is easy to understand and share with the entire team. It’s great for quick prioritization when working with a smaller number of features.

Cons: It can be tricky when there are several "Quick Wins." How do you decide which one to tackle first? Additionally, some "Fill-ins" can unexpectedly take more time and resources than planned, distracting from more valuable tasks.

Kano Model: Focusing on Customer Satisfaction

The Kano Model, developed by Professor Noriaki Kano in the 1980s, is centered around customer satisfaction. It helps teams prioritize features based on how much they delight users, how they perform, and whether they meet basic expectations.

Kano Categories:

• Delighters: Features that exceed customer expectations. For example, Apple’s introduction of Face ID was initially a delighter because it was a new, innovative way to unlock phones.
• Performance Features: The more you invest in these, the more users appreciate them. For instance, improving battery life or app speed leads to happier users.
• Basic Features: These are the bare minimum customers expect. Think of an e-commerce platform needing a functional checkout system. If these features are missing, the product is virtually unusable.

Example: Over time, what was once a Delighter can become a Basic Feature. For example, mobile-responsive design used to be a "wow" factor for websites but is now expected as a standard.

Pros: The Kano model emphasizes customer-focused features, making it excellent for prioritizing features that increase satisfaction.

Cons: It can be subjective, as categorizing features often depends on personal opinions. It also doesn’t account for factors like cost or technical feasibility.

Feasibility, Desirability, and Viability Scorecard: A Balanced Approach

The Feasibility, Desirability, and Viability (FDV) Scorecard was created by IDEO in the early 2000s to evaluate product ideas based on three criteria: feasibility, desirability, and viability.

How It Works:

• Feasibility: Can we build this feature with our current resources and skills? For example, do we have the technology to support this, or would we need to hire new talent?
• Desirability: Does this solve a key problem for the customer? Will users find it valuable enough to pay for?
• Viability: Will this feature generate enough revenue to be worthwhile? What’s the return on investment (ROI)?

Teams rate each feature on a scale of 1-10 for each criterion. The scores are then tallied to determine the priority.

Example: Say you’re considering adding a new subscription tier for premium features.

• Feasibility: You already have the tech infrastructure, so it's rated high (9).
• Desirability: Surveys show strong demand from users (8).
• Viability: The potential for increased revenue makes it viable (9).

Pros: The FDV scorecard is versatile and can be used for more than just features—it’s great for marketing strategies, MVP evaluation, and more. It’s also flexible, working well for teams that prefer discussions over rigid frameworks.

Cons: This approach depends on how well you understand customer needs and the complexity of features. If data on these factors isn’t readily available, the scoring can be inaccurate.

Weighted Scoring Prioritization: Customizable for Every Situation

Weighted Scoring Prioritization is a flexible method for ranking features by assigning different levels of importance (weights) to various criteria. This approach gives you more control over how much each category contributes to the overall score.

How It Works:

1. Choose Your Criteria: First, select the categories that matter most for evaluating your features. Common examples include:
2. Assign Weights: Decide how important each category is and assign a percentage (up to 100%) to each. For example, if you're building an MVP, you might prioritize UX at 40%, strategic impact at 30%, and user adoption at 30%.
3. Score the Features: Each feature gets a score between 1 (lowest impact) to 100 (highest impact) for each category. Multiply the score by the assigned weight for that category.
4. Calculate the Final Score: Add up the weighted scores to determine the final priority of each feature.

Example: Suppose you’re evaluating a new login feature. You assign 40% to UX, 30% to strategic impact, and 30% to user adoption. After scoring, the login feature gets:

• 90 for UX (because it simplifies the process),
• 60 for strategic impact,
• 80 for user adoption.

The final score would be: (90 × 0.40) + (60 × 0.30) + (80 × 0.30) = 36 + 18 + 24 = 78.

Pros: Highly customizable—this method can be used at different stages of your product’s lifecycle to fit shifting priorities.

Cons: Determining the right weights for each criterion can be tricky, especially when considering the broader product ecosystem.

Cost of Delay: Prioritizing Based on Revenue Loss

The Cost of Delay framework focuses on the financial impact of not launching a feature immediately. It helps teams decide which features to prioritize based on potential lost revenue.

How It Works:

1. Estimate Revenue: Figure out how much revenue the feature could generate per unit of time (e.g., per month).
2. Estimate Time to Develop: Estimate how long it will take to complete the feature.
3. Calculate the Cost of Delay: Divide the potential revenue by the time required to develop the feature. This gives you a monetary value for each unit of time the feature is delayed.

Example: If a feature could generate $10,000 a month and takes 2 months to build, the cost of delay is $5,000 per month. Every extra month you delay this feature costs your company $5,000 in lost revenue.

Pros: Great for aligning teams around the monetary value of features, especially when ROI is a priority.

Cons: For new companies or features without historical data, revenue estimates can be based on guesswork, making the results less reliable.

Product Tree: Visualizing Growth and Prioritization

The Product Tree framework is an engaging, visual approach to prioritizing features by imagining your product as a tree. Stakeholders collaboratively place features on different parts of the tree based on their priority and impact.

How It Works:

• Roots: Represent the core technologies or capabilities that the product needs to function. These are the foundational elements.
• Trunk: Stands for the main features that define the current product. These are stable and essential for growth.
• Branches: Represent areas of the product where new features or enhancements can grow. These are often more experimental or future developments.
• Leaves: Symbolize smaller, more specific features or enhancements that directly impact user experience. Leaves are the visible aspects that contribute to customer satisfaction.

Example: During a Product Tree session, you might place a new payment gateway feature on a branch, as it’s a significant but not core enhancement. Smaller usability improvements, like adding a search filter, would be placed on the leaves.

Pros: It’s a fun, interactive way to prioritize and helps teams visualize how different parts of the product can evolve.

Cons: While it’s great for brainstorming, this framework doesn’t offer quantitative metrics, which can make it harder to align priorities with business goals.

Choosing the Right Prioritization Framework

Selecting the best prioritization framework can be challenging. Each framework has its strengths and weaknesses, and the ideal choice depends on your specific needs and context.

The Kano Model

The Kano Model is a valuable tool for understanding customer satisfaction. It categorizes features into three groups: must-haves, delighters, and indifferents. While it can provide valuable insights, conducting the necessary surveys and analysis can be time-consuming.

The RICE Scoring System

The RICE scoring system is a popular framework that considers Reach, Impact, Confidence, and Effort. It's particularly useful for evaluating the potential impact of various features or initiatives. However, it can be challenging to accurately estimate these factors, especially for new or untested ideas.

The MoSCoW Method

The MoSCoW method categorizes requirements into Must-Have, Should-Have, Could-Have, and Won't-Have categories. It's a helpful way to balance the needs of stakeholders and customers. However, it can be tempting to overestimate the importance of certain features, leading to a bloated product roadmap.

Beyond the Frameworks

While these frameworks provide valuable guidance, many talented Product Managers have developed their own unique approaches to prioritization. The key is to experiment with different methods and find what works best for your team and product.

Prioritizing Individual Tasks: Tips from Busy Product Leaders

Microsoft: The Eisenhower Matrix

Anusha Bahtnagar, a Product Manager at Microsoft, uses the Eisenhower Matrix to prioritize her inbox. This framework categorizes tasks into four quadrants based on their urgency and importance. By focusing on high-priority tasks and delegating or deferring others, you can effectively manage your workload.

Amazon and Google: Customer-Centric Prioritization

Many successful companies prioritize customer needs above all else. Asal Elleuch, a Senior Product Manager at Amazon Prime, emphasizes the iterative nature of prioritization. By focusing on your customers' needs and aligning your product vision with their goals, you can make more informed decisions.

Google product teams use North Star Metrics to guide their prioritization. A North Star Metric is a key metric that represents the ultimate value you provide to your customers. By focusing on initiatives that have a significant impact on your North Star Metric, you can ensure that your efforts are aligned with your customers' needs.

HSBC: A Four-Step Approach

Mariano Capezzani, a Product Leader at HSBC, has developed a four-step prioritization process:

1. Know the context: Understand the broader context of the task or feature, including company KPIs, market trends, and regulations.
2. Understand the need: Differentiate between what customers are asking for and what they truly need.
3. Consider the execution: Evaluate the complexity and dependencies involved in delivering the feature.
4. Arrange the sequence: Prioritize tasks based on their alignment with company goals, market benefits, and other relevant criteria.

By following these steps and adapting them to your specific circumstances, you can make informed and effective prioritization decisions that drive your product's success.

Choosing the Right Prioritization Framework

Selecting the best prioritization framework can be challenging. Each framework has its strengths and weaknesses, and the ideal choice depends on your specific needs and context.

The Kano Model

The Kano Model is a valuable tool for understanding customer satisfaction. It categorizes features into three groups: must-haves, delighters, and indifferents. While it can provide valuable insights, conducting the necessary surveys and analysis can be time-consuming.

The RICE Scoring System

The RICE scoring system is a popular framework that considers Reach, Impact, Confidence, and Effort. It's particularly useful for evaluating the potential impact of various features or initiatives. However, it can be challenging to accurately estimate these factors, especially for new or untested ideas.

The MoSCoW Method

The MoSCoW method categorizes requirements into Must-Have, Should-Have, Could-Have, and Won't-Have categories. It's a helpful way to balance the needs of stakeholders and customers. However, it can be tempting to overestimate the importance of certain features, leading to a bloated product roadmap.

Beyond the Frameworks

While these frameworks provide valuable guidance, many talented Product Managers have developed their own unique approaches to prioritization. The key is to experiment with different methods and find what works best for your team and product.

Common Product Prioritization Mistakes and How to Fix Them

Mistake 1: No Agreed-Upon Scoring Guide

What does an impact score of "5" really mean? Is it a 1% growth in conversion rate or 10% in Monthly Recurring Revenue (MRR)? Without a clear and agreed-upon scoring guide, team members may interpret scores differently, leading to inconsistent prioritization. This can cause confusion and even conflict, as decisions that appear objective may be based on personal opinions.

How to Fix It: Create a shared scoring guide for your prioritization criteria. Define what each score represents with clear descriptions and examples. For instance, for a "confidence level" score, you might specify what a "high" or "low" confidence score looks like in the context of your product.

• Specific: Tailor it to your product and team context.
• Objective: Make sure it’s clear and easy to understand.

Even with guidelines, disagreements may still arise, and that's okay. Encourage team members to explain their reasoning, as these discussions can reveal blind spots and improve alignment.

Mistake 2: Mixing Discovery and Delivery

Product discovery (problem analysis and solution design) is just as important as development. But discovery tasks are often mixed in with development work or left out of prioritization altogether. This leads to messy dependencies or biased selections.

How to Fix It: Separate your product development into two backlogs: discovery and delivery, following the Dual Track Development approach. This doesn’t mean splitting the team—one team should handle both tracks to ensure continuity and efficiency. Prioritize these backlogs independently to keep everything organized and moving smoothly.

Mistake 3: Recency Bias

Backlogs grow faster than they shrink, leading to older items getting neglected. New ideas often seem more exciting (a natural "recency bias"), while old but still valuable ideas are forgotten.

How to Fix It: Review your backlog regularly. Track the "freshness" of each item, and if something hasn’t been updated in a while, reassess its priority using the most current information. If it’s no longer relevant, remove it to avoid cluttering the backlog.

Mistake 4: Ignoring Constraints

Product development is complex. In addition to considering value vs. cost, you must account for dependencies, deadlines, skill sets, and strategic fit. Ignoring these constraints leads to frustration and inefficiency.

How to Fix It: Define rules for managing constraints within your prioritization process. For example:

• Time-sensitive projects: Set aside resources to fast-track projects with firm deadlines (e.g., seasonal campaigns).
• Dependencies: If a project is blocked, resume its position once the blocker is removed, without disrupting ongoing work.
• Strategic alignment: Assign extra weight to projects aligned with the company's strategic goals using methods like Weighted Scoring.

Consistent guidelines build trust in the system, ensuring decisions are made fairly and objectively.

Mistake 5: Overcomplicating the Process

Prioritization is about making the best decisions with the information you have, but some teams get stuck trying to create the "perfect" plan. Over-analyzing small differences between features can waste valuable time that could be spent on execution.

How to Fix It: Timebox your prioritization discussions to limit the time spent debating. If there’s a tie between initiatives, introduce a simple tie-breaker rule, like "first in, first out" for items in the backlog. Trivial differences won’t matter in the long run, and you’ll never make progress if you don’t decide what to tackle first.

Mistake 6: Not Iterating the Prioritization System

No prioritization system is perfect from the start. Even if your current system works, it may not scale as your company grows. Sticking to the same system without reviewing it regularly can lead to inefficiencies.

How to Fix It: Treat your prioritization system like your product: continuously monitor and improve it. Schedule regular reviews (e.g., quarterly or bi-yearly) to gather feedback from the team and discuss possible improvements. Keep in mind that:

• It takes time to see the effects of new processes.
• Changes can temporarily hurt productivity as teams adjust.
• Not every problem will have a simple solution.

By iterating in small, frequent steps, you can fine-tune the system without disrupting your workflow.

Mistake 7: Management Interference

One of the most frustrating issues for product teams is when management steps in and reshuffles the backlog without a clear reason, often due to misalignment between company strategy and product goals.

How to Fix It: Product leaders (CPOs, directors, team leads) must bridge the gap between teams and senior management by facilitating clear communication. Ensure there’s a structured process for sharing insights across teams, and make sure everyone has access to key information like ideal customer profiles (ICPs) or data dashboards. Here’s how to start:

• Share insights across teams.
• Ensure all teams have access to critical information.
• Address information gaps proactively.

By keeping communication channels open and aligning strategies, you can minimize disruptions caused by management interference.

Frequently Asked Questions

• How do I balance competing priorities from different stakeholders, especially when they have conflicting goals? This is a classic challenge in product management. Stakeholders often have different priorities, and it can be difficult to reconcile them all. Some common approaches include using data to support your decisions, building consensus through collaboration, and using prioritization frameworks like MoSCoW or RICE.
• How do I prioritize features when I have limited information about user needs or market trends? This is a common problem, especially for new products or features. Some strategies for dealing with limited information include conducting market research, talking to potential customers, and using data-driven insights.
• How do I prioritize features when I have limited resources (time, budget, or team size)? This is a challenge that all product managers face. Some strategies for prioritizing features when resources are limited include using the MoSCoW method, focusing on the most impactful features, and being willing to say no to less important features.
• How do I avoid falling into common prioritization traps, such as recency bias, sunk cost fallacy, or confirmation bias? These cognitive biases can lead to poor prioritization decisions. Some strategies for avoiding these traps include being aware of them, using data to support your decisions, and getting feedback from others.

Let's Discuss

How does your organization prioritize product features, projects, or initiatives? What are the key factors or criteria that influence your prioritization decisions?

Lets share any specific examples or case studies that illustrate your prioritization process?