Beyond the matrix: Advanced prioritization techniques for product managers

As technology continues to evolve at an unprecedented rate, the role of a product manager has become more challenging than ever before. Product managers are the masterminds behind the success of a product, from its conception to its launch and beyond.

A critical aspect of their role is prioritization – the art and science of determining which features, enhancements, and initiatives to focus on to maximize value and impact.

Traditional prioritization methods such as the MoSCoW technique (Must-haves, Should-haves, Could-haves, and Won't-haves) or the High-Medium-Low approach have served product managers well.

However, in today's complex and competitive markets, relying solely on these methods may not be enough. To stay ahead in the game, product managers need to embrace advanced prioritization techniques that take into account multiple factors and adopt a more data-driven and strategic approach.

The Periodic Table of Product Prioritization Techniques

In this article, we will delve into some of the most effective and innovative prioritization techniques that go beyond the matrix, empowering product managers to make better decisions and drive product success. The major techniques that we will discuss are:

The Kano model: Understanding customer delight

Imagine a product that not only meets its users' expectations but also surprises and delights them. That's the essence of the Kano Model, a customer-centric prioritization technique developed by Professor Noriaki Kano in the 1980s.

The Kano Model

“Professor Noriaki Kano created the Kano Model in 1984 while studying the contributing factors to customer satisfaction and customer loyalty. The professor classified 5 unique categories of customer requirements, 3 of which you want to end up in your offering, and the other 2 should be taken out.”

The Kano Model categorizes features into three distinct types based on their impact on customer satisfaction:

Basic (expected) features: These are the fundamental requirements that customers expect to be present. Their absence leads to dissatisfaction, but their presence doesn't necessarily lead to delight.
Performance features: These are the features that directly impact customer satisfaction in a linear manner. The more you have, the happier the customers are.
Excitement (delight) features: These are unexpected features that can bring an element of surprise and delight to customers. Their absence doesn't cause dissatisfaction, but their presence leads to high levels of customer satisfaction.

By understanding the different feature categories through customer feedback and market research, product managers can prioritize their efforts on the most impactful features that drive customer delight.

For instance, let's consider a software product designed for graphic designers. Basic features would include essential tools like drawing, selecting, and saving. Performance features might include enhancements that improve the speed and efficiency of those tools. Excitement features could involve unique artistic filters or an innovative collaboration feature that allows designers to work together in real-time.

The Kano Model helps product managers strike a balance between delivering the expected and surprising customers with features they never knew they needed.

RICE scoring: A data-driven approach

In the fast-paced world of product development, data-driven decision-making is crucial. The RICE scoring method is a popular framework used by many product teams, especially in agile environments.

A Simple way to depict RICE Score

RICE is an acronym that stands for Reach, Impact, Confidence, and Effort. The RICE score is calculated as follows:

RICE Score = (Reach x Impact x Confidence) / Effort

Reach: The number of users or customers who will be affected by the feature over a certain period.
Impact: The degree of impact the feature will have on users or the business. This can be measured in various ways, such as revenue impact, user engagement, or customer satisfaction.
Confidence: How confident the product team is in the data used to estimate reach and impact. It takes into account the level of uncertainty in the evaluation.
Effort: The amount of time, resources, and complexity required to implement the feature.

By using the RICE scoring technique, product managers can prioritize features based on a combination of their potential impact, reach, and confidence, while considering the effort required for implementation. This ensures that resources are allocated to features with the highest potential for success.

Let's consider an example of an e-commerce platform that is considering two potential features: a personalized product recommendation engine and a social media sharing feature.

The personalized product recommendation engine could have a high reach, impacting a large number of users and potentially increasing revenue. The product team is highly confident in its potential impact and has estimated a moderate level of effort for its implementation. On the other hand, the social media sharing feature could have a limited reach and a lower impact on revenue, but it might be straightforward to implement.

Using the RICE scoring method, the personalized product recommendation engine would likely receive a higher priority due to its higher potential impact and reach, despite requiring more effort.

Weighted scoring model: Tailoring prioritization to business goals

Every product is unique, and its priorities should align with the organization's strategic objectives. The Weighted Scoring Model is a flexible and customizable prioritization technique that allows product managers to assign weights to various factors based on their product strategy and business goals.

Weighted Scoring Model

Here's how it works:

Identify and define criteria: Product managers start by identifying and defining the key criteria relevant to their product. These criteria can be diverse and may include factors such as customer value, technical feasibility, market demand, strategic fit, and revenue potential.
Assign weights: Once the criteria are established, product managers assign weights to each criterion based on their relative importance. For example, if customer value is the top priority, it would be assigned a higher weight than secondary criteria.
Rate and evaluate features: For each potential feature or initiative, the product team rates them against each criterion. This evaluation can be done on a numerical scale or a comparative ranking.
Calculate the score: The final score for each feature is calculated by multiplying the assigned weight with the rating for each criterion and summing up the results.

The Weighted Scoring Model allows product managers to align the prioritization process with the strategic goals of the organization, making it a powerful tool for data-driven decision-making.

Consider a software development company aiming to release a new version of its productivity application. The company has defined three criteria as crucial for success: user demand, technical feasibility, and revenue potential. They've decided to assign a higher weight to user demand, as meeting customer needs is a top priority for the organization.

The product team evaluates potential features based on these criteria and gives each feature a score. Features with high scores in user demand, technical feasibility, and revenue potential are given higher priority, ensuring that the team focuses on initiatives that align with the company's strategic goals.

The ICE method: Simple and effective prioritization

In the fast-paced world of product development, simplicity can often lead to more effective decision-making. The ICE method is a prioritization technique that has gained popularity in the world of startups and small teams with limited resources.

The ICE Method

ICE stands for Impact, Confidence, and Ease:

java

ICE Score = (Impact x Confidence x Ease of implementation)

Impact: Similar to the RICE method, this represents the potential impact of the feature or initiative on users or the business.
Confidence: The level of confidence the product team has in the potential impact. It accounts for the uncertainty in the evaluation.
Ease of implementation: This factor evaluates the complexity and effort required to implement the feature successfully.

The ICE method is particularly useful for prioritizing features and initiatives when resources are limited, and the product team needs to focus on initiatives that can be implemented quickly and have a high potential impact.

For example, a startup developing a mobile fitness application is considering two features: a personalized workout plan and a calorie tracking feature. Both features have the potential for high impact, but the product team is more confident in the implementation of the calorie tracking feature, as it leverages existing data in the app. The personalized workout plan, although impactful, requires more effort to create a robust algorithm for individualized plans.

Using the ICE method, the product team may choose to prioritize the calorie tracking feature, given its high impact and ease of implementation.

The value vs. complexity matrix: Striking the right balance

As a product manager, balancing short-term wins with long-term strategic initiatives is paramount. The Value vs. Complexity Matrix is a visual prioritization technique that helps product managers plot features or initiatives on a two-dimensional grid based on their value and complexity.

The Value vs. Complexity Matrix

Value is typically measured by the impact on users or business goals, and complexity represents the effort required for implementation.

Features are then categorized into four quadrants:

Quick wins: High-value features with low complexity. These are the low-hanging fruits that can be implemented quickly to deliver significant results.
Major projects: High-value features with high complexity. These initiatives are worth investing in but may require careful planning and resources.
Fill-ins: Low-value features with low complexity. These features are easy to implement but may not have a significant impact.
Maybes/parking lot: Low-value features with high complexity. They are deprioritized and can be reconsidered in the future.

The Value vs. Complexity Matrix provides product managers with a visual representation of their feature backlog, helping them make informed decisions and strike a balance between high-value quick wins and long-term strategic initiatives.

Let's take an example of a product team managing a project management software. They have several features in their backlog, including a robust reporting module, improved task assignment, and integrations with popular third-party tools.

By plotting these features on the Value vs. Complexity Matrix, the product manager can see that the improved task assignment feature is a quick win, providing significant value with relatively low complexity. On the other hand, the reporting module is a major project that requires more effort and resources, but it has the potential for high impact on user satisfaction and attracting enterprise customers.

Cost of delay (CoD): Prioritizing with urgency

In a fast-paced and competitive business environment, prioritizing initiatives with urgency can be critical to staying ahead of the competition. The Cost of Delay (CoD) is a prioritization technique rooted in the principles of lean thinking.

Prioritizing CoD with Urgency

The CoD method takes into account both the value of a feature and the cost of delaying its implementation. The cost of delay can include factors like missed market opportunities, potential revenue loss, or competitive disadvantage.

By quantifying the cost of delay for different features, product managers can prioritize initiatives that have the highest potential cost of delay, ensuring that the team focuses on the most valuable features with a sense of urgency.

For example, a software company is working on a new version of its mobile app, and one of the features being considered is a secure login with biometric authentication. The product manager calculates the potential cost of delay by considering the growing demand for enhanced security features and the risk of losing security-conscious customers to competitors.

By factoring in the cost of delay, the product manager can justify prioritizing the secure login feature over other enhancements that may not have the same urgency.

Conclusion: Making prioritization a strategic advantage

As a product manager, mastering the art of prioritization is crucial to the success of your product and, ultimately, your company. While traditional methods like the MoSCoW technique have their place, advanced prioritization techniques like the Kano Model, RICE Scoring, Weighted Scoring, ICE Method, Value vs. Complexity Matrix, and Cost of Delay offer valuable insights and a more data-driven approach to decision-making.

Remember, there is no one-size-fits-all approach to prioritization. Each technique serves a unique purpose and can be adapted to your specific product and business needs. The most effective product managers combine a deep understanding of their customers with a strategic vision to prioritize initiatives that align with their overall product strategy.

By embracing these advanced prioritization techniques, product managers can go beyond the matrix and unlock the true potential of their products, driving success in today's dynamic and ever-changing digital landscape.