A product manager should prioritize their work by first understanding the product’s goals and objectives and aligning them with the overall strategy of the company. They should also have a good understanding of their target customers’ needs and use that knowledge to determine the most valuable features to include in the product.
A product manager should use a prioritization framework to evaluate the relative importance of different features and ideas once they have a good understanding of the product’s goals and target customers. This could include evaluating the potential customer impact, feasibility, and resources required for each feature using a matrix such as the Value vs. Complexity Quadrant or the RICE framework.
The product manager should also solicit feedback from customers, stakeholders, and the team on a regular basis to ensure that they are focusing on the most important features and meeting the needs of the customers.
A product manager should also be able to make trade-offs and decline features that do not align with the product strategy and goals, or do not provide enough value to the customer.
Prioritizing the roadmap without market research is one of the most difficult challenges for product managers. Market research is an important tool for product managers because it allows them to better understand their customers’ needs, preferences, and pain points. Product managers may make assumptions about what customers want and prioritize features that do not align with customer needs in the absence of market research. This can lead to product failure and resource waste.
According to a study conducted by the Product Development and Management Association (PDMA), companies that conduct market research outperform those that do not. According to the study, companies that conduct market research are more likely to meet or exceed their product development goals, such as meeting or exceeding sales targets and launching products on time.
The case of the Kodak Company exemplifies the significance of market research. Kodak was once a dominant player in the film camera market, but due to a lack of market research, it failed to adapt to the digital age. Despite the fact that digital cameras were rapidly becoming popular, Kodak did not prioritize digital camera development and went bankrupt as a result.
Product managers may make assumptions about what customers want and prioritize features that do not align with customer needs in the absence of market research, resulting in product failure and wasted resources. Quadrant of Value vs. Complexity: This framework is a popular method for categorizing work items into four groups: High Value-Low Complexity, High Value-High Complexity, Low Value-Low Complexity, and Low Value-High Complexity. This aids in identifying the most important tasks to prioritize and in balancing short-term and long-term goals. Fixing a critical bug in the system, for example, would be considered high value-high complexity and should be prioritized.
The Kano Model: Based on customer needs and satisfaction, this framework is used to prioritize features and functionalities. It categorizes customer needs into three groups: fundamental needs, performance needs, and excitement needs. Customers must be satisfied for their basic needs to be met, while performance needs increase satisfaction and excitement needs can create loyalty. A basic need for a car, for example, might be that it starts and runs; a performance need might be good gas mileage; and an excitement need might be a built-in GPS system.
Weighted Scoring Prioritization: A scorecard is used in this framework to assign numerical values to various aspects of a project or feature, such as value, feasibility, and dependencies. The scores are then combined to generate an overall priority score that can be used to prioritize tasks. For example, a highly valuable and feasible feature with few dependencies would be prioritized over a less valuable but highly dependent feature.
The RICE framework is used to prioritize tasks based on the expected Reach, Impact, Confidence, and Effort. Reach denotes the number of people who will be affected by the work, Impact denotes the potential benefits, Confidence denotes the level of certainty that the work will be successful, and Effort denotes the time and resources required. A feature that will reach a large number of users, has a high potential impact, a high level of confidence, and requires minimal effort, for example, would be prioritized.
The ICE Scoring Model is used to prioritize work based on the required Impact, Confidence, and Effort. Impact denotes the potential benefits, Confidence denotes the degree of certainty that the work will be successful, and Effort denotes the time and resources required. For example, a feature with a high potential impact, a high level of confidence, and minimal effort would be prioritized.
The MoSCoW method: This framework is used to prioritize work based on categories such as Must-Have, Should-Have, Could-Have, and Would-Like-to-Have. Must-Have items are critical and must be completed, Should-Have items are important but not critical, Could-Have items are nice to have but not required, and Would-Like-to-Have items are not required but would be nice to have. A feature classified as Must-Have, for example, would be given a higher priority than a feature classified as Should-Have.
Opportunity Scoring: This framework is used to prioritize work based on the potential value gained and the level of uncertainty or risk involved. The potential value of an opportunity is weighted against the level of uncertainty or risk involved. For example, a high potential value opportunity with a low level of uncertainty or risk would be prioritized over a lower potential value opportunity with a higher level of uncertainty or risk.
These are some of the most popular prioritization frameworks that have been widely used in the industry; each framework has its own set of benefits and drawbacks, and the best one is a hybrid of the two.
