How to choose your Product Prioritization Framework
How to choose your Product Prioritization Framework
A framework for choosing frameworks. Inception much?
Many product managers “don’t know” or “don’t have” a process for planning and prioritizing initiatives, according to ProductPlan’s 2020 Product Management report. There are a few reasons for this:
Many managers simply want to focus on creating value and solutions to problems faced today, not tomorrow.
Many managers focus on having quality conversations about what they think is the most important and why, without needing to use any score-based approach.
Many products change priorities all the time due to externalities outside of their control, including commercial preferences, legal, regulatory, and customer.
There is no one product management prioritization framework that will work for every company and industry. Each company has its nuances and factors that impact priorities, so adopting any one framework overwhelming for even the most seasoned product manager.
While having no prioritization method in place can be tempting if you have a highly collaborative team, a significant downside is the inability to adequately summarize or communicate prioritization decisions to executives teams without some level of documentation or artefact. So I recommended that you do choose one if you can — if anything, it will give you a method to challenge your biases and decisions.
So, is there a way can frame how to choose the right prioritization framework that suits you and your team’s work styles? You’re in luck! — I have supplied you a very quick index of the most popular prioritization frameworks, organized by order of complexity and difficulty.
The List of Prioritization Frameworks
The first step was to collect the popular frameworks out there today for an evaluation. The frameworks, along with their ID used within the graph below, are:
Cost of Delay and Weighted Shortest Job First [WSJF]
Cost vs Benefit (Weighted Score) [COBE]
ICE Scoring and RICE Scoring [RICE]
Kano Model [KANO]
Buy-a-Feature [BUYF]
Story Mapping [STMP]
Opportunity Scoring [OPPS]
Affinity Grouping [AFFY]
Impact Mapping [IMP]
MoSCoW Analysis [MSCW]
Value vs Complexity [VCC]
Eisenhower Matrix [EIS]
If there’s a prioritization method you are using that’s not listed above, please let me know, so I can this to the list!
Categorizing The Prioritization Frameworks
The frameworks were categorized based on two key criteria:
The level of end-user validation needed on the inputs to the prioritization framework used: if “customer value” is a crucial input to one of the prioritization frameworks being evaluated, then some level of data gathering or hypothesis validation exercise is needed with the involvement of the customer or end-user to validate the score.
The degree to which prioritization method inputs are highly qualitative (low score) or quantitative (high score) in nature: for qualitative data, the data is primarily based on observations and subjective inputs. For quantitative data, this is usually hard numeric data or fact, and much harder to ascertain in particular businesses or industries (e.g., B2B companies with less direct end-user involvement or data).
A score of 1 to 5 was assigned for each of the criteria above and then mapped to a Bubble Graph to show their relative position to each other.
Product Prioritization Frameworks Mapped:
You will notice that I’ve also colour coded three sections, related to the level of complexity and difficulty in implementing each method.
Methods that needed a high degree of user validation and quantitative scoring was treated as an “Advanced” method, mainly clustered to the top-right hand corner of the matrix. 20% of the prioritization methods are found in this category.
Any method that was the opposite, something with mostly qualitative scoring and almost no need for user validation, was treated as a “Basic” method, mainly clustered to the bottom-left hand corner of the matrix. 14% of the prioritization methods are found in this category.
Everything else (65% of evaluated prioritization methods) were categorized in the “Intermediate” section. Product managers who are looking to take their 2-by-2 prioritization to the next level can start with an Intermediate framework before adopting an Advanced one.
How Do I Choose The Right Framework?
Start asking yourself some qualifying questions, mainly around the type of data you can collect (qualitative vs quantitative) and the amount of time you have to validate your hypotheses with end-user interaction.
How much time do I have to make our decision on priority?
If you haven’t got a massive amount of time and only a handful of data points, perhaps choosing one of the Basic frameworks is right for you… for now. You can always upgrade to a more advanced framework later if you feel inclined to do so!Am I able to engage with end-users in detail to validate scoring inputs? Do have I have more quantitative data available to me?
Sometimes product manager will have a plethora of quantitative data to back up their decisions. For example, B2C products that log user activities for every step of the user journey may be more suitable for the Advanced frameworks.Does my team have a culture for performing data-based decisions? If you have an organizational culture that thrives off data for decision making, it makes more sense to mimic their working style with a highly quantitative framework as well. This may also help your ability to synchronize your mindsets and empathize with some stakeholders who have yet to be brought onside. Just make sure that you are able to agree on the data points and the methods for gathering them in an objective manner.
Once you have chosen a couple of frameworks that may suit your data analysis culture and needs, get familiar with the framework’s inner workings and simply try them out! Remember — there is no perfect decision, and choosing the right framework that suits your team is an iterative process.
Although this article doesn’t deep dive into any one framework, links to my favourite articles discussing how to best to implement that framework are provided. Enjoy!
“Advanced” Prioritization Frameworks
Cost of Delay and Weighted Shortest Job First (WSJF)
What is it: The Cost of Delay (CoD) is a crucial metric in lean management that represents the economic impact of a delay in project delivery.
If you only quantify one thing, quantify the Cost of Delay. — Don Reinertsen
When you take the CoD and divide it by your ‘Job size’ (or Duration, the time it takes to implement) you get the “Weighted Shortest Job First (WSJF)”, the smallest most valuable increment that you should work on first. See Scaled Agile’s guide here.
Pros: Focuses on smaller, more valuable chunks, rather than larger, less valuable pieces of work. Incentivises users to break down tasks into smaller pieces; otherwise, features won’t surface highly on WSJF ranking. Consistent approach minimizing personal biases.
Cons: Apart from using many calculations, the framework is a lot like your crazy ex — very pedantic, usually requires a certain amount of attention to detail, and can be high maintenance. Often can be disliked by your peers due to complexity.
Cost vs Benefit (Weighted Score)
What is it: A long list of features, and their drivers, such as revenue, cost, maintenance, compliance, risk, effort. Each driver is scored from 1 to 5 (i.e., Likert scale) or through other means, such as a High/Medium/Low rating. Each driver is also weighted (e.g., in percentage terms) to allow for a weighted score calculation. Refer to Airfocus’ guide here.
Pros: Quantifies feature importance and Return on Investment.
Cons: Drivers’ weights can be manipulated to favour part of your team’s personal preferences. Requires full team alignment on the different drivers and features involved, and the weightings used per driver.
ICE and RICE Scoring
What is it: An objective scoring system based on four criteria, ‘RICE’: Reach (e.g., breadth of users), Impact (e.g., level of impact per user), Confidence (e.g., how confident you are in the score provided, typically in percentage), and Effort (e.g., low/medium/high). ‘ICE’ Scoring simply excludes “Reach” from its calculation, so it may be simpler to adopt if you are newer to the RICE model. Refer to Intercom’s guide here.
Pros: Helps teams that are deciding between hard-to-compare ideas brought to the lowest common denominator of 4 variables. Quantifies total impact per time increment worked.
Cons: Predefined scoring factors, unlike the Weighted Scoring model, where you can define your own strategic criteria.
“Intermediate” Prioritization Frameworks
Kano Model
What is it: Customer satisfaction model developed in the 1980s by Professor Noriaki Kano. The framework classifies customer preferences into five categories, based on an assessment of customer satisfaction vs level of functionality. Refer to Folding Burrito’s extensive guide here.
Pros: Uses qualitative reasoning with less reliance on hard data. Visual tool for mapping features to satisfaction.
Cons: Doesn’t take into consideration cost, effort, complexity, or extrinsic monetary value.
Buy-a-Feature
What is it: Create a list of potential features and provide each with a price. Just like for a real product, the price can be based on development costs, customer value, or something else. Customers buy features that they want in the next release of your product, justifying their priority and why. Refer to Scrum.as guide here.
Pros: High in collaboration and rather visual. Setting a budget allows participants to get used to resource constraints in prioritizing features.
Cons: Does not take into consideration direct user validation. User features selected by participants may not be what the end-user / customer may want.
Story Mapping
What is it: a visual model to arrange user stories in a way that allows the team to see how functionality fits into the overall customer journey. The priority of stories are placed from top to bottom, typically based on value to users and business. Refer to Medium post by Alin Mateescu.
Pros: High in collaboration and rather visual. Like Buy-a-feature, a budget for several stories helps the team understand trade-offs in selecting one feature over another.
Cons: No quantitative measure of impact or amount of effort it takes to implement each element of the story map. Requires a good understanding of the average size of each story so that each card is roughly the same size.
Opportunity Scoring
What is it: Model that prioritizes development by comparing feature importance versus satisfaction. The model came out of the outcome-driven-innovation (ODI) process created by consultant Tony Ulwick in the 1990s. Refer to the Medium post written by Eric Eskey.
Ulwick also created the JTBD (Jobs to be done) framework, referring to the process a consumer goes through whenever she aims to change her existing life-situation into a preferred one, but cannot because there are constraints that stop them.
Pros: Can be used in conjunction with JTBD to create valuable conversations on what are the most critical problems you want to solve for your users.
Cons: Moderate investment needed to collate data and each criterion, then compare all of them in a chart/graph, as per the example above.
Affinity Grouping
What: a collaborative prioritization activity where your team brainstorms ideas and opportunities on sticky-notes. The team then works to place sticky notes into groups of similar themes, before choosing which ones work on or deliver first. See the Center for Care Innovations’ step-by-step guide here.
Pros: Highly collaborative and easy to explain and setup.
Cons: Ignores complexity and effort to deliver. No quantitative metrics used to size the effort involved in working on each feature listed in sticky-note. Affinity limited to the group involved, and may need to change drastically when you have influential team members that weren’t present but want to contribute.
Impact Mapping
What is it: a model to arrange all features and deliverables to the end goal, actor/user and the impact it has on each. Similar in format to story mapping with an emphasis on setting the ‘why’ (objective) and ‘who’ (user persona) before mapping impact and deliverables to them. Refer to Mozaic Works’ extensive guide here.
Pros: Works well in a highly agile environment that promotes collaboration and iterating fast. Assumptions, goals, and impacts are all made visible, allowing participants to understand and justify each feature based on impact and broader company objectives.
Cons: Ignores complexity and effort to deliver. No quantitative metrics used to size the effort involved in working on each feature/deliverable listed. Can quickly grow to an unmanageable size of goals, users, and impact, depending on the maturity of the business and specific problem being solved.
MoSCoW Analysis
What is it: a model to classify identified feature requirements into “Must do”, “Should have”, “Could have” and “Will not have” (or wishlist item). It is used to gain buy-in from key stakeholders on the importance of each requirement relative to each other. See ProductPlan’s guide to MoSCoW Prioritization.
Pros: Works well when the requirements are known or elicited in advance. Prompts participants of the exercise to choose what is a “Must” and what is simply a nice to have.
Cons: Only possible once the requirements are known. A high degree of subjectivity. One participant’s perceived “Must have” may well be someone else’s “Could have”. Can be prone to much debate, which could be settled with data but may require a fair bit of customer validation to do so.
Basic Prioritization Frameworks
Value vs Complexity
What: A quick 2-by-2 model that allows the team to evaluate each initiative according to how much value it will bring, and how difficult or complex it will be to implement. Similar to “Impact vs Effort” Matrix. Refer to Reforge’s guide here.
Pros: Simple to use for quick prioritization. Can identify “Easy wins” that are “high value” but “low complexity”, as well as larger items that bring large value, which can be a sign to break down into smaller value increments.
Cons: While value is easier to justify in a Likert score (1 to 5) based on relative value, the term “complexity” can be composed of many things, so it is important to ensure a common definition is known amongst your team before scoring.
Eisenhower Matrix
What: A quick 2-by-2 model that allows the team to evaluate each initiative according to how important the initiative is relative to its urgency. Allows users to sort out less urgent and important tasks, and which to delegate or not do at all — crafted based on principles from 34th President of the United States, Dwight Eisenhower. Refer to Luxafor’s guide to the Eisenhower Matrix.
Pros: Simple to use for quick prioritization. If sufficient limits per quadrant are set (budget), then a collaborative session can force team members to choose what is more important than not.
Cons: “Urgent” is subject to debate as it is highly subjective to the individuals in the team. One person may interpret this as “priority” rather than time “urgency”, or the question “if we didn’t do it today, what would happen”?. This model can also diminish in value when too many items are listed in a single quadrant (e.g,. 80% of features end up in the “Do” quadrant).
Conclusion
In the end, it really doesn’t matter which framework you use, so long as you
Have a constructive team dialogue
that invites participation in a safe environment
and allows constructive conversation
about what you think is higher or lower in priority
and why!
The biggest value gained from the frameworks above is the ability to create a forum for conversation, a place of psychological safety, and a frame for creativity. The outcome should focus less on having a list of features you decide to create, and more on having a dialogue for the right internal and external stakeholders to voice what they think matters the most and why.
If you want to adopt a framework but don’t know where to start as you are new to it all, then simply adopt one of the basic frameworks (e.g. Value vs Complexity) to begin with, then incorporate more quantitative measures (e.g., Cost of Delay) over time, should you deem it necessary to justify your more difficult and/or strategic product decisions.
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