Prioritising features is a challenge for many product teams. Limited resources mean balancing new development with maintenance is essential.

Start with first principles: Does this feature align with your business’s North Star and solve real customer problems? As Jason Fried and David Heinemeier Hansson from 37Signals all too often say, trust your gut. Will it take your product in the right direction? Yes or no. Simple as that.

However, most of us don’t have Jason’s and David’s freedom. They own their company and can do pretty much whatever they want. For the rest of us? We’re likely constrained by our company’s context. Prioritisation often comes down to moving the needle on business objectives, set out by leadership or the C-suite.  

So, what happens when you have competing features and find yourself in a veritable Sophie’s Choice situation, forced to choose between multiple features? Equally, how do you justify that choice to others in your organisation? One thing people can’t argue with is numbers.

There are plenty of frameworks to help with this: Value vs. Effort, Kano Model, MoSCoW, RICE, Pasta, you name it. But in this post, I’m going to argue for a far simpler heuristic test, one that I’ve put to the test in practice.

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Prioritisation Made Simple: The Numeric Formula

The formula prioritises features using four key criteria: revenue potential, user impact, strategic alignment, and technical feasibility. These ensure decisions are outcome-driven and focused on creating value.

• Desirability: Does this feature align with what our target customer want and need?
• Feasibility: Can we actually build it given current resources and tech stack?
• Viability: Does it contribute to achieving product-market fit and drive business outcomes?

Each criterion is scored on a scale of 1-4, reflecting its impact and effort. For example:

Scoring Criteria	Score 1	Score 2	Score 3	Score 4
Desirability	No clear customer need	Some interest, low demand	Clear problem-solution fit	High-demand, must have
Feasibility	Major blockers, unlikely to deliver	Significant effort required	Achievable with existing resources	Easy to build, low risk
Viability	No business value	Limited ROI potential	Strong alignment with strategy	High ROI, critical to success

Map each feature across the criteria to understand its potential. Adjust the weightings for each criterion to reflect what matters most in your company’s context, ensuring alignment with your strategic priorities. After this, calculate the weighted average to rank features objectively.

Conversely, if it’s an existing feature, refine the scoring criteria to match a suitable goal, like optimisation. For example, adjust desirability to measure how well the feature drives customer support efficiency or boosts conversion rates. Tailor the criteria to align with the specific outcomes you want to achieve.

Here’s the example code in Python.

def calculate_priority(d, f, v):

    # Weights (total = 10)

    weights = [4, 3, 3]

    # Calculate weighted score

    score = (d * weights[0] + f * weights[1] + v * weights[2]) / 10

    return round(score, 2)

# Example features

features = [

    {“name”: “Feature A”, “d”: 4, “f”: 3, “v”: 4},

    {“name”: “Feature B”, “d”: 2, “f”: 3, “v”: 2},

    {“name”: “Feature C”, “d”: 3, “f”: 4, “v”: 3},

]

# Calculate and display scores

for feature in features:

    score = calculate_priority(feature[“d”], feature[“f”], feature[“v”])

    print(f”{feature[‘name’]} Priority Score: {score}”)

Suppose you’re deciding between improving the recommendation algorithm for Disney+ (Feature A) and adding a new homepage personalisation feature (Feature B). Using the scoring criteria, you assign the following scores:

• Feature A: Desirability 4, Feasibility 3, Viability 4 → Weighted Score = 3.7
• Feature B: Desirability 3, Feasibility 4, Viability 3 → Weighted Score = 3.3

Feature A scores higher, making it the priority based on potential impact and alignment with goals.

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Prioritising with Outcomes: Don’t Build for the Sake of Building

In order for this to be effective you need to prioritise with outcomes. Prioritisation isn’t about shipping things. It’s about shipping the right things that move the needle toward a specific, measurable outcome. Every feature or product decision should map directly to your team’s OKRs or strategic goals. If it doesn’t, it’s noise.

I’ve seen too many teams fall into the feature factory trap — pumping out shiny new things without a clear idea of why they’re doing it or what it’s supposed to achieve. Back when I worked at a large financial institution, this was the norm. Features got built because someone thought they sounded good, not because they actually solved a problem or made a difference. Be relentless in your pursuit of outcomes.

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Final Words

If you’ve read this far, I hope you’ve realised that the goal of the Numeric Formula isn’t to blindly trust the numbers. It’s a tool to help you contextualise the features you’re working on and assess how they align with your product outcomes.

Ultimately, the key is to deeply understand your customer, your market positioning, and your target outcome.