How to Prioritize Problems to Solve: A Framework for Entrepreneurs

The Entrepreneur’s Dilemma: Too Many Problems, Limited Resources

You’ve probably been there: a dozen ideas swirling in your head, each one seemingly brilliant. Maybe you’ve identified multiple pain points in your market, or your team has generated a long list of potential features to build. The question that keeps you up at night isn’t “what should I build?” but rather “what should I build first?”

Learning how to prioritize problems to solve is arguably the most critical skill for any entrepreneur or product leader. The difference between successful founders and those who struggle often comes down to this single ability: choosing the right problem at the right time.

In this guide, you’ll learn proven frameworks for prioritizing problems, discover how to validate whether a problem is worth solving, and avoid the common traps that lead entrepreneurs astray. Let’s dive into a systematic approach that will help you make better decisions about where to invest your precious time and resources.

Why Most Entrepreneurs Get Problem Prioritization Wrong

Before we jump into frameworks, let’s understand why prioritization is so challenging. Most founders make one of these three critical mistakes:

Mistake #1: Solving Problems They Find Interesting (Not Important)
It’s easy to get excited about technically challenging or intellectually stimulating problems. But “interesting to solve” doesn’t equal “valuable to customers.” The graveyard of failed startups is filled with brilliant solutions to problems nobody actually cared about.

Mistake #2: Following the Loudest Voice
One vocal customer requests a feature. Then another. Before you know it, you’re building based on whoever screams loudest rather than what moves the needle for your business. This reactive approach leads to a Frankenstein product that serves no one well.

Mistake #3: Ignoring Market Validation
Many entrepreneurs prioritize based on gut feeling or personal assumptions about what customers need. Without real data, you’re essentially gambling with your most valuable asset: time.

The ICE Framework: A Simple Starting Point

One of the most accessible frameworks for prioritizing problems is ICE, which stands for Impact, Confidence, and Ease. Here’s how it works:

Impact (0-10): How much will solving this problem move the needle for your business? Consider both the number of people affected and the intensity of the pain.

Confidence (0-10): How sure are you that this is a real problem worth solving? Do you have data, customer interviews, or evidence to back it up?

Ease (0-10): How simple is this problem to solve given your current resources, skills, and constraints?

Calculate an ICE score by averaging these three numbers. Problems with higher scores should generally be tackled first. For example:

• Problem A: Freelancers struggle to track expenses (Impact: 8, Confidence: 9, Ease: 7) = ICE Score: 8.0
• Problem B: Enterprise customers want advanced analytics (Impact: 6, Confidence: 5, Ease: 3) = ICE Score: 4.7

In this case, Problem A would be prioritized despite Problem B potentially having higher revenue potential, because you can solve it confidently and quickly.

The RICE Framework: Adding Reach to the Equation

RICE builds on ICE by adding a “Reach” component, making it especially useful for product teams:

Reach: How many people will this impact within a given time period (usually per quarter)?

Impact: Scored on a scale (0.25 = minimal, 0.5 = low, 1 = medium, 2 = high, 3 = massive)

Confidence: Percentage score (100% = high confidence, 50% = low confidence)

Effort: Person-months of work required

The formula: RICE Score = (Reach × Impact × Confidence) / Effort

This framework forces you to think about scale. A problem affecting 10,000 users weekly scores higher than one affecting 100 users, even if the individual pain is similar.

The Kano Model: Understanding Different Types of Problems

Not all problems are created equal. The Kano Model helps you categorize problems into four types:

Must-Haves (Basic Needs): Problems that, if unsolved, make your product unusable. These are table stakes. For example, if you’re building an email app, reliable message delivery is a must-have.

Performance Needs: Problems where solving them better creates proportional satisfaction. Faster load times, better search results, or more accurate recommendations fall into this category.

Delighters: Unexpected solutions that create disproportionate satisfaction. Think of Slack’s custom emoji or Spotify’s annual “Wrapped” feature - nobody expected these, but they became beloved.

Indifferent: Problems that customers don’t actually care about solving. These are traps to avoid.

Your prioritization should ensure must-haves are covered first, performance needs are continuously improved, and you occasionally invest in delighters that differentiate your product.

Validating Problem Severity: The Evidence-Based Approach

Frameworks are useful, but they’re only as good as the data you feed them. How do you actually validate that a problem is worth prioritizing? Here’s a practical approach:

1. Look for Frequency
How often does this problem occur? A daily frustration warrants more attention than something that happens quarterly. Track mentions across customer conversations, support tickets, and community discussions.

2. Measure Intensity
How painful is this problem when it occurs? A minor annoyance versus a complete workflow blocker should be weighted differently. Pay attention to the emotional language people use when describing the problem.

3. Count Real Users
How many people actually experience this problem? One enterprise customer might generate ten support tickets, but that doesn’t mean the problem affects your entire user base.

4. Assess Workarounds
Are people creating elaborate hacks to solve this problem themselves? The existence of complex workarounds is a strong signal that the underlying problem is worth addressing.

Using Real Community Data to Prioritize Problems

One of the most overlooked sources for problem validation is online communities where your target customers already hang out. Reddit, in particular, is a goldmine of authentic pain points because people discuss their frustrations openly without a sales filter.

When you’re trying to prioritize which problems to solve, having evidence-backed data from real discussions can transform your decision-making process. Instead of guessing at problem severity, you can see actual quotes from potential customers, understand the language they use, and gauge how widespread the issue really is based on upvotes and discussion volume.

This is where PainOnSocial becomes invaluable for the prioritization process. Rather than manually scouring through hundreds of Reddit threads, it analyzes curated subreddit communities and surfaces the most frequent and intense problems people are actually talking about. Each pain point comes with a smart score (0-100), real quotes, permalinks, and upvote counts - giving you the evidence you need to confidently prioritize.

For example, if you’re debating between solving Problem A or Problem B, PainOnSocial can show you that Problem A has been mentioned 47 times across different threads with an average score of 85/100, while Problem B only appears 8 times with lower intensity. That’s concrete data you can plug into your ICE or RICE framework.

The Opportunity Cost Question

Here’s a question that cuts through analysis paralysis: “If I work on this problem, what am I not working on?”

Every decision to prioritize one problem is implicitly a decision to deprioritize others. Make this trade-off explicit:

• What revenue might you miss by not solving the other problems?
• What strategic opportunities could you lose?
• What competitive advantages might erode?

Sometimes the best choice isn’t the problem with the highest score, but the one where the opportunity cost of not solving it is unbearable.

The 2×2 Matrix: Effort vs. Impact Visualization

Visual thinkers love the classic 2×2 matrix approach. Plot your problems on two axes:

• Y-axis: Impact (low to high)
• X-axis: Effort (low to high)

This creates four quadrants:

Quick Wins (High Impact, Low Effort): Your top priority. These are no-brainers that deliver results fast.

Major Projects (High Impact, High Effort): Important but require significant resources. Plan these carefully and break them into phases.

Fill-Ins (Low Impact, Low Effort): Nice-to-haves that can fill gaps when you have spare capacity.

Time Wasters (Low Impact, High Effort): Avoid these completely. They’re resource sinks that won’t move your business forward.

The “Jobs to Be Done” Lens

Sometimes the best way to prioritize problems is to step back and ask: “What job is the customer trying to get done?”

People don’t want a quarter-inch drill; they want a quarter-inch hole. Understanding the underlying job helps you prioritize problems that actually matter to customers’ goals rather than surface-level feature requests.

For each problem you’re considering, ask:

• What core job is this problem preventing them from completing?
• How critical is this job to their overall workflow or life?
• What are they using instead to get this job done (competitors or substitutes)?

Prioritize problems that prevent important jobs from being completed well.

Balancing Short-Term Wins with Long-Term Vision

A common trap is optimizing entirely for quick wins while neglecting strategic, long-term problems. Your prioritization framework should balance both:

The 70-20-10 Rule: Allocate roughly 70% of resources to core problems that drive current business, 20% to emerging opportunities, and 10% to experimental ideas that might transform your business.

This ensures you’re building sustainable momentum while staying innovative.

Creating Your Personal Prioritization System

The best prioritization framework is one you’ll actually use. Here’s how to create a sustainable system:

Step 1: Choose one primary framework (ICE or RICE work well for most)

Step 2: Set up a simple spreadsheet or tool to track problems and scores

Step 3: Review and update scores weekly or bi-weekly

Step 4: Use community data and customer feedback to validate your assumptions

Step 5: Make decisions transparent to your team so everyone understands the “why”

Consistency matters more than perfection. A simple system used regularly beats a complex one that’s abandoned.

Common Red Flags to Watch For

As you prioritize problems, watch out for these warning signs:

HiPPO Syndrome (Highest Paid Person’s Opinion): When decisions are made based on seniority rather than data

Shiny Object Syndrome: Constantly chasing new problems instead of finishing what you started

Analysis Paralysis: Spending so much time prioritizing that you never actually solve anything

Echo Chamber Effect: Only listening to customers who look like you or think like you

Build checks into your process to catch these before they derail your prioritization.

Conclusion: Start Making Better Decisions Today

Knowing how to prioritize problems to solve isn’t about finding the perfect formula - it’s about making better decisions consistently. The frameworks we’ve covered give you structure, but the real skill is combining data, intuition, and strategic thinking.

Start by choosing one framework that resonates with you. Apply it to your current list of problems. Validate your assumptions with real evidence from customers and communities. Then make a decision and move forward.

Remember: the cost of choosing the wrong problem is often less than the cost of choosing no problem at all. Successful entrepreneurs don’t just think about prioritization - they act on it.

What problem will you tackle first? The answer might be clearer than you think once you apply a systematic approach to finding it.