Problem Statement Examples
Example 1: Slack (Early Problem Statement)
Problem Framing Narrative:
I am: A software developer on a distributed team
- Working across multiple time zones with teammates I rarely see in person
- Collaborating on complex technical projects requiring frequent communication
- Drowning in email threads that are hard to follow and unsearchable
Trying to:
- Communicate in real-time with my team without losing context or important decisions
But:
- Email is too slow and threads get buried
- Skype/IM is ephemeral—conversations disappear and can't be searched later
- Important decisions get lost, forcing me to re-ask questions or hunt through old messages
Because:
- No tool combines real-time chat with persistent, searchable history
Which makes me feel:
- Frustrated, inefficient, and disconnected from my team
Context & Constraints:
- Distributed teams across time zones
- Need for asynchronous + synchronous communication
- Must integrate with dev tools (GitHub, Jira, CI/CD)
Final Problem Statement: "Distributed software teams need a way to communicate in real-time with persistent, searchable history because email is too slow and IM is ephemeral, which causes lost context and repeated questions."
Example 2: Bad Problem Statement (Solution in Disguise)
Problem Framing Narrative:
I am: A product manager
Trying to:
- Use AI-powered analytics
But:
- We don't have AI features
Because:
- Our competitors do
Which makes me feel:
- Behind the times
Final Problem Statement: "We need AI-powered analytics to compete."
Why this fails:
- "Trying to" is a solution, not an outcome
- "But" is a missing feature, not a barrier
- "Because" is competitor-driven, not user-driven
- "Makes me feel" is about the PM, not the user
How to fix it: Reframe from the user's perspective:
I am: A product manager analyzing user behavior across multiple features
Trying to:
- Identify which user segments are at risk of churning within the next 30 days
But:
- Current analytics require manual SQL queries and hours of data wrangling
- By the time I identify at-risk users, many have already churned
Because:
- Our analytics tools don't surface predictive insights automatically
Which makes me feel:
- Reactive instead of proactive, and like I'm failing to retain customers
Final Problem Statement: "Product managers need a way to proactively identify at-risk users before they churn because current analytics are manual and slow, which causes missed retention opportunities."