How to avoid building a solution in search of a problem
In a world driven by innovation, the pressure to create the next big thing often leads teams and organizations to build solutions without fully understanding the problems they aim to solve. As someone who has worked extensively in content strategy, knowledge management, and emerging technologies like generative AI, I’ve seen firsthand the risks of misaligned initiatives. Whether it’s launching a flashy tool or implementing new workflows, the consequences of building “solutions in search of problems” can be significant: wasted resources, disengaged teams, and lost opportunities.
1. Start with the problem, not the tech
The allure of technology can be blinding. I’ve worked on projects leveraging tools like SharePoint, Notion, and custom GPTs. While these tools have immense potential, their success hinges on understanding the user pain points they address. For example, when developing a custom GPT named “Policy Writing Buddy,” the focus wasn’t on the AI itself but on the inefficiencies and inconsistencies in policy drafting that needed solving. The tech was merely a means to an end.
Takeaway: Anchor your initiatives in clear, validated problems. Don’t retrofit problems to justify a shiny new tool.
2. Validate the problem before prototyping
It’s easy to assume you understand a problem because it “feels obvious.” Yet, assumptions often diverge from reality. For instance, when building frameworks for collaboration tools like Confluence or SharePoint, I’ve observed that what leadership perceives as inefficiency often stems from lack of user training or misaligned workflows — not necessarily the absence of a tool. Before developing content templates or launching new systems, I engage end-users to understand their real challenges.
Takeaway: Use surveys, interviews, and pilot programs to validate problems with stakeholders at all levels.
3. Think incrementally, act strategically
Large-scale overhauls often fail because they try to solve every conceivable problem at once. While working with a Kubernetes startup, I helped implement incremental changes to the GTM strategy rather than a sweeping pivot. This approach not only allowed for easier adjustments but also ensured each step was measured against tangible outcomes.
Takeaway: Break down solutions into smaller, testable components to ensure alignment with the intended problem.
4. Build a feedback loop
Solutions need ongoing evaluation. While mentoring teams on creating editorial calendars and playbooks, I emphasize the importance of feedback loops. For example, a playbook for ChatGPT adoption wasn’t a static document — it evolved based on team usage patterns and challenges.
Takeaway: Regularly revisit your solution. Problems evolve, and your solutions must adapt to remain effective.
5. Know when to pivot or stop
Not every idea will succeed, and that’s okay. While working with a federal cloud initiative, we encountered several tools that, despite initial promise, failed to resonate with the team’s needs. Recognizing these failures early saved us from sinking more time and resources into non-viable solutions.
Takeaway: Be willing to abandon or pivot solutions that fail to meet their objectives.
Conclusion
Avoiding the trap of building solutions in search of problems is both an art and a discipline. By starting with clear problem identification, validating assumptions, and maintaining a user-first mindset, you can create solutions that not only work but resonate.
As technology evolves, the temptation to chase innovation for its own sake will only grow. Let’s commit to meaningful, problem-driven progress.
Will Kelly is a writer, strategist, and keen observer of the IT industry. Medium is home to his personal writing projects. His professional interests include generative AI, cloud computing, DevOps, and collaboration tools. He has written for startups, Fortune 1000 firms, and leading industry publications, including CIO and TechTarget. Follow him on X: @willkelly. You can also follow him on BlueSky: willkelly.bsky.social.
