Most technology projects don't fail during execution.
It fails before it even begins.
Companies invest in digital systems, platforms, and solutions expecting increased efficiency and results. However, many of these projects fail to achieve the desired impact.
In most cases, the problem is not in the development. It's in the definition.
Why do technology projects fail?
Technology projects fail primarily when they start with the solution.
Before understanding the problem, the context, and the user, the discussion is already focused on functionalities, architecture, or tools.
This creates structural misalignment.
Technology begins to respond to a perception, not to a real need.
Key impacts of starting with the solution
When the problem is not well defined, three consequences frequently arise:
- development misaligned with the business
- low adoption by users
- rework and increased cost
In this scenario, technology does not solve the problem.
It only accelerates the mistake.
The role of Design Thinking in technology
Design Thinking is a structured approach to understanding problems before solving them.
When applied to technology, it allows:
- to deepen the understanding of the business context
- identify real user needs
- Validate hypotheses before development.
- reduce investment risk
At Paipe, this approach is part of the process. Building digital solutions by combining research, user journey analysis, strategy, and development to create more efficient and business-aligned experiences. This service can also be contracted separately to assist companies that want to understand their pain points before starting a technology project.
How to structure technology projects in practice.
Companies that manage to generate results with technology follow a different logic.
Instead of starting with the solution, they structure the problem, validate hypotheses, and only then move on to development.
This process involves:
- understanding the context
- immersion in the problem
- validation with users
- tests before construction
This approach increases accuracy and reduces risks in technology investment.
A practical example of this approach can be seen in the Santista case.
The company faced a significant challenge: a large volume of documents, difficulty accessing information, and low efficiency in data use.
Before developing any solution, the problem was structured.
From this, a solution was built combining artificial intelligence, data organization, and information design.
The results included:
- reduction in reading and comprehension time
- faster onboarding
- greater inclusion of employees
- better organization of information
Design played a central role in transforming complex data into accessible and usable information.
When to apply Design Thinking to technology projects
Design Thinking is especially relevant when:
- There is a lack of clarity about the problem.
- users are not well mapped
- There is a high risk of rework.
- Investment in technology is significant.
In these cases, structuring before developing significantly increases the chance of success.
Conclusion
Efficiency in technology is not just about developing better technologies.
It's about building the right solution.
Companies that better structure their problems before developing tend to reduce failures, optimize investments, and generate more results with technology.
