Stay curious
Think back to the last time you discovered something surprising or unexpected. Did you have the desire to learn more? That feeling is curiosity, and like any other skill, it requires nurturing over time. When you think something should be explored, follow that impulse and see where it leads. Hunches can often lead you down new and rewarding paths.
Keep asking why
Ask questions about the world around you. Be humble and honest about what you know and what you don’t know. Identify unanswered questions to explore rather than just problems to solve. If you create an account on our Enterprise Design Thinking platform, you can try out our “5 Whys” activity.
Dig deeper
Intentionally shift your point of view to see opportuntities more clearly. Go out, experience, and explore rather than simply reading about it. Observing is better than listening in most cases. Imagine trying to visualize a person’s daily routine based solely on a series of phone interviews versus spending the day with them.
Enterprise systems are made of many working parts. Explore problems from multiple angles to view all possibilities. Go deep, but also zoom out and consider the entire ecosystem of users, environment, and needs. What is the end-to-end journey?
Acknowledge bias
People are inherently prone to bias, whether personal, cultural, social, or otherwise. Your view of the world is shaped by your experiences. When you put yourself in someone else’s shoes, be aware that you’re still coloring their world with your perspective. Aim to keep your view of the world as unbiased as possible. Evaluate the research based on your users’ outlook rather than your own.
Where do you come in?
As a team and individual, practice curiosity to ensure it’s a skill that’s strengthened over time.
The Explorer:
- Where does our experience fit within the larger user journey?
- What bias do I bring to my team?
- Where can I physically go to learn more?
- What questions and assumptions should we prioritize to answer?
The Guide:
- What hunches have I ignored?
- What patterns emerge from this data?
- What are the research implications?
- How can I strive for unbiased research?