Design Dive - An Immersive workshop on Design Thinking
Design Dive (D2) is a 2-hour programme that offers leaders and managers a simulative experience of the powerful process of Design Thinking. The workshop offers a design challenge that provides an overview of the steps of Design Thinking through a quick hands-on experience of application and feedback.
Outline/structure of the Session
Participants work in pairs to Empathize with their partner’s needs, Ideate to find solutions and Prototype the same for Test and validation. The whole process is run a single exercise focusing on iterative “learning by doing” methodology, interspersed with case examples and videos.
• Discussion on observations, takeaways, and applications of Design Thinking based approach, from culture change to employee engagement and the way forward.
Leveraging simulations and activities which help explore dimensions of Whole-Brain Thinking, the programme combines right-brain imagination with left-brain logic and analysis; increases the capacity for breakthrough ideas and insights that lead to success. Through the strong use of experiential techniques, Audio-Visual methods and “learning by doing” approach, the programme helps participants walk away with new tools and experiences that are useful and innovative, in application and impact.
Business Leaders, Managers, Engineers
schedule Submitted 5 months ago
People who liked this proposal, also liked:
Nitin Ramrakhyani - Designing with a biased mindNitin RamrakhyaniGroup Product ManagerADP India Ltd.
schedule 4 months agoSold Out!
Biases are mental shortcuts for decision making. It’s like applying automatically and subconscious a rule of thumb. That is fast and saves energy but can lead to errors. To build great customer experiences, it's a no-brainer that we need to keep the customer at the center, understand their needs & pain points, but the problem interpretation & proposed solution often gets overpowered by our cognitive biases. For a product manager & designers, these biases can lead to bad decisions. But being aware of these biases and keeping them at bay, with a sound data-driven design approach can save the day.
I'll be talking about some real-life examples of such situations and share experience/ learnings on how we approached it in past.