Design Thinking never occurs in a perfect scenario. Many times the initiative is driven from necessity to change or be disrupted. In moments of turmoil and decline, a 180-degree change is vital. How do we navigate bureaucracy and long-established organizational structure to re-align the vision for growth and scale ideas organization-wide?
Change and transformation are major concerns and drivers for organizations. Adopting new practices and processes to achieve business goals has always been a part of the business. But now, there's increased pressure and desire to bring in new methods to respond to market-, customer-, and internal business needs.Design thinking and innovation practices are two ways that businesses are attempting to disrupt their patterns and unlock creativity to create new and novel solutions. While they have some shared goals, these two realms do not always mesh cleanly.In this talk, George White, Chief Innovation Officer at Cantina, will highlight where design thinking and innovation practice diverge, where they overlap, and how you can leverage both to build an organization that is flexible, creative, and innovative.
-Balance the responsibility for Design Thinking and Design Doing
-Optimize the balance of strategic and analytical designers
-Standardize core principals and missions of the company at large
-Develop best practices that align with culture and efficiency
-Utilize technologies as a tool to deliver innovative value, considering AI as essential
-Find the sweet spot between human-centered insight and machine intelligence to reach comprehensive, valuable solutions
-Adopt digital transformation strategies to enable continuous improvements
-Apply the design thinking methodology to complex digital transformation strategy
With so much information at your fingertips, empathy presents exciting opportunities, as well as complexities. With a massive amount of transactional data, balancing the qualitative connections, human-driven insights, and strategic vision native to design thinking builds much larger implications.Is the future of AI about more data or less?
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