Design Thinking for Data Transformation
IBM Data Science Elite team & IBM C&CS CDO
During my time at IBM, I developed a framework where I merged data design with the core concept of design thinking methodology.
Working side by side with IBM clients and data scientists on the development of AI tools, I realized the need for clients to better understand how data is being collected and organized within their companies. Clients need to first discover the business opportunities hidden in their company's data before using that data to implement AI solutions.
Data design is crucial to discovering overlooked components of industries’ data: these insights reveal new business opportunities that can allow companies to leverage AI and ML models and achieve their strategic business objectives. The visual organization of information displays patterns and relationships existing within the complex systems that collect and organize organizations' data.
That is why I developed this framework, and used it with more than 15 IBM Data Science & AI Elite Clients, including Lufthansa and James Fisher & Sons ---- to help these companies understand and anchor their data to a concrete AI solution and target specific business problems.
The above images are an examples of a few activities included in the framework developed for the
IBM EMEA Data Science Elite Team.
Data design is crucial to gaining new insights into industries’ data: these insights reveal opportunities that can help companies achieve strategic business objectives. The visual organization of information displays all the patterns and relationships existing within the complex systems that collect and organize a company's data. To visualize the tangled webs of connection that link data together, it’s essential to unravel them and empower enterprises to gain new insights into the potential of their business.
+ Design Thinking
Design thinking is an approach commonly adopted in many industries today. At IBM, we have been using design thinking for years. The goal is to place end user needs at the center of every solution we develop. We embrace design thinking principles as we help clients find the right solutions to their problems and needs.
= Data Strategy
By merging data design with design thinking methodology, we created a framework tailored to craft innovative strategies, enabling companies to renew their organization and fully exploit their data. If the principles of design are applied to visualize and understand data, and that data is used to advise development techniques focused on end user needs, then the result is a systematic approach to achieving objectives. Data Strategy is then, by definition, a data-driven approach that drives user-centered design to achieve business objectives.
To elaborate more about this framework and the adoption of data design into design thinking, I developed this website.