Meet Robert: Bringing Design Thinking to Data Science Projects

I come from an entrepreneurial family so pursuing a business background with a focus on change management was a natural way for my professional and personal worlds to converge. A few years ago, I started exploring various books and examples of Design Thinking. This was also when the Lean Startup and the first contemporary corporate innovators were coming to the foreground. This background, a mix of events and interests, inspired me to start with my business partner our own company in Design Thinking training and supervising Design Sprints. Design Thinking is a great example of a no-nonsense attitude. During the workshops and training I can do what I like best: combining my academic background and professional expertise with helping people while gaining experience in new knowledge and tools.

Why work together with Young Mavericks?

Young Mavericks is a young company with a concrete vision and a constant drive to improve and innovate. I love that. Young Mavericks has distinguished itself from most other companies I have worked with by its can-do and common sense attitude and culture. I find it fun and challenging to introduce a group of junior data scientists, most with little professional experience, into the world of Design Thinking. One of the most interesting parts is training them in communicating with the internal and external clients to craft end products that are more relevant and impactful.

What does Design Thinking training look like?

We run a mini Design Sprint in the introductory training at Young Mavericks. We do this by presenting the trainees with a real case. I guide the new trainees through the first steps of the Design Sprint process for two days until the plans for the prototypes are ready. After that, the group begins creating the prototypes with real data. In the following months, I periodically meet with them to provide them more depth on Design Thinking. At this stage we dive deeper into the practical tools and key mindsets.

What is the added value of Design Thinking?

Conceptually, Design Thinking is used for understanding and solving problems; we define a problem, come up with ideas to solve it through the simplest solutions and then present the finished product to future users. Researching and analyzing both internal and external problems and their solutions for customers can range across various operations. One of the most helpful insights data scientists utilize to increase the impact of the design and data for organizations and customers is understanding why and how future users will use a new tool or information. Another important element of Design Thinking is to approach the work in small steps. This ultimately increases both the impact and speed of a project as we work to complete it with colleagues from other organizations.

NIBC Case: Performing Analyses Faster through Machine Learning

NIBC Bank and Young Mavericks started a text data mining proof-of-concept at the Agency Management and Operations departments. Text mining is a form of analysis in which relevant information is extracted from large amounts of text material. The solution supports the banks’ employees to provide clients with accurate and relevant information, almost in real-time. By automating document review processes, employees can focus on offering personalized customer services to their clients and leave the routine analyses to machines. The application is ready for implementation.

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Machines Learning the Lay of the Land and Signaling Mutations

The Netherlands is defined by water and our ability to manage it. In order to manage it we have to monitor it, and monitoring it requires large sets of input data and their analyses. Using machines to automate these data processes brings 21st century tools to the long tradition of Dutch water management. Young Mavericks specializes in the design, data mining and analysis, and machine learning aspects of digital technology and then trains data scientists to apply the technology with an open mind to diverse contexts. Our model allows different companies and organizations to gain freshly trained talent ready to meet the demands of specific data and information analysis. One of our recent governmental partners required up-to-date analysis of geographic mapping representing the complex blend of land and water under its jurisdiction.

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