• An Art & A Science: How to Apply Design Thinking to Data Science Challenges

    We hear it all the time as managers: "what is the data that backs up your decisions?" Even local mom-and-pop shops now have access to complex point-of-sale systems that can closely track sales and customer data. Social media influencers have turned into seven-figure solopreneurs from digital advertising analytics. In 2023, globally, we will create three times the data we did in 2019, and by 2025, it is estimated that 181 zettabytes of data will be generated (that is 181 followed by 21 zeros). Data is becoming a critical, arguably inextricable, part of business operations in our modern context. Data-driven decision-making (DDDM) uses data to inform decisions rather than relying on intuition. The digital era has given rise to the importance of data science for business applications. This technical note explores how different design thinking principles can assist the data-driven processes in a project.
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  • Fizzy Fusion: When Data-Driven Decision Making Failed

    This case presents an inventory challenge. The goal of the case is to encourages students to redefine problem statements that Fizzy Fusion is faced with and to use innovative thinking to come up with solutions that can address the core underlying problem that the company is facing. The case encourages students to think from the perspective of the customer to solve data problems.
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