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Importance of Design Thinking for Data and Analytics

Design thinking is at the top of mind for business teams of big giants as well as startups. The traditional "If you build it, they will come," mentality has been taken from techniques like customer journey mapping and empathy-driven prototyping. Many companies are unsure how to implement it to improve their business - especially in areas like data analytics and decision sciences. The first step is to ask:  for whom are we designing and what is the problem they are experiencing? The second: to what end are we modeling the design - to boost consumption and engagement, improve performance, or to achieve scale? These same needs to be asked at the outset of any analytics effort. Here are five simple steps that are key to infusing analytics with a designer mindset.

1) Create a design framework that allows you to fail fast.

2) Empathize with your customer to impart emotion into your product.

3) Focus on problem-solving that allows for rapid experimentation.

4) Employ methods to inspire creative brainstorming across teams.

5) To design the killer solution, let nature be your guide.  

To read more visit at:  http://www.datanami.com/2016/02/16/what-design-thinking-means-for-data-analytics/

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