Learn Design Thinking: Data Intelligence

“Big data” is yesterday’s news—algorithms and machine learning have dominated the press and given companies a way to parse through it all efficiently. Now, the focus has shifted to making that data work to solve your business challenges. Design can help companies unlock the value in data in ways that resonate even with the most rigid of business structures.

“For a business to be sustainable in the long term, understanding why your customers are doing things and what really motivates them is way more important than measuring click stream here and there,” says Vahndi Minah, Principle Director of Applied Data, whose work at frog “provides the intersection of the ‘what’ and the ‘why ‘of user behavior.”

For those looking to use data to generate ground-breaking ideas and to connect with users in meaningful ways, design thinking can help you see the opportunities to build a better data science practice within your organization. Here are some principles to ensure you’re getting the most value out of data intelligence:

A Foundation for Design Intelligence: Best practices within data intelligence are few and far between, which is why design thinking is helpful in providing methods to optimize without getting bogged down in data paralysis. The synergy between data, design and its output is what we call “design intelligence.”

Applying Data Design for Better Outcomes: Data intelligence can be incredibly informative and lead to really great outcomes when it comes to create new products, services and experience. But it’s important to focus that intelligence on how it will affect the end user, rather than focusing on the literal technology, or algorithms. To understand how data intelligence can create value for the human experience, we look to four enablers: humanize, expedite, transform, and discover. Start designing intelligently by asking yourself if any one of these four enablers might drive a design that fulfills the need of your customers in a new or previously unimaginable way.

Seeing Data Intelligence: In order to create real value with data intelligence, you must know how to look at the data in new ways. Data sets can be massive and overwhelming, and lead to what we call “data paralysis.” Visualizing those sets in new ways can help you to find patterns and understand new insights. From here, you can gain insights that help you create real value for your end-user.

Transformation through Intelligence: Data is only has good as the inferences and insights we gain from it. And while many companies are scrambling to collect massive amounts of data on their customers or end-users, it’s equally important to have the methodologies in place to properly analyze that data. Building out a proper data intelligence structure requires taking up new skill sets, as well as new partners in areas such as design, who can help you get the most out of your analytics.

For more on frog’s approach to intelligent data design, check out the LinkedIn Learning course, or get in touch with one of our data design experts today.