Design Thinking in a Big Way

Collecting, converging, and accessing petabytes of data isn’t for the faint of heart. Some of the brightest minds in technology have applied their intellectual muscle to create innovative technical solutions that deal with big data. Recently, we have seen a lot of technical progress, but making big data systems effective for business decision-making has not progressed as quickly. In a recent study, a third of executives recognized that their organizations were using big data systems that “weren’t designed to meet their needs.” If the democratization of data is essential to advancing business decisions, it’s time to make volumes of diverse data far easier to work with.

At ClearStory, we are enabling organizations to move to a data-driven business culture by delivering products that are useful, easy to use, and accelerate insight. We made a conscious decision from the start to build design innovation into our development process. Over the next few days leading up to my session at the Strata conference, I’ll share a few of the principles and best practices that are driving our design-driven product development process.

Today’s principles speak to the mindset that we’ve adopted to balance our focus on design with the practical reality of delivering great products in a fast-moving market.

Guy in high heels1. Embrace Empathy

Empathy is defined as “the ability to understand and share the feelings of another.” Developing deep empathy for people who use your product is one of the most important traits a design, product and engineering team can have. It enables teams to make choices about the user experience not based on what is technically possible, but on what is most useful for people. Empathy is a mindset that is carried through everything a team does.\

For big data products, an empathetic mindset is often challenging because it is all too tempting to focus on technology platforms and forget about providing a useful experience. Overcoming this temptation and developing true empathy has the power to transform products from a random collection of knobs and buttons into a delightful experience that enables real people to solve important real-world problems.

At ClearStory, we fully embrace an empathetic mindset. We do this through constant customer interaction and spending time “walking in the shoes” of our users. We’re not simply talking to customers to gather usability feedback and prioritize features. We are working with them to understand how they want to reach a specific data-driven outcome through the use of our product. We iterate not just until the feature technically works, but until we feel that the experience is addictive and incredibly useful. With this mindset, we are able to invent innovative experiences.

This nuance of empathy is what makes design-driven products so great. Take a product like Nest’s Learning Thermostat that is transforming the way we interact with our cooling and heating systems. Behind everything complex, they believe a simple, beautiful experience matters. A home thermostat should not just functionally control the temperature of your home, but it should be a delightful experience. You should even be able to install one yourself without needing to be a certified electrician. Similarly, here at ClearStory Data, we believe that you don’t need to be a data scientist to work with diverse, complex data.

Guy in high heels2. Always Improving, Never Perfect

One of the most paralyzing attitudes designers and teams can have is to strive for the “perfect” solution. There is no such thing. The danger of striving for perfection is that during that process, no one agrees on what is perfect. The goal should be simply to create something better than what currently exists. This mindset liberates designers and teams from the shackles of perfection and allows them to focus on what is truly useful to customers, not what is perfect.

At ClearStory, this mindset allows us to engage with customers in a healthy feedback loop that constantly delivers customer value while at the same time providing hands-on feedback for quick iteration. As an example, take our process of developing our intuitive user controls. As a designer, I often prototype with the team in real-time, testing page layouts, interactions and labels to produce a “good enough” prototype to share with a customer or prospect. We then take that prototype out in direct customer interactions.

Over the last few months, we’ve iterated through a number of revisions to our intuitive user controls. Each design cycle involved feedback from a number of different customer teams. Our cross-functional team of product managers, engineers, and designers focused on actively listening to the customer experience and incorporated their learnings into the next product revision. The goal was to make the customer experience as intuitive and easy as possible. It is our view that design innovation comes from smart iterations rather than dreaming up that perfect design from the start.

Hopefully, I’ve given you something to think about when it comes to the role of design in big data product development. On a daily basis, we’re working to incorporate great design into the culture of our company. We’d love to hear from those of you who share this passion. Keep watching this space over the next few days for my next post and join me at Strata for a continued dialog on big data and design.

Upcoming Principle: “Everyone is a Designer”…