Published on | Prototyping: From UX to Front End — Medium Sejal Jamnadas

We live in the age of data. Everything from numbers, graphs, code, images, dots, lines, sound, video and hashtags. Sometimes we don’t even see the data. We just see that Amazon magically recommends us books we’d be interested in, or that Facebook happens to know the latest sales happening at our favourite online stores. We don’t generally pause to think about the fact that these ‘magic predictions’ come directly from our inputs; that they’ve been DESIGNED to make us feel heard, important and somewhat…special.

Every realm of our daily lives is feeding information into rich databases; from social networks, traffic sensors, weather meters, public cameras and other components gleaning our patterns of work, travel and living. The rate at which we generate data is outstanding; in 2017 alone, we will have generated more data than the previous 5,000 years of humanity. A mere 15–20 years ago, ‘intangibles’ such as brands and intellectual property was on organisation’s competitive advantage. Now it’s all about that voluminous, complex and rich ‘Big data’.

The growing challenge, however, is understanding how to structure the ‘mess’ and create authentic experiences with modern technology that is heavily dependent on data-driven insights.

Starting with the people

Earlier this year, Google Play and IDEO design consultancy held a series of workshops using human-centred design to understand the infinite possibilities for emerging technologies such as virtual reality, augmented reality (AR), digital assistants and ephemeral apps (apps you don’t need to download and only exist for a short period of time). Without being exposed to brands and features, the participants were given tangible blocks enabling them to be expressive with their imaginations and feelings.

The results? People were looking to be inspired and motivated by their digital assistants. They want AR to give them information when they need, but also to remove it just as instantaneously. Overall, people were not really excited by they capabilities of the technology itself, but more what the technology it enables them to do.

In the same way we analyse and understand data, its important to start with what people want, and not just what’s technically possible. Using a design approach to understand data and make it authentic and meaningful will ensure the results are lasting and impactful.

Traditionally, the inherent disparities between data and design meant that these professions sat across opposite ends of the technical-humanistic spectrum. Nowadays, it doesn’t make sense for technical analysts to not dabble in design or for designers to not use data as their primary medium for creating services and products. In all facets of an organisation dealing with data, we need interdisciplinary teams that constantly re-iterate how data inputs impact reality. As Tim Brown, founder of IDEO, states, “If the intelligence of our devices, systems, and relationships feels artificial, it will never stick.”

Data as the medium; design as the process

Data by itself is sluggish — dumb, raw material. Design, paired with analytics, allows for the data to be linked to references of time, space, history, demographics and emotions. The process of define, research, ideate, prototype, choose, implement and learn are fundamental to creating innovative solutions that integrate the needs of people, technology and business scope. The following sketch highlights the key tools designers use for the process of designing innovative experiences (adopted from Designing for Growth: A Design Thinking Tool Kit for Managers).

An iterative design approach is imperative to understanding how data could be more meaningful for users and save expensive time and resources on initiatives that have no impact.

But first, we need good data

Creating interesting and “heart-warming” experiences from data insights sounds all well and good. However, most organisations have huge bodies of pretty crap data.

Perhaps the more urgent imperative is to invest in machines that will ingest the data and put some structure to it. From a sustainability perspective, we need designers and data analysts to come in from the get-go to design where the data is collected, who can contribute to the inputs and understand how fields are linked. I can visualise office walls covered in data maps to remind employees that the accuracy and completeness of their data inputs have a huge impact on the bigger picture. Chuck in a few whiteboards and post-it notes, and you’ve created a nerdy hipster haven as an additional bonus.

The mindset shift

The biggest change will be getting designers to dive into a world of messy data and getting data scientists to adopt lateral thinking in the design process. Whilst the environment will dramatically change for all professionals, the fundamental mindsets of dealing with uncertainty and finding patterns will merge at this wonderful inflection point. Regardless of our professions, we will all be working together with complex data and human-centred design to co-create meaningful experiences for the future.

That’s right, more numbers and more working in teams. It’s going to be challenging, but a whole lot of fun. After all, predictions are easy, but people are complicated.

When data meets design was originally published in Prototypr on Medium, where people are continuing the conversation by highlighting and responding to this story.

When data meets design

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