Designing for data journeys

We often hear about the importance of mapping and designing good user journeys. What perhaps isn't as commonly discussed is the importance and value of data journeys. All organisations, both B2B, B2C, and public, generate immense amounts of data. Having this data well mapped out, accessible, and under control is essential for several reasons. It ensures safety and efficiency and can generate value for both the organisation and its users when used correctly.

Design methodologies are perhaps most commonly associated with mapping consumer and user journeys and getting user insights. However, we can use these methods for more than that and in contexts that don't necessarily focus on people. Data and data liberation is one of them. Just like mapping the journey of a person who is going through a process to reach a goal (for example, a customer making a purchase on a website), the journey of data can also be mapped out and visualised.

What is a data journey?

Journey maps are a common design tool. They come in all shapes, sizes, and formats. Depending on the context, we can use them in a variety of ways. As designers, we are naturally user-focused, but we look at it in a slightly different way when it comes to data. Instead of mapping the touchpoints with a user, we focus on the journey of the data itself. In other words – we treat data like users. Of course, we can’t interview the data, but we can instead observe the data flow to understand how and where it goes.

By mapping this out, we can understand the current "as is" state and the pain points in relation to data sources, system owners, target systems, how it is being transferred, where it is being manipulated, duplicated, or enriched. Questions we ask can, for example, be: Is it API (Application Programming Interface) driven and adhering to cybersecurity guidelines? Does it exist in the cloud or on-premise?

This helps us understand the opportunities for data optimisation and improvements in terms of quality and accessibility. We also retrieve insights by interviewing the owner of the data or other stakeholders to understand how they use, manipulate, enrich or distribute the data.

When mapping out data flows, we start with the broad picture and then narrow it down. We look at how data interacts with each other and other systems and applications. By drawing out dataflows, we can see if the data is fully optimised, accessible, and in the correct format for users, if it can be decoupled from an application, and if it causes any process bottlenecks.

What’s the purpose of designing data journeys?

As much fun as we may find mapping and designing journeys, we don't do it without a purpose. So, what's the point in designing data journeys? Well, there are several good reasons. In today's organisations, there are immense amounts of data floating around. No matter if we're talking about big corporations, B2B, consumer market, or public institutions – they all generate and handle large amounts of data. This data can be a great asset and provide organisations and businesses with valuable information, both commercially and from a more extensive, societal perspective. However, this requires that there is confidence in that data. For there to be confidence, we have to ensure that the data is available in high quality, that it’s reliable, and optimised for interpretation and modelling. By mapping, we can uncover cost-saving opportunities through the removal of redundant, incomplete, or duplicated data, as well as presenting it in an indexed and user-friendly format. These are only a few of the important aims when designing data journeys.

Apart from providing useful information, there are also other reasons for managing data – safety reasons, for one. When we have complete control and overview of our data, it allows us to eliminate cybersecurity issues, as well as help us comply with GDPR.

By understanding how and what data flows through your application, we can make it safer and more accessible. When mapping data, we can iterate on the design by examining both internal and external data movements. We can design for removing data redundancy, limiting data to be moved or manipulated, and removing any unnecessary hoops that data has to pass through.

Unleashing the potential in data

As a society, we’re only seeing the beginning of the digital transformation, including data journeys. The data we’re producing has an enormous potential that we’re only beginning to take advantage of. Much like the industrial revolution changed our world, we’re now living the data revolution, which is happening extremely fast and simultaneously across all parts of society. There are already examples of companies who build their entire business model around data systems, for example, Tesla and Amazon. I’m convinced that this is the way to go- data will be at the heart of all business going forward.

It will be – and is – in every organisation’s interest to learn how to manage complex digital product portfolios and to formulate strategies for data handling that is robust, secure, and cost-effective.Design and designers can, and should, help with this.

And, most importantly – it’s up to us to make data do good – and to do good for everyone. Dealing better with data is our window into tackling business challenges and also social challenges. It can help on the way to make companies, customers, societies, and people thrive.