Data Visualisation in the Financial Industry
Making graphs is easy, conveying a message is hard. In this article we explore what you need to consider when developing data visualisations for your business. And it starts with three simple questions.
- Why are you visualising?
- How are you visualising?
- Where is your data coming from?
1. Why are you visualising?
Before you begin any design or development exercise we need to understand:
- Who your audience is.
- Why do they need to view their data.
Organisations want to consume data because they are trying to make a decision or perform an action. Good data visualisation should empower them to do this, with the minimum effort required to interpret the data.
So, to create these great visualisations, we need to have a firm understanding of our user needs, and how data visualisation can meet these needs.
Examples of user needs which would benefit from clear visualisations:
- A homeowner wants to have more money at the end of the month, by managing expenses more effectively
- A CEO wants to make the company as successful and profitable as possible by ensuring their company’s products are priced correctly in the market.
- An administrator wants to efficiently identify and amend incorrect records.
In all cases, making it easier for users to consume and understand the data makes it easier for their needs to be met. The first mistake many teams and organisations make when developing visualisations is to skip over identifying user need and to jump straight into the tech. This approach has led to the avalanche of 'interesting but valueless’ BI dashboards we see around us in the financial industry today.
2. How are you visualising?
Once you understand user needs, you can begin to create effective visualisations. Before we dive into the technology, you need to be aware of some key points:
- The human brain can only process a limited amount of information in a short timeframe.
- End users may not share the developer's passion for data.
- A good designer is measured by quality not quantity.
When we present data to our users through visualisations, we do so because there is a message in that data that we want the users to understand. When we create visualisations we must take the user on a journey, which finishes with them understanding that message and being empowered to act on it, if required.
One of the most important principles to consider in this is to avoid excessive data. By adding more and more content to a visualisation, you lose control of the journey you want to take the user on. Different people process data in different ways, and by having too much on screen at once your users may choose to digest that information in a different order, which could result in a different interpretation. Don't be afraid to continuously test different visualisations with your users, receive feedback and validate that your intended message is being conveyed effectively.
Where is your data coming from?
An important part of data visualisation is the data itself. A key mistake that some organisations make is that there is insufficient engagement with the data teams during the initial development, and it only later transpires that the data for the visualisation either doesn't exist or does not get updated with sufficient regularity. It sounds obvious, but you can only produce continuous data visualisations if you can deliver that data continuously. The financial industry is fortunate in that it is data rich - with a global, information based financial system producing more data than many ever thought possible. However, that data is often trapped in legacy data estates, or stuck in organisational silos and inaccessible due to regulatory requirements. Knowing what data is available before the development process begins and working with the custodians of that data will both inform the design, and ensure that that design can deliver value continuously, and at scale.