Skip to main content

Adding meaning to numbers with data stories

Digitization entails that financial institutions are becoming more and more data-driven organizations. This data, however, needs to be presented in an understandable manner. For this purpose dashboards are used as a medium to review performance across the organization. Often, this enables you to structure and view information from every part of the business, using charts and metrics to make that data more accessible.

Yet, for the managers, team leads, and executives who aren’t experts in that data, dashboards can present an overwhelming array of information. Without the data literacy behind what something is or why it is, non-experts struggle to make sense of or to properly utilise that information, and need to rely on a business or data analyst to provide meaningful insight.

At ACT, the regtech branch of ACE + Company, we’re working to implement data stories to bridge this gap, using storytelling to add life and meaning to the data behind dashboards.

What are data stories?

Data stories are narratives built around data, usually in textual format. This changes the data from being a simple visualisation of data, to sharing a story of what that data is about, highlighting key facets, and engaging the viewer with what the information actually means.

Using Artificial Intelligence (AI) you are able to filter through data, recognize patterns and put together a story around that pattern. Using this technique you can automate the process of transferring raw data into something more meaningful and engaging. Take Uber’s app. Instead of just sharing how many miles you’ve travelled, it translates that information to how many times you’ve travelled around the world. Google Maps uses a similar approach, collating data and sharing a story of where the app user walked, what they saw, and which places they visited over the month. That’s a lot more engaging to most people than receiving a long list of coordinates of where you have been last month.

Financial organisations can take the same approach.

Of course, you still need raw data. The difference is in the approach. One analyst will look at raw data and draw a slightly different conclusion than another – sharing those insights adds value yes, but it is not built for scale. Your team of analysts can only be so big. Scaling insight across the organisation means you’ll have to break the data down into a digestible format, preferably in an automated manner, to the point where a non-expert can review the information and form a meaningful conclusion. And, data stories are a promising option to realise this.

A budding technology

Eventually, we’ll be able to scan all of our data automatically, create graphs, and add valuable stories around them. This approach is much more scalable than a team of analysts and enables people to process large amounts of data in one go.

Yet, data stories are still in their infancy. At ACT, our first step towards this technology is to create a standard narrative ourselves. Then, we use machine learning to fill in the gaps to create a coherent story. The process still requires human input, but it is a first step to eventually allow our clients to more easily access useful information for their decision-making. Most importantly, when we started, it was because some of our clients were struggling with the insight gained from dashboards – people didn’t always understand what was presented. Building narratives around that data, even simple ones like using the number of people or hours spent on a project to show the forecasted costs of the project, made those dashboards significantly more legible.

Over time, this process of creating stories will be fully automated, but for now, it still requires a human touch.

Why move towards data stories?

At ACT, we’re very much in favour of making data more human, more accessible, more real. And, data stories can do just that. They enable people to better interpret data, reduce basic clarification questions, and make underlying patterns visible to the user. They also free up expert analysts, who can then use their skill sets to address priority items or perform deep dives on topics of interest – providing more value for the organisation.

Data stories will only continue to become more significant. As self-service and on-demand analytics have become the norm, those narratives play a key role in ensuring that management and business can use data to extract the insight they need, in turn driving their decision-making. Brands like Gartner indicate Data stories will be the main form of data consumption in just a few years – even though the technology is still in its infancy. At ACT, we expect it to remain a human-led process for the time-being, but adding narratives to data, and sharing meaningful and engaging stories, will help your audience in their decision-making and will help you to become a data-driven organisation.

If you’d like to plan for the future, where self-service analytics is not the most dominant form of data consumption, and evaluate the use of automated storytelling in your current portfolio, feel free to start a discussion to explore your options with ACE and ACT.