Making Data Addictive

In a world where there’s a dashboard for everything, why do most dashboards go to die? According to Deloitte, two-thirds of executives report discomfort in accessing or using data from their tools, while Gartner notes that adoption rates for Business Intelligence (BI) and analytics hover around a mere 30%. 

The underlying issue is that many dashboards are designed with a focus on data rather than on the end user. This data-first approach often results in overwhelming interfaces that fail to provide clarity or support decision-making — the very things dashboards are intended to do.

At Gitwit, we advocate for a user-first methodology. We’ve developed a process that facilitates deep understanding of the specific needs and contexts of those who will interact with the dashboard and then keeps those needs top of mind throughout design and development. This user-first approach leads to dashboards that not only function effectively but are also indispensable to the daily workflows of their users.

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Your Data Isn’t Your Starting Point

The conventional approach to dashboard design starts with data—what metrics are available, how they can be visualized, and how much information can be packed into the interface. While this may seem logical, it often leads to dashboards that are cluttered, difficult to navigate, and ultimately fail to serve their intended purpose. Users are left to sift through an overwhelming amount of information, unsure of which metrics are most relevant or how to act on the insights presented.

This was the case when we began working with eLynx, a leading software provider in the oil and gas industry. Despite having millions of data points collected from production wells, eLynx found that production engineers were ignoring the built-in dashboards. 

Instead, engineers were exporting raw data into custom-built tools that better suited their daily needs. The dashboards, while data-rich, were not user-friendly and failed to address the key decisions engineers needed to make.

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If you want dashboards teams actually use, focus on the users

To design dashboards that are genuinely useful, it is crucial to understand the context in which users operate. Assumptions about what users need often fall short, and traditional methods of gathering feedback—such as surveys or interviews—are insufficient. This is where ethnography becomes invaluable.

Ethnography involves observing users in their natural environments, allowing designers to understand the nuances of their workflows, challenges, and decision-making processes. By watching users interact with their tools in real-time, rather than relying on self-reported behavior, researchers can uncover insights that would otherwise go unnoticed. 

A well-known example of the power of ethnography comes from Procter & Gamble’s development of the Swiffer. Initially, P&G’s chemists focused on improving cleaning solutions, assuming that better soap would solve customers’ dissatisfaction with traditional mops. However, after observing customers at home, the company realized that the real problem lay with the mop itself, not the cleaning solution. This insight led to the development of the Swiffer, a product that revolutionized the cleaning industry.

With eLynx, we conducted extensive ethnographic research with production engineers, compiling our user learning into a target persona we named Blake. By spending time with Blake, observing his daily workflow, and asking clarifying questions, we gained a deeper understanding of the specific challenges he faced—such as how to prioritize wells, diagnose problems, and dispatch technicians. This contextual understanding was critical in designing a dashboard that aligned with Blake’s real-world needs.

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So you know your users. How do you build for them?

To translate ethnographic insights into actionable design, Gitwit employs the Dashboard Canvas, a framework that helps map out the most important aspects of a user’s role, including their mission, key decisions, and challenges. This structured approach ensures that the dashboard is tailored to the user’s specific context, rather than being a generic tool that attempts to serve too many purposes.

For instance, in the case of Blake, the production engineer persona from our eLynx work, his primary mission was to maximize uptime and production on active wells. His biggest challenges included knowing how to prioritize wells and diagnosing problems in time to prescribe effective solutions. 

By using the Dashboard Canvas, we were able to focus the design on the metrics and insights that would help Blake make these critical decisions—such as identifying which wells were down, which needed immediate attention, and where to dispatch field technicians.

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It’s not user-centered design without user feedback

One of the most common mistakes in dashboard design is moving directly from concept to development without sufficient feedback from users. At Gitwit, we emphasize the importance of prototyping—creating low-fidelity sketches or mockups that can be shared with users early in the design process. This allows for rapid iteration based on real feedback, ensuring that the final product is aligned with user needs.

Users are often more candid when reviewing sketches or prototypes than they are when presented with a polished product. By engaging users in the design process from the outset, we can refine the dashboard to ensure that it delivers the right insights in the right format.

For eLynx, we developed a prototype of the dashboard based on our ethnographic research with our target persona, Blake. We then sat down with him to review the prototype, gathering feedback on what worked and what didn’t. This iterative process allowed us to fine-tune the dashboard before any development work began, ensuring that the final product was both functional and valuable.

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eLynx: a dashboard success story

In the end, our work with eLynx transformed a dashboard from a tool that was ignored into one that is indispensable. By observing production engineers in their daily context, using the Dashboard Canvas to structure the design, and iterating based on user feedback, we were able to create a dashboard that engineers like Blake now rely on daily.

The final dashboard provided Blake with the critical information he needed each morning—well statuses, production trends, and actionable insights that helped him prioritize his work. The result was a dashboard that not only delivered value but also became an integral part of the engineers’ workflow.

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For more information on how to apply these principles to your own dashboard design, or to learn more about our work with eLynx, please contact Austin Boardman, Data Engineer, at austin@gitwit.com.

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