Are Data Dashboards Delivering Data Stories Effectively?

In order to deliver insight understandably, analysts use data dashboards to convey data stories

The influence of data has changed our lives in many ways. Datasets are helping us to improve the processes, initiative and innovations of organizations across sectors through the power of insight. However, in order to deliver insight understandably, analysts use data dashboards to convey data stories. Unfortunately, it doesn't go well always. Sometimes, the employees and non-technical people working for the organization get stuck in obtaining the content of the dashboard.

Data insights are very important for business progress. But everyone involved in the improvement process getting the most out of data is also critical. Even though when analysts come up with interesting insights and explain the dashboard thoroughly, employees often have doubts after the presentation is over. This also stagnates the implementation process. Remarkably, most of the analysts suffer to deliver the content in the consumption layer where gaining the necessary understanding of the data to make decisions and action takes place. Even though businesses are rapidly adopting analytic and business intelligence tools to make insights out of enterprise data, they are only leveraging it at the most hectic spots.

What is a data dashboard?

A dashboard is a tool used for information management and business intelligence. Meanwhile, a data dashboard is an information management tool that visually tracks, analyzes and displays key performance indicators (KPI), metrics and key data pointers to monitor the health of a business, department and specific process. In laymen's term, data dashboards are a visual mechanism for organizing and presenting quantitative data insights in such a way that it tells a clear, concrete story, ideally bringing your message to life. Using data visualization, dashboards uniquely communicate metrics visually to help users understand complex relationships in their data. In a data dashboard, it is easier to draw parallels between different but related metrics, identify trends, and head off potential challenges hidden in an organization's data.

The idea of a digital dashboard came up in the 1970s after a study on a decision support system, an information system that supports business or organizational decision-making activities. During the 1990s when the information age was at the hype, dashboards quickly became a reality with the existence of data warehousing and online analytics processing (OLAP). Furthermore, the introduction to KPIs in business enabled dashboards to be utilized more in the current day market.

Functionalities of data dashboards

The first thing that we need to understand about a data dashboard is that neither all dashboards serve the same purpose, nor do they play the same role. Remarkably, there are many types of dashboards namely business dashboard, executive dashboard, KPI dashboard, project dashboard, etc.

Business questions trigger data dashboards: One of the major roles that data dashboards play is to answer critical business questions. Unlike advanced business intelligence tools, data dashboards are designed for quick analysis and informational awareness. Building a question and answer format to extract the maximum benefit is seen as a common approach for data dashboards.

Presenting operational and analytical data: Based on the enterprise data, an analytical dashboard can help decision-makers, executives and senior leaders to establish targets, set goals and make them understand what and why something happened. With the same information, they can even implement appropriate changes.

 Providing interactive data visualization: The best way to convey data is through understandable data visualization techniques like tables, line charts, bar charts and gauges, which help analysts to track their business against benchmarks and goals.

Conveying data stories through dashboard is becoming difficult

Business organizations are urging data analysts to turn enterprise data into actionable insights. However, the process is not as easy as it sounds. By many of the endless dashboards, visualization falls flat with their intended audience. Sometimes, the reason behind this is cited as the overwhelming recipients with too much data, other times, it is about presenting the wrong data or not fully understanding how to create an effective narrative that will resonate with recipients. An effective data story should have a beginning, middle and an end. Furthermore, there are tactic and empathy that should also be conveyed in the storytelling. Even though when analysts try their best to deliver it with approximate content and crisp lines, non-technical employees are often left in dark. To far worsen the trouble, analysts sometimes find that the data doesn't have any correlation to the message, or may leave gaps that don't tell the full story. So instead of starting from the actual data, consider working backwards from questions that convey the apt answers. Identifying the specific message will help to dial in on data that is important.