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LATEST THINKING


Accelerating understanding through
data visualization

Learn the value of why data must be presented in a visually and meaningful way.

Overview

As companies go digital and leverage exponentially larger big data sources, they must apply a new logic to how they manage their data supply chain—from ingestion to insights. Yesterday’s model of data warehousing and periodic reporting is a slow, linear approach; the future model is nimble and multi-faceted, supplying the right data to companies and executives in real time.

But having instant access to the necessary data is not enough. The data must also be presented in a visually appealing, meaningful way that people can quickly understand. This emerging field is called data visualization. With it, companies can turn raw data into meaning and ultimately into understanding to make better, faster decisions about strategy, operations, supply chains, logistics and more.

Background

There is a right way and wrong way to visualize data. The right way is through storytelling, which is an art form that can amplify the power of the data. Bestselling authors do storytelling extremely well when they write riveting plotlines. Online journalists rely on storytelling to add illustrative dimension and clarity to their posts. And enterprises build their brand through storytelling to improve public perception and increase loyalty.

Telling a story through data takes preplanning, clear objectives and the right interactive visual elements. The result can be a competitive differentiator: the ability to share information that quickly guides people toward a conclusion, persuades them to take a different action or invites them to ask entirely new questions.

Analysis

Why does storytelling through data visualization work? The human brain has a unique ability to perform visual pattern recognition. This is an important capability to leverage in addressing data because it accelerates understanding of complex situations, which is especially critical as companies strive to make decisions and act at digital speed in a constantly changing landscape.

Equally important, the human brain has evolved to remember and understand stories more easily than other forms of information. In recent years, researchers have shown that when people talk about facts, only two areas of the brain are activated—language processing and comprehension. When people hear a story, however, multiple areas of the brain are activated, helping an audience to better digest, understand and remember the relevance of the data. That is why sharing work and data visualizations within the framework of a story make it more comprehensible and memorable.

Recommendations

Accenture’s visual literacy methodology comprises five essential steps:

  • Define your audience—By understanding the audience’s background, goals and needs, companies can tailor the language, explanations and presentation style accordingly.

  • Frame insights—Companies should select the snapshots that directly align with the audience’s needs and wants, and provide targeted messages that support the story.

  • Consider context—Focus on how and where the data will be shared, such as mobile devices, Web-based presentations or live audience. Also determine whether the data visualization will be used collaboratively or by a single user.

  • Select storytelling elements—The data may lend itself more toward exploratory or explanatory information. Exploratory data visualizations are often part of the initial analysis process to find insight through the data, whereas explanatory data visualizations typically present insights, patterns or trends unveiled during the data analysis phase.

  • Organize and practice—To bring everything together into an organized story, companies must decide which type of storyline structure best fits the defined goals, based on the audience, insights, context and elements.