The Beauty of Visualisation: The Rise of Visual Organisations

Exploring and Explaining Data

We are living in an era of data explosion where new data sources and types are being released every day. However, unless we recognise the true power of hidden elements within the data, its potential remains unfulfilled. There are multiple ways to understand and analyse voluminous data across platforms, but the concept of visualisation has taken the lead, an idea supported by fast growing research.

Vision is considered to be the primary sensory source for assimilating, remembering and comparing information. Gestalt psychology and its principles, help us to comprehend how we cognitively perceive shapes or forms as grouped. When used systematically, these shapes will allow us to see a bigger picture more easily. Pre-attentive attributes (unconscious collectionS of information from the environment) are the patterns we recognise automatically, before we are even consciously aware of them. They work to our advantage by presenting patterns we can interpret immediately without pressure being placed on our short-term memory. These attributes are particularly useful for representing quantitative values.

The world of visual information may appear, at first, disconcerting. However, learning more information about visualisation and data interpretation can equip us with the ability to understand our world more comprehensively. It not only helps us to solve problems faster, whilst allowing us to learn something new, but these activities in the data world often have monetary value.

The Idea of a Visual Organisation

Decision-makers can exert a lot of their energy looking at a dashboard that can sometimes only have an ill-defined perspective of their context, the markets and economy they operate in and their target demographic. The decision-maker needs to understand the whole business narrative quickly and take necessary actions or decisions before their competitors.

Data visualisations may include inaccurate, duplicate or incomplete data. However, that does not prevent anybody from proceeding in interpretation. In fact, data visualisation can help users identify anomaly information and purify data faster than manual hunting. By establishing a data friendly architecture and adopting a data-oriented mind-set, a smaller organisation stands an increased chance of attaining higher levels of data visualisation than their bigger competitors that possess greater technological and cultural excess.

Some of the key reasons for a business to aspire to become a more visual organisation:

1.     It can help to understand what has happened and why (past).

2.     It can help to understand what is currently happening and why (present).

3.     It can help to understand what is about to happen and why (future).

4.     It can help to discover new insights from existing datasets and sources.

5.     It can help to make better business decisions.

6.     It can help to diagnose and address impending issues.

7.     It can help to ask pertinent questions of business data, maximising its value.

Increasing your application of data visualisation will assist in gaining insights from data and its visual interfaces. The main function of data visualisation is its ability to visualise data and communicate information clearly and effectively. Visual organisations recognise, in the current environment, that you can visualise almost anything.

Stages of Data Visualisation

1.     Collection and storage of data.

2.     Data processing.

3.     Mapping the data to a visual representation.

4.     Cognitive understanding and association with output.

Best Practices

1.     Think of your data analysis as a narrative.

2.     Authentic source of data.

3.     Think of yourself as a film editor when it comes to visuals.

4.     Make it easy for the audience to understand. 

5.     Incite and invite direct discussions.

Opportunities to become Visually Compliant

A heavy investment is no longer required to become proficient in this system. Many powerful data visualisation / BI / data mining tools are available on the market: examples of this are DOMO, Tableau, SAS Visual Analytics, MicroStrategy, QlkView etc. Any of these can effectively slice and dice data, extracting new business insights, developing storyboards, creating unique dashboards, and generating relevant graphs or diagrams alongside popping statistical charts.

Furthermore, every new release of Microsoft Office suite has advanced features added onto Microsoft Excel (the latest being the 2016 version), which is now built upon a robust analytical platform to efficiently generate a number of graphs, charts, diagrams and statistical analysis. Simultaneously, Microsoft products also allow the integration of add-in applications from third parties, which tightly integrate with Microsoft Office to bring to the surface a power packed and authentic business analytics and visualisation capability. Traditional business intelligence (BI) and reporting tools that handle relatively small amounts of structured data can expose many unexplained aspects of business environment.

Visualisation tools help us generate popular visual charts like line graphs, scatter plots, area charts, histograms, horizontal bars, stacked bars, pie charts. They also create some of the most advanced and aesthetic visual features with unique dimensions and colours. Visualisations such as tree maps, heat maps, symbol maps, filled maps, circle views, box and whisker plot (widely referred to as box plot), Gantt charts, bullets graphs, packed bubbles can be created, offering innovative and aesthetic ways to visualise data.

Visualisation applies vision research to the practical problems of data analysis in much the same way as engineering applies physics to the practical problems of constructing buildings. A visualisation can be viewed from two important viewpoints: from the perspective of the developer, and from the outlook of the user. Despite the data deluge and techniques (or, at times, as a result of this), data can often provoke confusion, however, we must embrace this process as a journey.

Maninder Singh is a leader in Cloud Business Intelligence and Analytics with more than a decade of experience. He is the author of the Flagship Model: The BI Pentagon of Success. Many thanks to Hannah Jones and Harpreet Singh for their contributions to this article.

Want to know more about the BI Pentagon of Success? Connect with our LinkedIn to ensure you have access to our forthcoming series of articles that will explore the individual sub dimensions in more depth.