OPINION: Does your picture tell the right story?
|Good business decisions are more likely to be made when information is presented in a meaningful and relevant way and in the right context to be understood. Humans are best equipped to understand by seeing pictures. Being presented with columns and rows of data makes it difficult to see trends and patterns and often requires the uninformed to seek assistance. To make matters more difficult, new data sources from social media and scientific fields are not as well suited to being presented in traditional spreadsheets and graphs. So, it follows that being able to see the underlying patterns within these new data sources requires new ways to display them.
Informing stakeholders with easily understood visuals is being driven by two trends. First, for analysis of big data and second, the commoditisation of tools to create and publish high quality and relevant data visualisations. Knowing how and when to apply data visualisation to be a more effective communicator and influencer of business decision makers is what all managers will need to embrace or be able to access from their corporate resources.
Connecting the dots
The value proposition of data visualisation lies in being able to convey information in a way that shows connections and relationships among all the available data in a way that is not possible with traditional methods. Data visualisations make it easy to rapidly understand context, relevance, relationships, patterns and stories within a complex data set. Interactivity with underlying data is a feature of modern visualisation technologies such that visuals are no longer static but dynamic. Many business intelligence tools have long enabled drill-down reports yet they typically only contain common visuals and constrain users to predetermined paths. These limitations and constraints are effectively removed with new visualisation tools and replaced by immediacy.
Successful visualisation is not merely about pictures and effectively conveying complex information but rather, creatively provoking human interaction and actionable insight. For information to provide valuable insights, it must be interpretable, relevant and original in its capacity to shed new light on its subject matter. If any of these elements are not present, then visualisation is unlikely to make the information valuable.
Creating meaningful conversations
The decision for those preparing visualisations is, ‘What kind of conversation and interaction should the visualisation generate?’. Visualisation usually works best when generating situational awareness and contexts that otherwise wouldn’t be identified or even thought to exist. Like good maps, they should provide a sense of where you are and provide guidance and insight as to where you may need to go next. Visualisations, particularly those involving simulations, can force organisations to rethink how they could be used as platforms for creating common understanding across the enterprise and encouraging increased collaboration.
Visualisation as a human interaction interface leading to new opportunities for value creation has to be better than regarding it as a medium that substitutes pictures for words. Ultimately, data visualisation is about communicating ideas that will drive action. Understanding the criteria for information to provide valuable insights and the rationale underlying data visualisations permits communicating ideas with efficiency and impact.
Why use data visualisation?
There must be valid reasons for constructing data visualisations and these broadly fall into three categories:
Confirmation – validating assumptions about how a system or process operates and observing whether the underlying system has deviated or varied from a defined operating model, and assessing the risk of executing planned actions.
Education – there are two forms here; reporting and insight generation. The former relates to measuring the underlying system of interest and the values derived from the measures of system performance over time, compared with other systems or models. The latter relates to developing intuition on and new insights into the behaviour of known systems under experimental conditions and in a compressed time frame. Gamification is a good example of this form of visualisation.
Exploration – where there are large sets of data and we are goaled to provide optimal human-machine interactions to it to identify and draw out relationships, processes and models, visualisation allows better prediction and management of the system being analysed.
If visualisation has a well-defined purpose, necessary and sufficient data and metadata and is able to generate interpretable, relevant and original insights, how can an executive decision maker have confidence that such insights are actionable and can potentially generate value for the business? For visualisation to provide genuine value at a high level of confidence and reliability, three areas of risk need to be understood and managed:
Data quality – completeness and reliability of underlying data and the analytical data processes used to collect and prepare it for use.
Context – for large amounts of data to be approachable and permit pattern detection, the potential relationships of the data elements must be accessible. Context is the source of insight and leaving out contextual information or metadata impedes and restricts our understanding of data elements.
Biases – minimising or eliminating the undue influence of the semantics of visualisation and syntax of its elements such as colour, positioning and effects which challenge data interpretation.
If not properly managed, each of these risks can adversely impact the value derived from data visualisation. Visualisation should bring data to life by providing the flexibility to analyse large volumes of data and apply analytical techniques and methods within a selfservice business intelligence environment. Being able to express complex ideas with clarity, precision and efficiency and tell a compelling story through the graphical depiction of statistical information is what data visualisation should be doing. For good decision making, there are fewer forms of compelling communication than a persuasive picture and narrative. Is your business telling a good story or an insightful and compelling one?
- Paul Franks, SAS, Good business decisions, new data sources, big data, data visualisation
- AB+F Online
- Article Posted:
- August 01, 2013
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