How Data Visualisation enables smarter, faster decision-making

Every organisation recognises the value of data. The digital world in which all businesses now operate has seen a proliferation of information with which business leaders can make faster and better-informed decisions. But translating raw information into clear, actionable insights remains a challenge. Collecting, analysing, and interpreting data can be time-consuming and prone to human error, as can consolidating information relevant to a particular stakeholder from the wide variety of data sources businesses can now use.  

Part of the solution to these problems is high-quality, automated data visualisation dashboards, and with recent advances in analytics software, creating sophisticated dashboards isn’t the technical challenge it once was. 

Here are a few of the reasons organisations are investing so heavily in data visualisation: 

Access to up-to-date information 

Automated analytics dashboards allow you to make decisions based on real-time (or near real-time) data. Rather than responding post-hoc to some insight gleaned from a monthly or quarterly report, they allow you to identify and react to problems and opportunities as they arise. The speed at which information flows through an organisation is critical to its success. Building a suite of live dashboards for stakeholders across the organisation accelerates the flow of information by creating a highly informed workforce with up-to-the-minute data and insights specifically relevant to them. This in turn facilitates more informed conversations and more effective decisions. 

Easy interpretation 

As data proliferates within an organisation, extracting what’s relevant and valuable becomes a complex technical challenge. Businesses have suddenly found themselves working with large data sets from a variety of data sources that until very recently didn’t exist. The audience for this data is often time-poor decision makers who need to be able to quickly digest and act on the information they’re presented with. Effective data visualisation is about reducing complexity and clearly demonstrating whatever’s pertinent to the stakeholder in question – after all, “a picture can say a thousand other words”. The interactive features of data visualisation tools also allow you to explore large data sets (without any specialist analytics expertise) and spot trends or identify relationships between variables that would otherwise be hidden in the data. 

Minimising manual effort 

Building automated dashboards is getting easier and more intuitive, and consequently the business case for automating manual reporting tasks is becoming increasingly compelling. Weekly or monthly reports often need to consolidate data from multiple source systems, increasing both manual effort and the likelihood of introducing human error. Building an automated dashboard minimises this risk with the added bonus of eliminating a task that nobody particularly enjoys doing. 

Facilitating collaboration 

With data visualisation tools becoming easier to use, non-technical stakeholders can quite easily develop the requisite skill set to edit or build their own dashboards. Many organisations are now aspiring to a self-service reporting model, with business stakeholders taking a more active role in creating visualisations, exploring datasets, and interpreting data. This model reduces the number of requests made of the analytics team and prevents them from becoming a bottleneck.  

One of the major obstacles to building a data-driven culture is a disconnect between the analytics team and their business stakeholders. Insufficient understanding of how the business operates on the part of the data team or a lack familiarity with source systems and data sets among business stakeholders leads to inaccurate or irrelevant analysis and ultimately to inefficient business operation. Integrating a well constructed data visualisation program across your business such that employees can see what they need to see is an effective way of overcoming this disconnect and embedding a true data-driven mindset. 

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