Benefits of Data Visualisation


The benefits of data visualizationData visualisation has become one of the most popular technologies today. Not only does it provide an organisation with the ability to visually present and analyse its information, but more importantly, it gives the organisation a new way of seeing and interacting with its data.

Given the recent increase in focus on self-service in IT, data visualisation tools allow analysts to reach insights very quickly, all while decreasing the load on IT. Data visualisation enables data scientists and other analysts to share new insights and discoveries directly with to the business. So if an organisation is looking for ways in which to obtain actionable insights that deliver immediate business value, data visualisation tools have a strong business case.

Let’s examine what I believe are the top five benefits that data visualisation provides to organisations and in particular to their decision makers:

1. Grasp more information

A data visualisation tool enables a user to view and understand vast amounts of information – far quicker than conventional reporting and dashboards. The benefit of this is that it allows decision makers to not only see previously unknown connections between different data sets, but it also gives them an easier way in which to navigate through and interpret the data. To my mind, businesses that use visual data analytics are more likely to find the information they are looking for, quicker, than other organisations using conventional reporting platforms. It really is a case of a picture tells more than thousands of tabulated data records.

2. Determine patterns in business operations

Data visualisation enables users to see interesting and previously unknown patterns – like, for example, being able to picture the relationship between business and operations – and then related performance measures. In fact, with data visualisation, it is easier to see how your day-to-day job impacts the overall business performance, and find if any operational changes caused an increase/decrease in business performance.

Today, the amount of customer and market information that organisations are able to gather is overwhelming. However, to ensure organisations actually derive key insights from all this data, things need to be simplified. That is the beauty of data visualisation, as it allows decision makers to quickly visually identify any changes in customer behaviour or market conditions and make the necessary adjustments. You don’t have to be intimate with tables and tables of values to detect different patterns – visually they stand out like a sore thumb. Now decision makers are able to easily identify the reason for growth or detect the reason for a dip in the organisation’s performance and address it.

3. Identify trends

Furthermore, data visualisation also allows users to see historical trends in the business, like tracking the monthly sales of products, by category, by region, in fact by a myriad of related dimensions, jointly or separately. Through this, businesses can now accurately compare its present performance with the past, and forecast the future.

Timelines and grouped bar charts are useful to verify anecdotal seasonal trends, and also to identify and analyse new trends that appear in the ever-changing business landscape. Stacked bar charts are useful to compare the trends in related categories. Small multiples can be used to compare the trends in large sets of measurements. There are many more examples where visualisations are used to identify trends and pinpoint periods of particular interest.

4. Relate to data

Data visualisation enables users to interact with data – but what does that mean?

Well, take the example of a motoring company, where a sales manager wants to understand why certain cars sales are down. A spreadsheet is not necessarily going to easily give him the answers he needs. However, with data visualisation, the sales manager can view the latest sales figures and see which models are not doing well, where and why. By visually navigating through the sales data he can pinpoint the problem. He can even cross-drill into marketing or even HR data. The company is now able to respond to this very quickly and decide what actions need to be undertaken – from increasing a sales target, all the way through to kicking of a new very targeted marketing campaign, even to offering a regional discount, all depending on the findings surfaced from the data. Maybe a certain salesman just needs a wake-up call to spend more time on the sales floor instead of taking long joy rides in the demo models.

Getting visually intimate with the data allows the decision-makers to relate much closer to the information it portrays. They can now go one step further than making data-driven decisions – they can now make data-related decisions.

5. Storytelling

As I pointed out in my previous blog, a good visualisation is, in essence, the illustration of a data ‘story’ using well designed graphics that are understandable and easy to ‘digest’. Good visualisations should focus on enabling users make decisions based on accurate data. A proper visualisation facilitates good storytelling – it plays a key role in getting the message across.

However, with that said, it is important not to get lost in the noise, in the colour, or in the animation of the visual graphics. Translating data into a graphical representation is not about making it pretty – rather, it is all about getting the message across as simply and as easily as possible, while retaining the integrity of the data, and creating an inherent trust in the message. Data visualisation is way more science than art.

Concluding remarks

Looking at the above, data visualisation really can provide a new way of tracking the implementation of the business strategy, and in some cases can even assist in setting or changing that business strategy. It ensures that decision makers are able to map business performance to stories that are easier and better understood. As the need for visual representation increases, data-driven organisations must equip themselves with the resources required to utilise and make more effective use of data visualisation, in order to make and track business decisions better in the long run.

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