Skip to main content

Demystifying data visualisation

(Image credit: Image Credit: Flickr / janneke staaks)

We humans are predisposed to images instead of text: in fact, we process the former 60,000 times faster than the latter. It makes sense: we’ve always had an immediate, instinctual understanding of pictures and paintings, but language is something we had to invent.

Data visualisation is a logical extension of our inbuilt bias towards images and graphical representation. According to Edward Tufte, it ensures that complex ideas are ‘communicated with clarity, precision, and efficiency’. And yet, for all that it is designed to simplify and streamline ideas, it’s a concept that many find difficult to get to grips with. 

This is, perhaps, partially because of the name. When you give a simple thing a complicated moniker, you gain a certain pseudoscientific authority, but you also lose that heralded ‘clarity, precision, and efficiency’. Data visualisation is, at root, about turning information into images; if you’ve ever used a map, you’ve seen it in action. 

But in the context of business, it can be terribly confusing. It’s supposed to help companies identify and conquer their operational obstacles; it’s supposed to help them identify and exploit trends; it’s supposed to help them turn messy, nebulous information into clear-eyed strategic insights. 

The reason that it doesn’t is because it’s often used incorrectly. In truth, it’s neither a magic bullet nor a red herring: the efficacy of data visualisation tends to align closely with the end-user’s competence, confidence, and knowledge. 

Here are three ways to boost yours and better understand it. 

1. Focus on automation

In 2017, it’s easier than ever to automate the collection, interpretation, and visualisation of data. This is convenient, because the modern world requires businesses to parse a lot of information, and doing that manually is inefficient, repetitive, and mind-numbingly boring. 

It can also result in errors. Human beings are fallible, after all: the brain may outpace the computer in terms of creativity, but in terms of efficiency and accuracy, machines will always have us beat. Use them correctly, and they can help you gain greater control over your data.

And as this data gets bigger and bigger –  by 2025, collective world data is expected to eclipse 180 zettabytes, or 180 trillion gigabytes – exerting this control only becomes more important. If you can automate data visualisation, you can present information in a manner and with a level of detail that suits your specific needs and objectives. 

Data visualisation is most effective when your company has as little involvement with the process of collecting, gathering, and interpreting it as possible. Automate it wherever possible. 

2. Leverage analytical capability

Data is becoming the spine of many a sales and marketing team, and that has advantages and disadvantages. One key disadvantage is that these professionals don’t know how to use it in the way that a trained specialist might. 

In fact, getting into the nitty gritty of several nodes of information is kind of antithetical to the role of a salesperson: their job is to forge meaningful connections and relationships with customers, not to scrutinise data. They need to own the beginning, the middle, the end, and the post-sale stage of the buying process. If they’re poring through stuffy spreadsheets in Microsoft Excel instead, something’s gone wrong. 

Of course, the information held in a spreadsheet can contain multitudes: it can analyse the present to predict the future. It’s important to make sure sales and marketing people can benefit from this capability, even if they can’t derive insights from it personally. 

Data visualisation makes this possible. If you’re running an IT hardware business, for example, you’ll know that certain items are purchased cyclically, others are purchased in pairs, and others still are only bought in bulk once discounted. But the who, what, where, and when of it can be difficult to discern on your own. 

When you visualise data in the form of a chart or a graph, you have an immediate understanding of whether your computer mice are selling well on their own, or if they only sell with keyboards; if you sell more monitors in spring or winter; if your customers are responding well to your newest product or if they’re rather cooler on it. 

With this information to hand, you’re in a better position to act. Data visualisation isn’t there to make your PowerPoint presentations appear more impressive: it can have a direct impact on your operational effectiveness. 

3. Free your information 

You can only get the most out of data visualisation if you make the information that underpins it available to everyone who needs it. 

In bigger businesses, it’s often the case that data becomes siloed: sales and marketing might need information from customer service, IT might need information from finance, the C-Suite might need information from HR. These departments, however, tend to jealously guard the information that’s under their control. Whether this is due to security concerns or something else is unknown, but it can disadvantage the wider business. 

If you’re going to use a CRM, an ERP tool, or another data management system, you should make sure that they’re set up to eliminate silos and maximise organisational transparency. The more visibility you have into operational considerations, the easier it is to visualise accurate data. 

And when you can visualise this data, great things can happen. If you need more funding and have to make a case to the C-Suite for it, a chart or graph that demonstrates where this money might go and what effect it might have can be advantageous indeed. If you need a quick overview of how a new development might affect customer experience, data visualisation can provide it. 

Data visualisation is only as complicated as your company makes it. Keep it simple, and make it as easy as possible for your business to take advantage of it. 

Paul Black, CEO, sales-i
Image Credit: Flickr / janneke staaks