It’s a balance that gets drilled into us early in our education: the teacher sets us an assignment, we are given a time limit in which to complete the assignment, and we understand that there is a certain level of quality which needs to be reached.

Hand the assignment in too quickly, and receive a stern telling off from dear teacher for rushing our work. Pour our heart and soul into the assignment – draft, re-draft and draft it again – and then hand in a perfect piece of work one week beyond the deadline, and we find ourselves in detention so fast it makes our heads spin.

This is a lesson in reality that we carry through our whole lives: success means striking the perfect balance between quality and timeliness.

But the world is accelerating. Conference calls which span continents, reports which are commissioned and delivered within hours, real time data access, input and interpretation; all of this is now possible.

So, it makes sense that data visualization should follow this trend. Real time visualization feels like the next step. But should we be in such a rush to earn that extra gold star by turning our assignments in so far ahead of time?

The Age of “The Hot Take”

In reality, instant access and interpretation is causing us problems. The landscape of round-the-clock news coverage and immediate insight has left news organizations scrabbling to give us the news when it breaks. Not days, hours or even minutes after it breaks, but literally *when* it breaks.

This has had tremendous ramifications within news journalism and within the communities these outlets serve. An article published by The Atlantic in 2013 found glaring data omissions in the reporting of stories relating to the 2001 anthrax panic, the Iraq War, the Enron collapse, and the Vioxx scandal.

When Anders Breivik perpetrated horrific mass murder on a Norwegian island in 2011, less scrupulous publishers were quick to shoehorn the shocking events into the narrative of Islamic fundamentalist terrorism before the truth became known. As recently as March of this year, in the wake of the terrorist attack outside the British parliament building, commentators were quick to share and discuss a photograph of an apparently unconcerned Muslim woman, which had been taken wildly out of context.

The frightening truth is, data can be misinterpreted in the heat of the moment – either willfully or accidentally. When we seek to use a tool as evocative and powerful as data visualization, can we be trusted to utilize this in a responsible and genuinely useful manner? How can we make sure that we avoid certain traps when we use real time DV?

Tech and Responsibility, in Tandem

This can only be avoided through the methodical and systematic use of personal restraint and consideration, and, of course, through the development and deployment of the right kind of technology. One cannot exist without the other.

Before it is used in a visualization, data must first be verified. If it is not verified it cannot be relied upon and if it cannot be relied upon it cannot be trusted. As we all know, data which cannot be trusted is inherently useless.

We can deploy technology in an effort to speed data through this gauntlet of verification – to bring it to a point where it can be relied upon and used sooner rather than later – but it must first pass these verification checks.

But how can data be verified quickly? It can be cross-referenced against existing datasets known to be valid, it can be run through software designed to pick out and assess anomalies, it can be looked at by a second or third pair of eyes; basically any of the methods you would usually use to assess the veracity of data can be deployed here.

This is perhaps an example of an area in which technology is lagging slightly behind endeavor and is barring us from pursuing the dream of real time data vis. If this is the case, then so be it. We cannot run before we can walk. If our haste to publish information and derive insight makes us act prematurely, then there is no advantage to be gained. We must simply cool our heels until the technology can support our need for speed.

The Applications of Responsible, Real Time Visualization

It doesn’t matter which market or industry you operate in, getting results that little bit quicker is always going to be a good thing. This is what makes real time visualization, when deployed properly and responsibly, so valuable.

In an ideal world, real time data visualization will allow media outlets to unfold and decipher narratives before our very eyes, with each new piece of information adding directly to the totality of our understanding. It will add a whole new dimension to board meetings and conference calls, as data streams are drilled into and discussed without delay.

At a lower level, real time techniques will enable teams to get the most out of collaborative work, delivering efficiency and team efficacy on an unprecedented scale.

In short, real time data visualization is an objective worth building toward.

The Real Time Compromise

So, perhaps this is not the time to give up on real time data visualization altogether. Instead, it is a time to recognize what we have, to recognize the advances we have made, and to safeguard them. To do this, we must compromise.

Whether we work for a marketing team tracking the progress of simultaneous product launches in parallel markets, or for a new agency with a tip off that gives us the jump on the competition, the principle is the same. The insight cannot be delivered and the visualization cannot be released until the facts are indisputable.

Every week, technology gets a little faster. Every day, perhaps even every hour, we get incrementally closer to a truly sustainable, viable real time data visualization environment, but we are not there yet. And until we get to that point, pace of delivery cannot be allowed to get the better of accuracy. This is truly a case of less haste, more speed.

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