Data visualization is getting more cost-effective. Of the 20 products cited by Software Advice as the top data vis tools of 2016, almost three quarters were described as carrying a ‘low’ or ‘extremely low’ pricetag.
Rolling back by just over half a decade, we see that costs for data visualization tools have traditionally been much higher and that free tools, while reasonably effective in achieving very specific results, tended to be one or two trick ponies which required a whole lot of complicated orchestration if they were to be integrated into a wider, more diverse strategy.
The natural progression from such a reduction in price is that more and more businesses and individuals are able to access the technology they need. Any move in business must be costed; it must be analyzed and examined to ensure that the results to provide it are worth the capital outlay. When prices drop, the potential financial benefit of such tools is augmented.
What is Driving this Price Reduction?
Such a price reduction doesn’t happen by accident. There are factors and circumstances involved, which drive prices down. A combination of the following elements is contributing to this prevailing move towards cheaper, but no less effective, data visualization tools.
Technology is more widely available
In the technology industry, products and services follow a tried and tested curve. Initially, they must be developed and tested, which adds to the immediate costs. In addition, the technology is expensive to implement. Over time, testing ceases, and initial income helps to bring costs down. This gives the developer more ‘wiggle room’ in terms of price; i.e. they can reduce the price without harming profit.
Appetite is growing, slowly
In five years, the stock of data visualization has risen considerably. The waters have been tested and the appetite is certainly there, so much so that BARCS Business Intelligence Trend Monitor named data visualization as the most important BI trend for 2016, and predicted that this will continue to be the case throughout 2017. However, there is still caution in the market; businesses are not ready to leap two-footed into an expensive DV strategy just yet.
Businesses are still feeling the effects of 2008
The dark economic days of 2007 and 2008 are now almost a decade gone, but their aftershocks are still being felt. Businesses, having weathered that particular storm, are reluctant to leave themselves exposed once again. It will take serious price reductions to tempt these smaller sized enterprises to take a risk on DV.
It’s an Effective Entry Model
Many of the lower price data visualization tools are ‘vanilla’ editions of a more expansive product. They are effective and powerful, but they also offer a taster of the wider benefits of data visualization. When organizations begin to experience an upturn or benefit from their DV endeavors, they may be tempted to spend more money. As a business model for tool developers, this could prove effective.
What Does this Mean for Data Visualization?
This represents a major shift in data visualization. While once, DV was once reserved for cash, time and resource-rich entities, it is now in the hands of everyone. Popular revolutions like this are the driving force of BI and data insight. Innovation has a history of coming from organizations operating on tight budgets, or within claustrophobic constraints, so putting these companies in touch with the potential of DV is very exciting indeed. But what will this mean in real terms?
Democratization of the Medium
Something we can certainly expect is a democratization of the medium of data vis. In an era of fake news, misleading insight, and veiled agendas piled on top of veiled agendas, such a move is a welcome one. More data visualization means more perspectives, which in turn means a more well-rounded understanding of the data landscape we encounter every single day.
Recent developments in news, in business, and in the interpretation of data have taught us that there are always two sides, and that we should always strive to see things from another angle. A newly democratized style of data visualization brings us a little closer to achieving this.
More Examples of High Quality DV/ More Examples of Low Quality DV
Investing heavily and having time on your hands does not always translate to great results, particularly not in terms of data visualization. Putting the tools required to produce these visualizations into the hands of the masses will help to foster a positive environment of innovation and creation, so we can expect to experience lots more examples of truly jaw-dropping DV.
Of course, it would be naïve to presume that all examples of the data visualization in this diverse market will be ‘jaw-dropping’, or even any good at all. The flipside of this proliferation of amateur visualization is that there will be just as many examples of low quality DV as there will be high quality visuals. It will be up to us to sift through these visualizations in search of quality. However, as with most mediums, genuine quality has a habit of getting its voice heard.
Development of Visual Codes of Practice
In a landscape in which anyone can produce a visual of a reasonable aesthetic quality, and in which people from all backgrounds and walks of life can get their hands on the data needed to produce such visuals, new codes of practice will be required.
This is likely to be less of a regulatory code to police the data visualization field, and more of a ‘gold standard’ for data visualization. Data sources, visualization parameters, presentation styles and authorial bias will all be taken into account. Data visualizations are powerful rhetorical devices, so great care must be exercised to prevent the public being misled.
These are simply speculations. We will have to wait and see how this shift in cost affects the industry over the next 12 months. However, DV has proved itself to be a rapidly evolving field, in constant development, so it is unlikely to stay still for long.