It has become evident from the advancements we’ve seen in the business analytics market that the use of visualization is now becoming mainstream. In my analysis of the market last year I wrote about the pathetic state of dashboards, where the assumption in the business intelligence software industry is that placing four to six charts or tables of data in a screen and publishing to business users can create business intelligence. That assumption has yet to be proven and is completely irrational, as presenting analytics in basic charts does little to provide context and a guide for taking actions and making decisions.
Now enter the new age of visual discovery, drawn from advanced data visualization tools with interactive analytic capabilities that enable users to present large volumes of data in an appealing manner. This technology does not need to just operate against big data technology where the volume and velocity of data also need a better method of interacting with the data and is a top capability not available today in 37 percent of organizations, according to our big data benchmark research. These types of data visualization go beyond the doldrums of overused pie and bar charts, bringing heat maps, scatter plots and other forms into the standard presentation of business analytics. However, such visualizations are not designed for the average business user, since most are not trained in visual interpretation of data. Rather, they are designed for the analyst who can interpret what the visualization means and then take some set of interactive steps to investigate and discover what is behind the presentation. Sometimes called visual discovery, this method is one of four main approaches used to maximize the outcomes of the analytical discovery process, along with data, event and information discovery, as I have previously outlined. Also realize that analytical discovery is just one of many types of business analytics that organizations need to be successful. And while many in the industry are calling this segment visual analytics, the scope is the same in terms of the proper use of visualization.
Despite the skills gap in business and IT in interpretation of visualization and the ability to know what type of visualization should be used when, where and why, adoption of visual discovery software is growing, mostly in business to complement business intelligence software efforts in IT. Technology providers have seen this growth in recent years, and now most business analytics vendors have expanded upon existing products, created new ones or acquired technology to enter the rapidly growing market. This frenzy has just about every business intelligence software provider touting existing or new visualization like it is the recipe for living forever.
Let’s get a little reality check that visual discovery is an important step in the business analytics market, as it provides more intelligent representation of data than just simple bar and pie charts. However, we have to also realize that just providing sophisticated visualization to business users is not going to magically help them interpret the data and make a decision or take an action. Interpretation of visualization is as much art as it is science unless an analyst makes notations of the key points the business user should focus on. This concept of annotation is lacking in most analytics tools, which is why analysts continue to copy and paste visualization into Microsoft PowerPoint to highlight bullet points of interest for the business users and then publish to business users that in many cases is converted to Adobe Acrobat format. I pointed this out in a previous piece titled “Why Business Intelligence is Failing Business,” noting that technology vendors should place more intelligence in their analytics software to generate observations and places to focus on using expert systems, personalization and maybe even methods of artificial intelligence.
Presenting hundreds of points in a scatter plot or 25 shades of green and red in a heat map is not an intuitive approach for business users trying to determine where they should start and where they should stop. In fact, sometimes performing visual discovery on data points that look obvious for interacting might not be the best place to focus as the data could be blinding areas of opportunity or concern that have been aggregated or masked out by the data and visualization. Visualization of what should be interacted with and discovered needs to be more intelligently presented. For example, the visual discovery tool might provide a link to a document, report or even the actual events that impacted the metric being represented. Most important, electronic and collaborative discussion forums where analysts and business users can discuss and address issues and opportunities are needed to guide the business in the discovery-to-actions process. The current approach of interacting via telephone or email is insufficient, as the complete context of issues is often lost using these methods.
Until visual discovery can graduate to being more than visuals or tables of data and relate to how business actually works and meet the real competencies of the larger scope of users, we will see over-adoption of visual discovery. Until organizations realize that this type of tool is good for only a specific type of individual, one with a high level of analytic and data competency, we will see growing frustration among users, as has occurred with dashboards. What we need is to have more visual presentation methods will expand to formats that are more digestible by business users, including geographic maps, paths of activity traffic, workflow of business processes and even presenting the key facts inside of a business centric infographic, all of which today are available and found in separate products. As I pointed out in my analysis of information optimization, the point of visualization is to provide information that is optimized for effective utilization across any role and competency in the organization. I do believe that visual discovery is critical to larger technology innovation within the business analytics market: According to our business technology innovation benchmark research, it is the top-ranked technology innovation priority in 39% of organizations. I believe we will continue to see advancements in the application of visualization and even where it can be more effectively reviewed on tablets and integrated with other technologies that are used frequently.
For business users and analysts, it is essential to assess visual discovery tools based not just on the role of the users, but also their competency in analytics to ensure a full return on investment. Take heed of the best practices in discovery analytics that my colleague Tony Consentino discussed recently and do advanced visualization in your organization if it can be used properly. If you are passionate about visualization and presenting the real meaning of information, then a read through Edward Tufte books might help provide a larger perspective, as his work looks at the history and importance of presenting information properly through visualization is well recognized. Rationalizing the potential tyranny of visual anarchy is critical to the success of your business analytics and big data investments.
This blog was originally published on Ventana Research. Published with permission.