Data & Analytics
5 minute read
Jun 4, 2020
Written by: Ben Abbott
Think about how much the tried-and-true adage “a picture is worth a thousand words” says.
When reviewing what may feel like an endless stream of tables containing megabytes of data, it’s not easy to pick out trends, outliers or even patterns. And as the volume of data increases, coming at us at breakneck speed, it’s becoming increasingly difficult to parse out meaningful insights and markers that matter.
That’s why the field of data visualization has exploded in recent years. Data visualization is about using graphics and images to communicate what data is telling you – what you can’t easily glean from looking at a 250-word executive summary or even a well-curated data set.
Visual literacy – the science of how we read and interpret images – helps us see clear relationships between different things. As a human’s most complex sense, vision influences how we process and retain information. We simply take away more from something we see, so the better we package data, the better our teams and decision-makers can envision the many dimensions of what’s in front of us.
When applied in the business world, these graphic data representations can help anyone from your customer service team to the C-suite quickly grasp key proof points and inform decision-making. At Spinnaker, we use data visualization to present the right data in a way that helps our clients solve specific problems.
Not too long ago, most of us relied on Microsoft Excel and its many spreadsheet capabilities as the backbone for data analysis. And while Excel can export data in tables and basic visual representations, it immediately pales next to tools designed specifically for data visualization. Their sophistication builds exponentially on basic pie charts (which date from 1801), scatter plots and bar graphs.
Data visualization adds in flow charts, heat maps and animation – just to get started – along with custom color palettes and imagery that can transform basic information into corporate works of art.
The rapid evolution of Big Data is allowing us to understand, at unprecedented depths, how various pieces across the enterprise fit together – both in tandem and in competition with organizational goals. As information strategies take on an increasingly important role in shaping today’s business decisions, companies are looking for better ways to engage with the right data. Building the best analytical platform to collect those insights requires a lot of heavy lifting, but you also need to think about how to best present them.
The best data visualizations begin with defining the precise question you want your analysts to answer and the key messages you want your audience to take away from the data. Effective use of this reporting approach relies on several core fundamentals.
To start, you need analysts with the skill set to think outside the box and creatively bring data to life with graphics that make sense for your business. In other words, don’t push this assignment to a graphic design function – it should remain in the hands of someone who can read and interpret the data to ensure that the visuals accurately communicate the underlying analysis. Otherwise, you’ll just have a bunch of pretty pictures.
The second essential is partnering with your CIO to identify the right data visualization platform for your organization. Tableau is on the more sophisticated side of the spectrum because of its variety of templates and customizations. If your reporting needs are simpler, or if you’re in the early, experimental stages of leveraging this tactic, you may want to consider testing out a free resource, such as Google Data Studio. Both Tableau and Google Data Studio offer galleries where you can get a quick sense for their visualization capabilities.
When taking advantage of the visual aspect of these tools, be sure to look into how you can access and manipulate your data. Most tools can connect to a variety of data sources, from uploaded CSV files to live database connections. Some connections may have built-in support, while others may require customization. Make sure you know what you’ll be getting into when it comes time to implement a tool, and that you have the necessary resources to dedicate to it.
Finally, don’t overlook where you’ll continue to conduct your core analytical work. Like many others, I still find myself frequently conducting exploratory analysis in Excel before I start thinking about how to create and publish compelling visualizations. Be sure any tool you select will work and play nicely with the rest of your organization’s analytics workflow.
One last caveat: Too much information is information overload. Just because you can present thousands of pieces of data in visual formats doesn’t mean you should. Less is more. An effective visualization can draw the viewer’s attention to very specific insights, so be sure to take advantage of that.
Once you have the right tools in place, be rigorous about determining where you can get the best returns for your analytics investment. Different companies, naturally, will find different opportunities, but every option should tie back to giving you information that aligns to your overall strategy and goals.
Let’s look at a case study of how one Fortune 200 company put this into practice. One of the business’ call centers needed a real-time tool for understanding key customer service agent metrics to drive specific agent behaviors. We guided them in installing a tailored scoreboard that posts – with up-to-the-minute and easy-to-read graphics – key performance metrics. If managers glance up and see a drop in, say, average handle time, they can nimbly push targeted behaviors to drive that metric back to expected levels.
The call center isn’t forcing managers to tap into data sources and calculate that metric on the spot; presenting it visually means they can grasp the meaning and go right into the action phase.
The up-front strategy is the lynchpin of putting data visualization to its best use in your organization. Ask your team three key questions, and be sure to involve your target audience so you get the right answers.
Again, because this is perhaps the biggest takeaway, think through the best applications for data visualization and make sure you’re presenting meaningful data that drives smart decision-making. You’re placing a premium on the information that gets this specialized treatment.
Even so, the greatest struggle with any data analysis is often with getting the right people to look at it. Data visualization helps you solve that lingering challenge by giving your audience a clear, actionable picture of what critical data is telling your company.
When you’re ready to see how to take your analytics to the next level, check out our sister company, Flying Phase, which delivers advanced automation and machine learning. Don’t hesitate to reach out with questions about our approach or additional suggestions.
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