The Significance of Data Visualization
“Having all the information in the world at our fingertips doesn’t make it easier to communicate it makes it harder.”
― Cole Nussbaumer Knaflic, Storytelling with Data: A Data Visualization Guide for Business Professionals
Data visualization gives business leaders an upper hand in this evolving landscape. It brings better clarity, increased engagement, and unexpectedly important insights. Dealing with extensive volumes of siloed data can often lead to misinterpretations between departments. Visually grouping several data points improves the quality of analytics and insights while providing a seamless way for the business leaders to make strategic and informed decisions.
Here are some of the top reasons why data visualization is valued so much:
Identifying New Opportunities
Making Schedules for Deliverables
Processing Huge Networks
Quantifying Change and Frequency Happening Overtime
Since last year, the pandemic has disrupted the global markets significantly. With a major drop in ROI and a drastic shift in consumer behaviors, companies were forced to adopt new ways to operate their businesses. As the economy struggled to adjust, companies that adapted and learned eventually succeeded exponentially.
Making data-driven decisions has always been important, but disruption has forced businesses to make critical decisions with narrowed information. The business models have changed like the way we work has changed. Leaders at all levels have the urgency to make the right decisions faster. In today’s business environment, Organizational Speed is becoming a competitive advantage and differentiator.
It can reduce the time it takes to process information.
It enables business leaders to understand how the business data can be interpreted for decision making
Leads the target groups to focus on useful insights to find areas that need attention
Reveals plenty of unnoticed key points to compose a perfect data analysis report
Visualizes data to manage growth by making sense of the information
Navigating Through the Blind Spots of Data Visualization
While analysts with data visualization expertise have the power to unleash the data stories, creating insightful graphs isn't easy as there are some critical challenges. A lack of design in the charts and maps will mislead the audience and distract them from important information.
A lot can happen with data visualization. For example, there is a unique feature called "Data Blending" in data visualization. This feature enables to capture of data from multiple data sources together in a single view. Over time, data blending has garnered major attention amongst analytic companies as it is a fast way to extract value from several data sources. It can also help to deliver meaningful insights without additional time or resources.
However, there are a few challenges that can make visualizations problematic, such as
Lack Of Better Data Visualization Literacy
Did you know that 60 to 70% of all enterprise data is never analyzed?
A lack of proper knowledge of data visualization can do more harm than good. First, it confuses the audience, or worse, it misleads them. Additionally, a poorly structured data visualization denotes a loss of time and effort, which delays the decision-making process in deadline-driven projects. For example -
Using the wrong chart type.
Poor use of a 3D chart.
Presentation of misleading or insufficient data.
Inconsistent scale across the data represented.
A visually cluttered graph.
Organizations' lack of data literacy blocks their efforts to become data-driven and creates a significant barrier between merely gathering data and utilizing it to make informed decisions. For instance, a new report called "The Human Impact of Data Literacy" conducted by Qlik and Accenture says that only 32% can produce tangible value from data, and 27% can create meaningful insights from data. This highlights the major challenge that firms face in their journey to translate data into long-term business success.
The Oversimplification of Data
Another challenge is making the data visualization overly simple. This is harmful as making it more complex. Your clients or the decision-makers won't have sufficient data to make well-rounded decisions if critical points are being left out to make it simple.
Data visualization intends to showcase the data in a way that is easy to grasp. However, if the crucial parts are being left, the audience won't understand the essential point of the presentation. Therefore, instead of oversimplifying data, it is better to put all the critical context points together and structure them so that anyone can quickly grasp the true aspects. For example, the chart below is neat and straightforward, but what can be the takeaway here?
Source - Link
Without a clear context, your audience will take away the wrong message from the data or may not understand. Ensure to put as much relevant data as possible and showcase it in an approach that is easy to understand and access. On the other hand, you don't want to miss out on the reader's attention with oversimplification. It's all a balancing act.
A Need to Balance Beauty and Understanding
Beauty in the context of data visualization is a worthy goal to pursue. For a data visualization to qualify as beautiful, it must be aesthetically pleasing, yes, but it must also be novel, informative, and efficient. Several design components can make a significant difference in data visualization.
For example - color is known as one of the critical design components. It is often observed that too much color is being used in visualizations to make it look beautiful. To avoid this, it is crucial to understand that picking the right ones requires knowing how our intended audience perceives colors.
Consider selecting colors that go well together. Make sure to use only two or three colors throughout the visualization to keep the pictures clear and concise. Include the same iconography and typography in every image so that your reader can quickly understand it. The graphical aspects of the design must focus on serving the goal of presenting the information. Any facet that doesn't aid with the presentation is a potential road blocker as it can reduce the success of a data visualization. Proper usage of these elements is crucial for guiding the audience, conveying meaning, accentuating conclusions, and visual appeal.
The Inevitability of Visualization
Data Visualization has garnered a lot of attraction already as there are several tools available to help in knowing the complicated data sets, including charts, illustrations, and visual diagrams. We are on a short journey to take it in multiple industries, and there is no going back. This may not look like an issue; however, this may create an overreliance on visuals since companies are developing products that offer visualization and consumers are looking for products that provide visualization. These feed into overemphasis on visuals and increase the potential of human errors in development.
Data visualization isn't perfect. It isn't a magic bullet to make data more interpretable. Here are a few things to consider while depending on data visualization -
Graphs don't tell the entire story - It is essential to realize that charts don't tell the whole story always. For example, think about the fact that an interactive map may showcase the average salaries are higher in Los Angeles, California, than they are in Cleveland, Ohio. While that is based on true depiction, it can create a misleading verdict. The living expenses are much higher in Los Angeles than in Cleveland, so you don't have similar buying power even with an increased salary. This underscores the fact that graphs and charts can only take you so far.
Explanation is Still Needed - Several analysts and marketers utilize data visualization products and tools to explain their work and result. For instance, an analyst may use a chart to show the ROI of a recent strategy. However, it is not enough to influence or fully educate an audience. You would still need to conduct the interpretation and articulation of the results.
Sources Matters - Data visualization can work with what they're given. This means the reliability of the data is still paramount. For example, if wrong data is being included in a visualization, you're only going to receive a misleading chart even if the visuals are aesthetically pleasing. This emphasizes that none of the chart, diagram, or infographic should be relied upon until you know where its stats and numbers came from.
Data Visualization to the Rescue
Looking at our challenging reality, it seems that all we can do is wait for developments. But data, even in this troubling world, can assist you in navigating uncertain situations for the business. A crisis is an opportunity to recognize the hidden business avenues. So yes, this can be an opportunity to do even better. Data will help you to make the most of the possibilities.
Curious to know whether this could be the solution to your business goals? Find out more by scheduling a 1:1 here today.