There is an adage that goes – a picture speaks a thousand words. In the business context, it means that if an organization wants to put across its ideas, inferences, or any other information, it must consider representing it visually. As more organizations become data-driven and given the enormous amount of data they collect every day, data visualization will help decision-makers understand and interpret the data better. There are several ways to represent data. One of them is interactive data visualization. It means that the data does not necessarily have to be presented in a static or uninteresting way. It can be intuitive, interactive, and engaging. Most importantly, with static data visualization, organizations cannot change the story as more data points get added. With interactive data visualization, organizations can change the context of the story as more data gets included.
But why are they so significant, and how can organizations implement them in their business?
Let’s explore to answer these questions.
Why Organizations Need Interactive Data Visualization?
Data visualization simplifies complex data through storytelling
Humans love compelling stories – be it the story about the outcome of a recently launched campaign or trends in a particular industry. The endless columns of numbers on spreadsheets or the large chunk of text on the PowerPoint slide do not appeal to the audience anymore. They want to know what the data says in a way they understand. To tell that compelling story, organizations need to simplify the data to make it understandable and digestible. Big Data is complex in nature. Often it is so unintelligible that it cannot be presented in a raw form. It has to be presented in a way that the audience gets the message instantly by just looking at the data.
Interactive data visualization can help in simplifying the complex data and creating an engaging story around it. The advantage of interactive data visualization is that even as data becomes more complicated, it can be presented in a way that the audience can zoom in and out and filter them to view the relevant information. They can also get multiple viewpoints of the data by changing parameters.
Data visualization makes it easy to spot trends and predict forecasts
Organizations realize that the only way to thrive in a competitive industry is to spot trends and abnormalities early on, predict forecasts, and align the business decisions with them to stay a step ahead of the competition. But how does one find the hidden or untapped trends that might be a treasure trove for the organization? The good news is the organization doesn’t have to go out of the way to spot the trends. The data they collect every day can serve as a good starting point to identify trends and work on actionable strategies.
With the help of interactive data visualization, organizations can present the trends simply and effectively. It makes it easy for the decision-makers to understand the trends, build a predictive model and develop strategies to meet the changing trends.
Data visualization accelerates decision-making
Studies show that it takes a maximum of 90 seconds for an average person to decide based on what they see. In the business context, it takes months for organizations to arrive at a decision. But given how quickly the external and internal situations change, organizations have to accelerate their decision-making process. And these decisions cannot be made on instincts. They have to be based on the data collected and analyzed. To balance between making data-driven decisions and the timeliness of the decisions, organizations need to harness the power of interactive data visualization.
Data visualization can show a cause-and-effect relationship, give real-time information in a visual format, and identify how daily operations can be changed to achieve goals. The compelling visuals help decision-makers process information faster. A Stanford University research on data visualization revealed that 64% of participants made evidence-based decisions due to the visual representation of information.
Data visualization encourages collaboration
Considering that data visualization simplifies complex information, everyone in the organization can understand the data easily. This democratizes the meetings and enables every participant to brainstorm and discuss ideas. Data visualization also promotes collaboration between cross-departments, decision-makers, and employees. Decision-makers can effectively communicate the data and decisions to their employees, building trust and boosting the organization’s productivity and efficiency.
Data visualization communicates findings effectively
The primary responsibility of a data scientist is to communicate findings and observations to the decision-makers to make informed decisions. Given how some findings are complex, the onus lies on the data scientists to convey their findings in a digestible format. With interactive data visualization, data scientists can present their large volume of inferences and records in easy-to-interpret graphs, dashboards, maps, etc. They will be able to show correlations in a consumable form.
How to Begin Using Interactive Data Visualization?
To become data-driven, organizations have to start communicating the data to the stakeholders and employees in an understandable manner. Here are some ways to start using interactive data visualization.
- Set a clear purpose of what the data would reveal. Will it reveal the trends, monitor progress, measure effectiveness, etc. This will help the data team to focus on projecting the data that delivers the right value.
- Know the target audience. This will help in customizing the data visualization in a way they understand better.
- Ensure that the data is clean to maintain its accuracy.
- There are various ways to represent the data. Choose the format that can best communicate the information to the audience.
- Ensure that the data is presented in a manner that the audience can choose how and what part of the data they want to skip or analyze further.
- Ensure the data is coherent enough for users to process the information easily.
These best practices can serve as guidelines for organizations to build effective data visualization models.
Let’s connect to discuss how you can transform your organizational data into actionable insights.