Data visualization refers to presenting data in a graphical or pictorial form, such as a pie chart. This allows audiences to recognize patterns more quickly. Interactive visualizations allow decision-makers to drill down through the layers of detail. This changes perspectives so that users can review the facts behind the analysis.
Here are seven ways that data visualization affects decision-making and changes organizations.
1. Faster Action
The human brain tends to process visual information far more easily than written information. Use of a chart or graph to summarize complex data ensures faster comprehension of relationships than cluttered reports or spreadsheets.
This provides a very clear form of communication allowing business leaders to interpret and act upon their information more rapidly. Big data visualization tools can provide real-time information that's easier for stakeholders to evaluate across the enterprise. Faster responses to market changes and quick identification of new opportunities is a competitive advantage in any industry.
2. Communicate Findings in Constructive Ways
Many business reports submitted to senior management are formalized documents that are often inflated with static tables and a variety of chart types. They become so elaborate that they fail to make information vibrant and memorable for those whose opinions matter most.
Reports coming from big data visualization tools, however, make it possible to encapsulate complex information on operational and market conditions in a brief series or even single graphic. Decision makers can easily interpret wide and varying data sources through interactive elements and new visualizations such as heat maps and fever charts. Rich but meaningful graphics help engage and inform busy executives and business partners on problems and pending initiatives.
3. Understand Connections Between Operations and Results
One benefit of big data visualization is that it allows users to track connections between operations and overall business performance. Finding a correlation between business functions and market performance is essential in a competitive environment.
For instance, the executive sales director of a national software company may see immediately in a bar chart that sales of their flagship product are down eight percent in the Southwest region. The director can then drill down to see where the variances are occurring and start formulating a plan. In this way, data visualization allows executives to spot problems immediately and act on them.
4. Embrace Emerging Trends
The amount of data now being collected on consumer behavior can expose many new opportunities for adaptable companies. However, that requires that they are consistently collecting and analyzing this information. By using big data visualization for monitoring key indicators, business leaders can more easily spot market shifts and trends in varied and large data sets.
For instance, a clothing chain may see that in the Southwest, sales of darker suits and narrower ties are on the rise. This may allow them to promote clothing packages including both, or a new line of narrow ties well ahead of rivals who haven't noticed the trend yet.
5. Interact With Data
A chief benefit of data visualization is that it brings exposes changes in a timely manner. But unlike static charts, interactive data visualizations encourage users to explore and even manipulate the data to uncover other factors. This creates a better attitude for use of analytics.
For instance, big data visualization tools can show a boat manufacturer that sales of its larger craft are down. This could be due to a number of reasons. But team members actively exploring related issues and correlating them to actual boat sales can identify the root causes and find ways to minimize their impact to drive more sales.
6. Create New Discussion
One advantage to big data visualization is that it provides a ready means to tell stories from the data. Heat maps can show the development of product performance over time in multiple geographic areas, making it easier to see those that are performing very well or underperforming. This allows executives to drill down into specific locations to see what's being done well or poorly.
They may learn that targeting higher income market segments doesn't sell higher-priced products, or that traditionally solid sales of cleaning products are now less popular compared to environmentally-friendly green products. These insights could be used to brainstorm marketing strategies by region to support higher sales overall.
Big data visualization tools provide a more efficient way to use operational data. Changes in real-time performance and market indicators are easier for a wider audience of business leaders to recognize and respond to.
7. Machine Learning: Come One, Come All
The hype around machine learning is all to real. Not are only the big companies like Amazon, Google using machine learning to eliminate oh let’s say spam email, companies like Pinterest uses machine learning to show you relevant content, Yelp uses machine learning to sort through user-uploaded photos. Even Disqus uses machine learning to weed out spammy comments. Get ready to start using ML for your own businesses or user generated content.
Home Depot uses machine learning to help users find products faster and even smaller startups like Lyst use machine learning to help customers find relevant information for any query.
Customer service is being transformed by machine learning's ability to interpret customer emails and sort them to correct departments or areas within a company. Say goodbye to “Hello, operator.”
The future of machine learning is limitless.