Data Visualization: Why It's Important
Does your organization currently have a strategic initiative focused on presenting and making better use of data? Companies spend an inordinate amount of time, money and resources on these initiatives year over year only to see them lose momentum or fail altogether. It can be an endless cycle but also a cycle that can be broken. Let’s start with examining the why. There are many reasons companies struggle in this area but in my experience it typically comes down to 3 things:
Presentation is too complex – The best data in the world presented in an unclear, difficult to digest and tough to translate manner accomplishes very little. In the end, everyone wants insight that is concise and relevant to them. The data must tell a story and that story must be compelling enough to command the attention of the intended audience. Too many times solutions fail because too much raw data is presented at the top layer, confusing and often losing its audience out of the gate.
Data is not actionable – It’s not the data people care about, it’s what the data incites them to do that is important. Insight derived from data and presented cleanly and graphically to specific roles for a specific purpose can transform companies. The timeliness of these insights also has great influence on an organization’s ability to take action. In today’s online world the need for real-time or near real-time insight is profound. The ability to keep a finger on the company’s pulse and course correct in the moment is absolutely critical. Many traditional analytics solutions fail to embrace this concept limiting the potential value their data can provide.
Story is incomplete – Important information typically resides across many disparate organizations and repositories. The power of data visualization is realized when you relate and present these sources together. For instance, you might have application uptime data which by itself is valuable but correlating that with customer usage, customer satisfaction, social media sentiment or sales data is more compelling and powerful as you begin to see the impact of downtime. This can be a challenge when the data has multiple owners and lives in multiple formats (structured and unstructured) but it’s one of the most important elements to having your data tell the right story and get on a path to the holy grail – predictive analytics.
Some of the information above touches on underlying data management concepts but are important enablers for effective data visualization. Data visualization is not about graphs, KPIs or even the underlying data itself. It’s about bringing data to life; having it tell a compelling story, making it easy to consume and driving appropriate action.
“The greatest value of a picture is when it forces us to notice what we never expected to see.”
- John Tukey
Here are 5 common sense principles to help your organization break the cycle and become more proactive, predictive and data driven in its decision making:
Keep it simple – Present the data in a clean, easy to understand format. Design a flow to get to the relevant detail (i.e. click through) but make it so the user understands what they see at a glance. Make it accessible with multiple modalities including mobile. Don’t limit when, where or how users access and leverage insight.
Present the story – Focus on visualizing insight rather than the data itself. Bring to life the story the data is telling us as much as possible. If you can present the meaning of the data it will be more likely to be actioned. Data visualization should not simply answer known questions, it should discover and raise new ones.
Personalize & customize – Provide insight specific to the user’s role. Know who the user is and give them data insight specific to their job. Give the user power to customize for the things they care about. This is crucial for increasing the “signal to noise ratio” and a feature that is often an afterthought. Make it a priority.
Go real-time – Determine the right level of timeliness for each type of data being presented and if real-time is needed, fight for the changes required to enable it.
Gain breadth – Don’t try to “boil the ocean” but identify and go after the data sources needed to present key insight. If you can’t get them all right away make sure they are on the roadmap and stay diligent. Think about a “single pane of glass” approach, consolidate tools so users don’t need to go to multiple places and tools to obtain the information they need.
Asking new and important questions is critical to leveraging big data effectively. Without visualization we are much less efficient in identifying those questions and ultimately taking transformative action. This is why data visualization is such a vital piece of the data puzzle. It’s our light in a sea of darkness.
- Kyle Wagner, VP of Operations
Blueprint Consulting Services