By Adam L. Stanley, Global CIO and Frank Spadafora, Technology Director, Investor Services
Data visualization is the presentation of data in a pictorial format that enables decision-makers to better grasp complex ideas, so when it comes to creating data visualization, it’s easy to focus entirely on how to make the most beautiful, brilliant chart possible. But that’s not the whole point or advantage of data visualization. In fact, the process to get there is as important as the goal itself.
Effective data visualization is based on the premise that data is well-defined and trustworthy, and this is where the journey starts. Technology leaders must work with business leadership to define the what, where, and why of mission-critical data. Organizations must face challenges of data quality and standardization, governance, and client confidentiality, in addition to answering the primary questions of how this information will be delivered and consumed.
Cushman & Wakefield’s own journey toward developing great data visualization as a communication tool, and as a way to improve our data, followed seven steps. These were developed through an effort to create a production and revenue tracking visualization tool for our Valuation & Advisory group. The effort successfully resulted in coordinated data strategy and improved processes across a service line with global reach and complexity.
Seven Steps in the Journey
1) Start with the end in mind. What question is the business trying to answer? Often, organizations begin “big data” initiatives by gathering information and then thinking about questions they want the data to answer. Start instead with the complex questions your clients want answered.
2) Define data and understand complexity. Data is often contextual in delivery and opaque in nature. Challenge the rule of thumb, and identify and clearly define data through business subject expertise. Deploy standards when possible, and create process to manage complexity.
3) Drive service and insights together. IT and business must collaborate to address important client questions. Availability and collection of data must be coupled with a true understanding of our clients and their specific practices and interests.
4) Park intuition and experiential biases. “In God we trust; all others must bring data,” W. Edwards Deming claimed. Business and technology leaders can be biased by prior experience, creating a barrier to new ideas, or, leaders’ opinions get in the way of fact.
5) Watch the pot. A typical person can absorb only so much information in one visualization. Effective data visualizations tend to be simple and utilize only the most valuable data. Rather than overflow the pot, tell your story via multiple visualizations.
6) Drive client profitability. The end game is not the data visualization itself. Our technology energy focuses on what drives client profitability. A more profitable client makes for a more favorable business relationship. That is our end game.
7) A picture is worth a thousand words. The strongest data model and most compelling insight will fall flat if the visualization is not good. While we should not focus so much attention on fitting the question and data into a pretty sample visualization chart, we do need to get the chart right. A successful visualization can cultivate insight and foster deeper intelligence by exposing relationships beyond the traditional lens.
By embarking on the data visualization journey, you’ll find the reward is rich: creating value, identifying risks and presenting opportunities, and opening new possibilities for competitive advantage. Feel free to contact either one of us with comments or questions.