| | DECEMBER 20188CIOReviewTHE BIGGEST CHALLENGE TO EFFECTIVE DATA VISUALIZATIONSBy Kevin Loudermilk, Director, Auto Data, USAAExecutives, your company's infrastructure is not the most significant challenge impacting your data visualization program. Of course, you must address the technology, people, processes, and data issues that can, and eventually will, reduce your effectiveness. But once you have done this, you must face the biggest challenge to useful visualizations - you. Your expectations and requirements will ultimately determine how successful your data visualization program is.The "Easy" IssuesTechnology, people, process, and data issues are not always easy to address, but they are the obvious issues that we know about and create plans to resolve. Your company has probably already looked at these, but let's quickly walk through them, just in case.Choosing which software best fits into your IT stack and budget can be a difficult task. What business questions do you need to answer, and how will you consume this information? There is no right answer, contrary to what the vendors at a conference will tell you. There are many choices, and all have their strengths and weaknesses. Trust your analytical and IT community to make a good recommendation and stick with it. Changing technology regularly will guarantee failure.You must provide training for your analysts, not just on the chosen tool(s), but on design, storytelling, data manipulation, and even business ethics. The visualizations they create will drive your business decisions, and you will need clear, unbiased information to make the best choices for your business. Leaving training up to on the job self-development is inadequate. Invest in training your analysts to maximize their effectiveness.Unless they are addressed early and strategically, data issues can quickly escalate and create rework, or worse, decisions that will negatively impact your business goals. You have to decide what works best for the volume, security, and reliability needs of your company and establish appropriate processes for governing these requirements. Ensure someone is managing the quality of your data, whether in IT or on the business side. Poor data quality leads to poor analysis. Finally, think about having one source of the truth. That means eliminating data replication, defining metrics once for everyone's use, implementing a version control process, and reconciling reporting across multiple visualizations as appropriate. Data maintenance is complicated, but you cannot afford to neglect it. The Hard StuffI realize that sometimes, technology, people, process, and data requirements are overlooked in the desire to stand up a visualization program quickly. But they are not the most significant challenge out there. You are. Don't be offended. You didn't do it on purpose. Examine your expectations and see if you are guilty of any of the following:IN MY OPINION
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