| | July 20199don't make logical sense. Over time, data collection methodologies change, leaving fields that were initially populated with good data deprecated due to newer collection methods.As a result, you may need to normalize the data set prior to visualization.Assembling a comprehensive data set prior to attempting to visualize the data is critical to providing an accurate visualization of the data.Accuracy of the data during the first presentation to leadership is crucial in gaining confidence in the platform and will allow you to grow the platform rapidly.Defining the values you are presenting sounds like a straightforward process, but it can make or break a visualization project.The goal with any reporting is consistency across visualizations.To accomplish this, you must be very precise and consistent in how you define and refer to your values, whether they be calculated or native in the data set.An example of this is how you define "New Patient" in healthcare.If you are in a sizable organization, a simple label can mean very different things to different viewers of the data.For example, is the patient new to the provider; new to the specialty; new to the organization; or the billing definition of "new" (3 years since last treated in the organization)?As you can see, this gets very confusing, very quickly.Standardize your naming conventions, and you will be poised for success.The last principle to understand is how your consumers of the visualizations prefer to work.Depending on your organization, you will most likely find a number of consumers who are very comfortable with dynamically accessing the visualizations to leverage the filtering, drill down and other capabilities that the platform provides; where others will prefer a static PDF delivered to them. We utilized a bolt-on tool that worked with our platform to schedule the delivery of provider-specific dashboards to the individual attending physicians on a monthly basis.This allowed for a greater distribution of the visualizations without the consumption of additional licenses for the platform. This hybrid approach has served us well in providing information to all who need it. Educating the consumers on which type of visualizations are available will help gain buy-in and expedite the acceptance and usage of the platform. To further gain buy-in and to justify the purchase of the platform, try to quickly determine the pain points in your organization. Some of the first visualizations we developed were focused on "missing charges."By understanding where this was occurring, we were able to work with the staff involved to recover what would have been lost revenue and educate them so that their workflow could address the gaps. The amounts recovered from these visualizations alone have essentially paid for the platform.These are the basic principles that I've found can help with the successful implementation and adoption of a Business Intelligence/Analytics platform to provide visualization into your data.In all the principles described above, remember to keep the lines of communication open with the business side of the organization. Meet with senior leadership to ensure you are given direction on where to focus, but also engage with the front-line workers to understand the data that they are entering into the systems. This is what you will need to drive change and lead to success within any organization. HTStandardize on your naming conventions and you will be poised for success
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