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Within the pharmaceutical industry, there are many experts with varying backgrounds who specialize in data and analytics. Some are statisticians, others analysts or the big new buzz word of data scientists. Irrespective of the title or label, the biggest challenge is to communicate insights generated from data to the target audience. No matter how advanced the analytical approach, if the presenter is unable to explain the insights generated effectively while also toggling and capably communicating the analytical approach in a way others can understand, the message is lost. With a few simple steps, visualization can be a key tool for success!
Some key steps in effective communication which could be enhanced by visualization are shared below.
Understanding the Audience
Listening is a key tool for a good communicator. This includes better understanding the audience and what they value getting out of the collaboration or specific engagement. I have seen analytically-minded experts get very deep into the weeds when trying to understand the scope while losing the stakeholders. It is important to match the tools with the audience, for example, instead of sharing a busy spreadsheet of data, keep those details in the background and present a succinct summary of the scope in several slides.
“Visualization is an opportunity to create additional value when communicating key insights generated from data”
Defining the Problem
Another key tool is asking timely clarification questions when defining the problem. For example, if the deliverable is to be in slides for a one-time use, using a visualization technology to create graphics which summarize the analytical model results such as SAS, SPSS or Tableau could very useful. However, if there is an opportunity for automation, a technology such as R-Shiny can allow for reproducibility and reusability that may be of immense value to the collaborators.
Developing Insights and Solutions
There are many technologies which exist to analyze and visualize data; they will not be listed here. From tools within existing software to technologies and platforms designed specifically for graphics generation, the main purpose of visualization is for communicating insights and evidence generated.
After many efforts made to understand the audience, define the problem, dive deep into the data to produce insights and solutions, sharing of the results could make or break the collaboration. In addition to the above considerations, it’s important to be able to simply and concisely explain the journey to the evidence generated, including the advanced analytic methods used. Here, visualization can support the story by using art to describe the science and process of analytics.
Overall, visualization is an opportunity to create additional value when communicating key insights generated from data.