Simon Beaumont – Biography
Simon Beaumont is Head of Information, Data Visualizer, and Tableau UK Healthcare User Group co-chair. He is passionate about all things data and Tableau.
Working in the NHS, he leads a Tableau Centre of Excellence, consisting of 15 analytical staff, supporting improvements in care through informed, visual, analytics.
In his spare time, Simon actively participates in Makeover Monday, Viz For Social Good and Data For A Cause in addition to vizzing about his favorite past time, sport, as part of the team responsible for #SportsVizSunday.
Simon’s thoughts and insights can be found on his blog, Vizionary (https://www.vizionaryblog.co.uk/).
Questions
Michael: Since I work in local (City) government, I was especially interested in your Workforce profiles Tableau Workbook you published on Tableau Public last year. Can you discuss the process you follow to develop workbooks like this (e.g., data prep, design, development)?
Simon: This report actually forms part of our annual accounts; within which we are required to provide an overview of our workforce in terms of age, pay grade, role and length of service.
Prior to Tableau this was provided through multiple, lengthily, tables that were produced from Excel Pivot Tables. One of the founding principles of our Tableau Centre of Excellence is the phrase ‘intrigue leads to insight’; when I reviewed the previous presentation of this data I quickly realised it was just that, data. There is was no intrigue, let along insight, it was reporting for reporting sake; we were asked to provide numbers so that is just what we did.
As with any of our internal reports the first step in designing this report was to understand the use case for the visualisation. In this example the key objective is to present analysis of our workforce in such a way that the public can understand our staffing profiles. Using visualisation best practice examples from across the community, we quickly realised a heatmap was a visual way of representing profiles, encouraging the user to move beyond the numbers and to, instead, understand the key messages. Beyond this we also wanted the report to be of value internally to managers; for this reason we added some filters at the top to allow internal users to filter the data by Gender, Working Hour and Month.
Michael: In your blog post last March, in the article, Business <> Boring : Heat dial demand analysis, you introduce the heat dial data visualization. Right now, I am going through some struggles as my business partners want to use pie charts as one of their visuals. Your heat dial somewhat resembles a pie chart. Did you have any concerns using this new dataviz and how did your business partners react to it?