Using Tableau to help consumers make more informed decisions about where to eat or buy food

Did you know that the NSW Food Authority has a “Name & Shame” register on their web site? The Register of Penalty Notices is publicly available and allows consumers to see who has been issued with a penalty notice for breaching NSW food safety laws as well as details of the alleged offence.

The Register includes businesses or individuals “…if they have been issued with a penalty notice for an alleged food safety offence and have not challenged the notice…” The NSW Food Authority publishes the register to give “…consumers more information to make decisions about where they eat or buy food.”

My intent is not to comment on the NSW Food Authorities policy in this blog. It’s up to you to decide if “naming and shaming” businesses or individuals is the right strategy to bring about change. It’s also up to you whether you would make decisions about where to eat or buy food based on reviewing the Penalty Notices. My goal with this blog is to show that there is a better way to present the Penalty Notices in the register to make it easier for people to find what they are looking for. This blog will show you the Register of Penalty Notices data as it is currently presented by the NSW Food Authority on their web site and then how the same data can be presented visually in Tableau.

NSW Food Authority Name & Shame Register

The NSW Food Authority Register of Penalty Notices presents information as per the screenshots below.

Keyword search and browsing options:







Table containing a list of all Penalty Notices:



The Penalty Notice Number can be clicked to take you to another page listing more details about the infringement.

The information is great, but it requires consumers to read through a lot of text to find what might be of interest. There is an opportunity to present the information in a way that makes it easier for consumers to find what they are looking for.

Using Tableau to visualise the data

We performed a few technical steps to extract the data from the NSW Food Authority web site and prepare it for visualising in Tableau. You can read a summary of these steps at the end of this blog.

The resultant data file was then used as a source to build a Tableau dashboard that allows consumers to interact visually with the data. Go ahead and have a play with the interactive dashboard below!

If you’d like a bit more information about how to use the interactive dashboard before having a play, then read the section following the dashboard which takes you through how a typical consumer might interact with it.

Click here to visit the Tableau Penalty Notices Dashboard

Please note that any comments/questions about the Penalty Notices should be directed to the NSW Food Authority.

Walking through a typical use case

We all purchase food or dine in restaurants so this type of dashboard is potentially of value to everyone. Below is a series of screenshots (with commentary) explaining a typical scenario of how someone would use the dashboard.

1. The initial view is a map of NSW with circles representing the location of offences. The larger the circle, the higher the number of offences by that Party. There is also a list of all Offences at the bottom of the screen.


2. Consumers can narrow down their search by typing in a Postcode, selecting a Council or a Trade Name or Offence Code, or filtering by number of offences. Here is an example of typing in a postcode of 2000. You will notice that both the map and the list of Penalty Notices at the bottom of the screen are filtered to Postcode 2000.


3. Consumers can further zoom in by hovering over the map until the zoom controls appear.


4. After zooming in, the pin icon in the zoom controls area turns blue. Click on this to zoom back out to the view that best fits the area you are filtered for (in this case, Postcode 2000).



5. Consumers can focus in on alleged offenders by clicking on a specific circle, holding down the Control key and multi-selecting circles or by lassoing multiple circles by clicking and dragging to draw a square around an area of circles. You will notice that the list of Offences at the bottom of the screen is reduced to those alleged offenders selected in the map.




6. Consumers can then hover their mouse over the red dollar amounts (Penalty Amount) to see the details of that specific penalty notice. You will notice that this view also provides a Google Map link which takes the user to a Google Map for the address of the Trade Party served. There is also a link to the specific Penalty Notice page on the NSW Food Authority web site.


7. Clicking on the “NSW Food Authority web site” link:



Technical overview of how the data was prepared

Getting a bit technical for a moment, we did the following to prepare the data before creating the Tableau dashboard:

  • Developed a Python script to read the Penalty Notice data (including the data available from separate web pages linked by Penalty Notice Number) and output it to a flat file.
  • Each Penalty Notice has an address so we took the opportunity to geocode each record.
  • The geocoding step resulted in us having the latitude and longitude coordinates for each Penalty Notice. This allows us to then visualise the Penalty Notices on a map.
  • The geocoding doesn’t necessarily result in an exact positioning of the alleged offending party on the map. The position should be treated as a good approximation.
 

Conclusion

The NSW Food Authority publishes the Register of Penalty Notices to give “…consumers more information to make decisions about where they eat or buy food.” I believe that presenting the information in a visual way that allows consumers to more readily interact with the data goes further toward fulfilling this objective.

Feel free to contact Chris Kearns directly if you’d like to learn how Altis Consulting can help you produce similar visualisations/dashboards for your business:

+61 2 9211 1522

chrisk@altis.com.au 
www.altis.com.au/ourpartners.html


About the author

Chris Kearns has been in the IT industry since 1990 and has been focussed on Data Warehousing and Business Intelligence since 1996. Chris joined Altis Consulting as the first employee in 1998 and has worked as a Consultant, Quality Assurance Manager, Education Practice Lead, Account Manager, Tableau Certified Trainer, and Data Visualisation Practice Lead. He has helped to deliver solutions to many customers across a variety of industries in Australia and New Zealand.

When not at work, Chris can be found on the tennis court, playing the guitar, singing or swing dancing; usually not all at once.

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