Important announcement at the end of this post, do not miss it.

Mentoring and feedback
The past week and a half has been quite an experience for me.  6 days ago I signed up to become a Mentor as part of the Tableau community #MentoringMeetup - Last year I tried to sign up with a previous mentoring program, but for whatever reason it went no further.  So 6 days ago, I took the plunge and decided to offer my services to those that felt they wanted to improve their Data Visualisation skills.  What followed was some wonderful honest conversations between my mentee and myself, an initial 2 hour call to discuss our data backgrounds, what we both wanted from the match up and how we wanted to go forward.  

Over the course of the next 3 days there was a constant communication between us which started with a brief discussion of the latest #makeovermonday dataset (which I participated in, to be able to understand the nuances of the data) and then it moved on to a back-and-forth iterative process of an initial concept drawn up by my mentee.  It was an enriching process to find someone that I never spoke to, who was relatively new to the community, have an appetite for data viz as much as I do and was completely open to ideas and taking on board feedback.

Part of the discussions we had, centred around the community and trying to improve your viz skills by asking for feedback.  Sometime feedback would be received other times you can feel as if no one is listening and start to question why are you here?

With this in mind and a lucky coincidence of taking a week's annual leave from work to recover from a manic first half of the year.  I decided to try and look out for those people in the #datafam, on Twitter, that were specifically asking for help & feedback on their work.  There was no process on picking which individual I tried to help, other than trying to pick those who I have never interacted with before, people that for all I know were new to the community.  These in my mind are the people that need supporting as much as possible and early into their data community lifespans.  

Over the next 3 or 4 days I then responded to seven individuals, from various locations in the world to assist them the best way I could.

My feedback I adopted formed a three step approach:

1.) I have seen and heard of the JLL (Jones Lang LaSalle) BI Centre of Excellence approach to data viz feedback from Zen Master, Simon Beaumont - an approach that was the created by their BI Strategy Director, Fi Gordon.  Their approach being that when reviewing their own internal dashboards they have a strict language that is enforced to remove any negative connotations.   The phrases "I like" and "I suggest" are used.

So I trialed using these as an initial feedback response, trying to list a few things that was done well in the visualisation, before trying to provide pointers and tips.

2.) I then followed up with a 'quick' redesign of their work, by downloading the workbook from Tableau Public and quickly mocking up visually what I felt would improve the viz.  This was done with the real intent not to change the essence of the viz, it should still be their work and their visualisation even after my feedback.  

A lot of what I centred my feedback on was formatting choices, alignment and space issues and lastly my new favourite topic - bring detail into the viz without cluttering / overpowering the rest of the aesthetic, so that the static image of the viz can also be read as well as the interactive version. 

3.) I then followed up with each of them on Twitter direct messages to explain my thinking in more depth and why I made the changes as I had done.  This was to help their understanding of what is important and why.  To encourage them that even though the feedback might be extensive, its not a negative on their initial work.

This proved to be a masterstroke, every single person I fed back to responded overwhelmingly positively.  Most highlighted how frustrating it can be to not receive feedback in such a vibrant community as the Tableau Twitter community, the #datafam.  What is more, to each person's credit, they all changed their vizzes and iterated them to the best of their ability to mirror my changes.  This is a credit to them, it shows that they care, they want to learn and they are open to feedback!

So I would just like to showcase the fantastic changes of each individual's, before and after images of their work.  

After which I have something important I want to announce.

Alisha Dhillon


Francisco Cardoso
Before (concept, not finalised viz)


Luther Flagstad




Priyanka Rohatgi


Takafuni Shukuya

Yanning Wang


Now to the announcement...

Feeding back with the data family on Twitter appears to be a very hit and miss thing.  We all strike up relationships, and naturally so, and of course are willing to give our time to our friends to help them be the best they can be.  

The massively successful #MakeoverMonday project has its own feedback process, using #MMVizReview, so they can pick those people asking for feedback on their work and give pointers to improve.  Yet, there are only two people doing this and their time is limited, an hour and half video review is not going to cover everyone.  

I should say here, this is not a slight or dig at Eva and Charlie, or Andy before, it's the nature of the beast - they only have so much time they can give to the project (no doubt they get directly contacted as well).  It is unreasonable to expect a project such as Makeover Monday to capture everyone in their feedback loop.  But our data community is much wider than two individuals!  

As part of my feedback process I have described in this article I have received feedback reminding me what it is like to be new in the community, new with Tableau, or even someone that has been around a while but is just for whatever reason not being heard or noticed.  Putting your work out there can be a daunting think, especially if you know it isn't perfect, asking for feedback is brave, no receiving any is, well disappointing, deflating, demoralising.   

I am not talking here of the quick 'like' or 'retweet' of encouragement, or the 'that's nice', 'I love it', 'great work!' - encouragement is fine, we need that, but it is not true feedback, no one can improve on a 'I love it', we all need pointers, definitive responses.  You can't learn effectively if you have to guess at what people like or don't like, be specific!  "I suggest" changing the colours of your fonts... , change the wording... , have you considered this...  

Provide feedback that people can act upon. 

So welcome to a new process I would like to kick off, which starts with a simple hashtag....

Add this hashtag to your visualisation on Twitter / LinkedIn, if you would like the data family to give you constructive feedback on your work.  

Why will this be any different than before?

1.)  We can search for hashtags!   If you are looking to support the community and have a spare few minutes, search the hashtag and pick someone that you don't know!  Give them constructive feedback.

2)  Want to find those individuals willing to give their time to support others, search the hashtag #DatafamFeedback and see who has been responding.

3)  Use it as an opportunity to strengthen our community and expand your own personal network.  No doubt we will find gems that have gone unheard for so long.

4.)  This will be a consistent and focused method which to focus on those individuals asking for feedback.

5.)  This does not replace #MMVizReview, still use this hashtag for specific feedback on Makeover Monday from the Makeover Monday Team.

This obviously will need buy-in from the #datafam, I cannot do this all myself.  Maybe this could be championed by a Zen Master or the Tableau Ambassadors?

Maybe some clever person, can create a leaderboard on who is responding to the #DatafamFeedback

Lets strengthen our community, work together, we all have skills we can feedback with and make this the best most inclusive community yet.

Thank you


P.s.  I finished my week by accepting to mentor a 2nd individual who has been working on their vizzes each week, recieving no feedback from the datafam and keen to learn, improve and get back to work after a career break to start a family.  I'm looking forward to being a part of their process to process!