We often see books and articles talking about the importance of adopting data to make decisions. They usually focus on technology and strategy, and most of them agree there seems to be a skill gap preventing everyone from reaching their full potential when it comes to using data. We also hear a lot about the challenges of getting people to adopt new ways of working with their data - be it in a new tool implementation or in a lack of evidence-driven decision-making. There are also those sad reports from analysts churning dashboard after dashboard, only for them to end up in the bottomless void of dashboards everyone seems to ask for and then never use.
This may be the biggest hurdle in fostering a genuinely data-informed culture: getting people excited to make use of the wonderful things data can give them.
If a good strategy is in place and the appropriate tools are being developed by a team of experts, why does no one else seem to care or bother? Why is it so difficult to engage stakeholders when showcasing that new report? Why does the leadership team still go with their gut feeling instead of using all those KPIs that took months of development? The answer may be more obvious than we’d like to admit: change is hard, and it gets even more difficult when the culprit of change seems full of jargon, complicated concepts, code, new tech and maths.
This is where communities of knowledge play a crucial role: by fostering a sense of belonging and shared enthusiasm, they help to break down barriers, encourage open dialogue, and ultimately can inspire a genuine cultural shift while providing a supportive environment where individuals can learn, collaborate, and grow.
The bit where I rave about the Tableau Community.
No other tool in the market understands the power of community better than Tableau and their datafam. Even before I knew of the hashtag or had a Twitter account, I already knew about their super welcoming community. I started using Tableau in early 2016. I got a job as an Insights Analyst, and my first few months were all about spreadsheets. Excel was my safe space. Then, within a few months, a colleague discovered Tableau. After some time, our boss jumped into it as our new go-to tool for reports, and we slowly started turning our beloved spreadsheets into shiny new Tableau reports.
My first Tableau report was created shortly thereafter. It was a Pest Management report. The theme may not have been glamorous, but I was very proud of what I could achieve in very few days of scavenging through the Tableau Community forums. I had used Stack Overflow, but this was next level. People not only answered questions others had - they wrote entire tutorials about it! They got creative!
I remember finishing the first version of my brand-new dashboard, showing it to my boss and getting feedback that it was hard for him to compare categories within a tooltip when hovering over a map. What he really wanted was a bar chart within the map. I was intrigued - this was Tableau 10.3. There were no visuals in tooltips back then. I looked up the forums and came across a brilliant tutorial on how to sort of mimic a bar chart inside a tooltip using only text. How cool is that?!
My report was launched later that year, and that was about when I met Alex Waleczek and learned about his Tableau User Group in Auckland. There were meet-ups about making reports with this new tool! I even timidly was a speaker at one of them! How cool is that?!
Fast-forward a few years, and finding a community of people enthusiastic about data visualisation had changed my career - I had fully transitioned from a business analyst that nerds about spreadsheets to a data analyst starting her own data visualisation business.
This was when I asked Alex if he had any advice for someone jumping head-first into consulting. The comment that stuck with me was: if you’re not on Twitter following the #datafam, you’re missing out. I have never been a big fan of social media. I do not enjoy the whole Twitter experience. I had a Facebook account for less than a year, which felt like enough for a lifetime (I killed my account in 2011 and never looked back). The only social media I maintained was LinkedIn because of work. Getting on Twitter was a big effort for me. But alas, there I was, hiding behind my logo, shily looking around.
Then there were the Makeover Monday challenges, run by Eva Murray and Charlie Hutcheson at the time on Twitter. I had heard of Makeover Mondays before. I had even joined an in-person one, run at our local TUG. But this was a whole different level: an entire buzzing community of people would grab a common dataset and makeover a viz, sharing it for feedback from everyone. It looked terrifying, so I watched it for a few weeks from the sidelines. I finally jumped into it on Week 01 of 2020 and published my first ever viz on Tableau Public. Here it is:
I didn’t expect the feedback I received. I expected to perhaps see a couple of likes. It exploded, and my viz was reviewed at the weekly Makeover Monday feedback sessions run by Eva Murray and Charlie Hutcheson. Not only that, my first-ever viz was selected among their weekly favourites. HOW-COOL-IS-THAT?!
You don’t need a specific tool to have a thriving community.
That Tableau wouldn’t be what it is today without its community is a given. But the power of a great data community outweighs any tool. This is what Eva Murray’s book Empowered by Data is all about. Eva has been running public projects in the data community for many years. This book is the summary of all her learnings. It is a practical manual full of information, tips, and ideas on how to create your very own amazing and engaging data community.
In the book, Eva argues that giving people within a company the opportunity to connect encourages everyone to share their challenges, learnings, and questions, to identify overlaps or gaps in projects and informally co-ordinate initiatives that can help everyone overcome challenges together and feel more like an integral part of data initiatives. It also provides an opportunity for people at different levels in their data journeys to learn from each other - where technical analysts can share what they know about the inner workings of data, while the subject matter experts can bring their valuable practical knowledge about how the business works. Communities can enable the adoption of tools and increase the use of data through collaborative projects. They can also be highly effective at dissolving information siloes.
Data communities are, therefore, the missing link in building a data-informed culture: it enables the strategy to be shared and acted upon by everyone, promotes technology upskilling and adoption, and brings the invaluable human element to the equation. There’s also the IKEA effect: people value more the things they help build.
All this sounds like great stuff, and you may be now wondering how you’d implement something like this within your own company. Empowered by Data contains a treasure trove of supplemental materials, frameworks, and ideas on how to start nurturing your data community. And it can be simpler than you’d expect. Some ideas include:
Start an internal group of people interested in a common theme related to data: a meet-up about a tool or a particular area of data work (like data visualisation, engineering or AI).
Run lunch & learn sessions where people can share their expertise of how they used data to make an impactful decision.
Create an online forum to help others with their data woes - much like your own Stack Overflow or Tableau Community forum.
Establish a regular schedule of formal training sessions and make them available widely within the company.
Create your own internal mini-conference where people can come and share their data-related work with others.
Create mini hackathons or weekly challenges around a particular skill set open to anyone to participate. Make feedback an integral part of these challenges so everyone can learn from each other.
Empowered by Data by Eva Murray also talks about the challenges you may face while creating and maintaining a data community. Even though communities are somewhat decentralised and a bit anarchic in nature, it is paramount to define a clear purpose, a set of values and intentions before launching any initiatives. This will serve as a guiding star for those times when things seem a little too chaotic. The book dedicates a whole chapter to this subject. It runs through the main potential risks for your data community, including how to address the potential for distractions, the creation of echo chambers or groupthink, the lack of buy-in or how to deal with disruptors.
Lastly, Eva also outlines how to set up an internal community, with a clear and in-depth process composed of 4 phases:
Phase 1 - Planning: This may include documenting and clearly outlining your community’s purpose, its goals, and what key activities will be part of it.
Phase 2 - Pilot: run a test drive of a few initiatives to ensure they’ll be sustainable in the long run - this is where you figure out the most operational bits of how the community will be run - rooms, times for calls, invites on people’s calendars, the strategy for sharing content, the topics, etc.
Phase 3 - Growth: Once the community is up and running, it takes a life of its own, but challenges to its growth may still arise. These can include a lack of time available from others, changes in management or restructures or technical data governance issues.
Phase 4 - Development: this is when you begin to formalise your community’s processes and how new members are onboarded, when and how the periodic sessions and challenges are run, and if the community can evolve into wider learning and developer programs within the company. This also includes making an internal communications plan for your community to ensure people are in the loop of the latest news and changes.
Following Murray’s frameworks will surely help you create the ideal environment for everyone to be part of the significant data transformation that must occur for a culture to embrace data as part of its culture.
Should you read it?
If you’re currently struggling with internal data initiatives, buy-in from stakeholders or getting other teams excited about embracing data in their day-to-day, creating an internal community where people can congregate and learn, teach and share their concerns, skills, challenges, and joys can be the missing link you’re looking for. Empowered by Data is an easy read and full of valuable, practical content and insight on how to create a fantastic data community your way.
Always check your local library first to see if any of the books I recommend are available. If they’re not, consider donating a copy!