Unlocking Data Enthusiasm: How to Spark Interest in Bored Audiences

Time to engage with everyone's inner data nerd

Data teams are increasingly told to spend more of their time “engaging the business” in data transformations.  Initially, this sounds easy; people are more interested in data than ever before, and board members are eagerly awaiting their data dividend.  

However, the reality is that data is a topic that still causes many business audiences to moan, groan and ultimately zone out.

So where are data teams going wrong?  How can they keep people outside data teams interested in data long enough to run a successful data transformation?  These are the questions which we will answer in this article.

First, let us dispel the myth that data is a dull topic.

If you’ve attended a Tableau conference, you will have seen first-hand just how passionate people can get about data.  If you’ve not had this experience, then check out the Let’s All Data musical number they used to kick off the conference one year.

However, you don’t have to travel that far to see people displaying their passion for data.  You can see data passion everywhere, from the scene of classmates elbowing each other out of the way to see everyone's exam results to the sprawling stats spreadsheets of the fantasy football fan to the eternal popularity of top 100 lists.  It’s all data!

Just like flames, there is something about data that draws everyone in.  And as technology captures and quantifies more of the human experience, we find more numbers to obsess over.  The number of steps we take each day.  The number of likes on a post or tweet.  Even the number of poops your baby takes a day (new parent here - sorry for the overshare).

This convinces me that everyone is a secret data nerd, but too often, the topic is just approached in the wrong way.

I think most people's love-hate relationship with data is like my love-hate relationship with languages.

I hated learning languages at school.  I have painful memories of reciting verb conjugations and struggling with grammatical concepts like dative and accusative.  Needless to say, I didn't do well in my language exams.

However, today I love languages so much that after university, I spent three years travelling as a language teacher whilst learning other languages.  I find experiences like learning and understanding a new word and then realising you can't translate it into your native tongue to be one of life's great pleasures.  You literally gain an entirely new way of thinking about the world.

I haven't changed.  Put me in a language lesson, and I will still struggle to focus when grammar comes up.  I love how languages enable connections with new people, thoughts and cultures, but I am not at all interested in the mechanics of language.

This is similar to most people's position on data.  Discussion of participles, clauses and sentence structures is as appealing to me as discussion of partitions, clusters and data structures is to most people not in data careers.

People are fascinated by the insights data can offer into their personal and professional interests and are bored by the mechanics of how data works.  Quite honestly, I don’t blame them, and with today’s tech and UI, I question how much of the mechanics they really need to understand.

What can we learn from this?

If data teams want to engage and excite the rest of the business, then the conversation should focus less on how and more on what data can do for people.

Discussion of the modern data stack is as relevant to most data consumers (and business sponsors) as discussion of the modern publishing stack is to readers.

If you need to discuss the data stack to get investment, then lead with examples of business insights that are currently not possible or delayed because the current stack is too cumbersome.  Then offer analogies for how modernising the data stack will increase agility and speed up insights.

An offer to help a business area improve its data quality is as appealing as an offer to review a document's spelling, punctuation and grammar.  

I’m currently doing a writing course, and someone did offer to review this very article.  I said yes because their offer was focused on making the article more valuable and impactful, although they did spot some punctuation issues.  Likewise, don’t offer to help teams with their data quality. Offer to help them get more impact and value from their data.

In short, to excite people about data, first understand their priorities and then explain how data can help them with what matters to them.  Save all the technical talk for internal meetings or for when the aim of the communication isn’t to create excitement but to help stakeholders understand why a project is going to be challenging.