cancel
Showing results for 
Search instead for 
Did you mean: 
About the Author
Ben Jones is the founder and CEO of Data Literacy, LLC, a training and education company that's on a mission to help people learn the language of data. Ben teaches data visualization theory at the University of Washington, he's the author of Communicating Data With Tableau (O'Reilly 2014) and the forthcoming book Avoiding Data Pitfalls (Wiley, 2019). Ben also writes about data topics at his blog DataRemixed.com, and to balance out the digital side of things, he loves hiking and backpacking on the beautiful trails of the Pacific Northwest. Ben holds a BS in Mechanical Engineering from UCLA (2000) and an MBA from California Lutheran University (2011).

How to Start Small with Data

BJones
New Member - Level 1
1 0 109

My career at Tableau taught me that data could be an incredible business tool. It can help you confirm your intuition and provide proof to help you make gut decisions with more confidence. It can help you avoid upcoming obstacles and alert you to opportunities you might miss. It can help challenge your preconceptions to make incredible insight.

 

Leveraging data for your company is like using a radar to fly a plane. It provides a level of confidence you wouldn't have otherwise.

 

However, my career at Tableau also taught me that many business owners don't consider themselves very competent – or even capable – when working with data. Many are even a little data phobic once you start talking about spreadsheets, databases, visualization, and analytics.

 

It made me realize that, for most of us, our formal education never prepared us for this world awash in data. How could they know 20 – or even 10 – years ago that this is what a professional career would require? It became clear to me that there is a massive education gap.

 

Since I had that realization, I’ve made it my goal to “teach people how to fish” rather than just setting up their dashboards. I've started a new venture called Data Literacy to help fill in these gaps – to provide education, training, and guidance to people who want to learn the core concepts behind the data, the practical impact of data, what pitfalls to avoid, and how to ask the right kinds of questions.

 

The biggest thing I’ve learned is that data isn’t just about the statistics. It’s about the humans.

 

Data lesson one: Listen to your instincts

 

Someone told me the other day I was a data guru. It’s funny, because I feel like I’m just getting started in a field that’s changing at an incredibly rapid pace. From my guru’s perspective, there's always more that can be learned.

 

With data, you have to check your ego at the door and approach the learning process with a childlike playfulness. That’s because – despite the statistics and math involved – data and analytics are inherently tied to gut and intuition. You can’t rely so much on your expertise in data that you lose the connection to the initial intuitive question you brought data in to check against in the first place.

 

Otherwise, it's easy to get caught in a trough of disillusionment about what data can and cannot accomplish. I hear all the time from companies who say they’ve invested so much time and energy in data but aren’t realizing the benefit of it. Or, they’ll say they’re misled more often than not.

 

But data and human intuition aren’t mutually exclusive – good data science melds the two together. We need to apply our own instinct and intuition to the process of working with data. A human spark is required to even be able to know what matters. What are the priorities? What questions should we ask?

 

Data lesson two: It’s about the story

 

Before Tableau, I worked at a medical device company that had just launched a new wearable product. We launched one size with four colors and another size with three – excluding pink. The decision was made to keep down costs, but the data showed customers wanted the pink option in both sizes.

 

I was due to present to a bunch of the top executives for a full day of product launch results. I had the stats to show the demand for the pink option, but I knew for the executives to understand what a real problem it was, they needed more than stats on a slide.

 

I got in touch with our customer help line and social media manager to get quotes from actual customers. In my presentation, rather than only showing the sales stats for the two sizes, I included the verbatim quotes along with customer pictures and names.

 

The data view of the stats of the sales of this product was one thing; the charts were interesting. But seeing that someone named Julie on Twitter was complaining about the lack of the pink option had the executives leaning forward in their chairs. They connected with the data on a whole different level.

 

There is power in finding the human stories to illustrate the statistical data. These human anecdotes help you tell a data story that demands attention.

 

How to start small with data

 

You don’t have to have a degree in data science to start getting the story behind the numbers. Here are five ways you can use data to uncover – and tell – powerful, moving stories.

 

  1. Realize you're not starting at zero. You're likely already using data to make decisions. Start by identifying where and acknowledging the ways data has already helped you in your business. (You're done! Just kidding.)
  2. Conduct a small survey. Ask questions of your clients and customers – use a simple survey, email, in person, or online. This can help you put numbers to market needs and understand the verbiage people are using to describe their issues.
  3. Start with free tools already available to you. A lot of the cost-effective solutions you can use to measure and track your business, like Google Analytics or MailChimp, already provide some pretty useful data dashboards. Familiarize yourself with the tools you’re already using.
  4. Watch online tutorials. The way I learned a lot of these tools was by simply watching the amazing tutorials online. You can find some great options to help you learn the ins and outs.
  5. Connect what you have. After you've started seeing what interfaces those platforms give you out of the box, the next step is to connect an analytics platform like Tableau or Power BI to data from your various sources to begin executing analytics. Don’t forget to look for ways to humanize the data and connect it to your story.