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Understanding the Problem

When I accepted my first Tableau job over four years ago, I was required to work in a closed computer lab where new ideas were developed in quiet isolation. The data visualizations, interactive dashboards, and demonstrations I created were observed by only a small group of people. The amount of feedback I received was naturally limited. While this level of isolation gave me freedom of direction, it eventually caused my learning and development to plateau. I realized something needed to change.

After two years in this role, a feeling of restlessness encouraged me to seek a more exciting environment at Gallup. I hoped this transition, and the uncertainty that came with it, would renew my professional development by challenging me in new ways. I was quickly rewarded as the number of projects increased significantly and the range of requests I received expanded my responsibilities when compared with my previous role. This change renewed the professional growth I was looking for.

Unfortunately, complacency crept back into my work before long. The new culprit was my reliance on fixed-requirements when starting new projects. This paint-by-numbers approach to Tableau is a common mistake that plagues even the most talented data teams. Having key decisions already set so early in the data process prevents many valuable activities from ever taking place, like data discovery and ad-hoc analysis.

Software methodologies are a poor fit for Tableau analysis in the long run; they dull potential insights and creativity. Using a standard process is a good way to reduce errors and wasted motion, but when taken too far, it can entrench behaviors and fix expectations, which hurts growth, responsiveness, and continuous improvement. Focusing too much on efficiency had paused my progress again, which caused fears of complacency to resurface.

Lessons from #MakeoverMonday

An answer, which would alleviate my concerns, didn’t emerge until I participated in my first #MakeoverMonday session at the Tableau Conference in 2016 in Austin, Texas. During the event, I witnessed spontaneous ideas, valuable discussions, and group collaborations buzz around a crowded room. Everyone shared the goal of trying to find new and elegant ways to visualize a dataset. This experience was rather foreign to me because my normal routine and specific role prevented collaborative design work or valuable feedback.

For the first time in my Tableau career I was faced with a real design challenge. #MakeoverMonday forced me to face the uncomfortable situation of having complete design freedom. The final design decisions were now solely up to me, which required more confidence and a willingness to make mistakes. Sharing my work openly was equally as intimidating. I am not immune to this anxiety, and these pressures forced me to be more purposeful throughout my design process. This discomfort led to a surprising source of creativity which I never knew existed before this experience.

Questions that previously never seemed intimidating started to require an exhausting amount of time to explore: Should I design this for me, or my audience? Do I want to focus on best practices, creativity, or novelty? Is it easy to understand? Will it capture interest? Will it keep interest? Is it accurate? Avoiding tough questions makes our design process easier, but significantly reduces the potential impact of our work.

Developing a New Approach

Upon returning from Austin, I discarded my typical approach to Tableau and went to work with renewed purpose. My approach now emphasized sharing work, testing ideas, collaborating with new people, and stretching my capacity for creativity. This change in thinking gave me an outlet to break up my habits and challenge the status quo more broadly.

Sharing ideas more openly also led me to deeply reflect on my past design choices, which then caused a constant stream of second-guessing. Brooding over potential mistakes is often not a welcomed activity, but this honest self-assessment is an important step to self-improvement. Insulating ourselves by avoiding honest feedback prevents us from learning.

This experience has taught me how important it is to get outside of my comfort zone and embrace criticism. I am even more encouraged to push myself further into situations that are challenging and uncomfortable. Similarly, these lessons can be applied more broadly to an organization. A truly data-driven culture supports its employees by allowing them to explore, test, challenge, create, and even fail with new ideas.

Now, rigid requirements have been replaced with uncertainty. Once clearly articulated project goals have been exchanged for a blank canvas. Conversations have changed from checking off requests without reflection to working closely with stakeholders to collaboratively solve problems. Although impossible to predict, fostering a creative environment is the best way for a Tableau team to add value and stay relevant in the long run.

Improvement is never linear for us individually or for our teams. The creative process ebbs and flows in a seemingly messy fashion. Inspiration goes dark at unexpected times. After countless iterations, rarely anything turns out as originally intended. The creative process, coupled with honest feedback, can be harsh and unforgiving, but it’s a cycle we must endure and one that our employers must embrace when trying to reach our full potential.