Unleashing Creativity: how to connect your analytical brain with your creative side

As data professionals, we're used to thinking analytically and logically, following established methodologies and best practices to deliver insights and drive action. But in a rapidly changing and competitive business environment, relying solely on established frameworks and practices may not be enough. To truly make an impact and stay ahead of the curve, you need to be creative and innovative in your approach to data-driven decision-making.

Creativity: from coloring mandalas to a PhD award nomination

I never thought of myself as a creative person. I’m analytical, rational, and direct. I was never particularly good at drawing, my musical skills were way below zero, and let’s not even start about dancing … But I always created things. As a child I wrote a book for children, made necklaces and drew and colored mandalas. Probably my parents still have boxes filled with my ‘output’…

Years later, during my PhD research, I learned how to combine my creativity with my analytical skills. I learned how to make my two hemispheres work TOGETHER, instead of one at a time. In the end, my thesis was even nominated for an award in the medical rehabilitation sciences. Even though I currently do not work as a scientist, I’m delighted to have developed the skill to be creative AND analytical at the same time. It brought me where I am today: designing dashboards. Letting my left and right hemisphere have some fun together and make amazing sh*t.

In this article, we'll explore practical tips for unleashing your creativity as a data professional, from brainstorming techniques to reframing problems and thinking outside the box.

Breaking Out of the Box: Overcoming Common Barriers to Creativity

One of the biggest barriers to creativity is the fear of failure. As data professionals, we're often risk-averse and hesitant to take chances that could result in suboptimal outcomes or negative feedback from stakeholders. But to be truly creative, we need to embrace the possibility of failure and see it as an opportunity for learning and growth.

Another common barrier to creativity is our tendency to stick to established frameworks and methodologies, even when they may not be the best fit for a given problem. To overcome this barrier, it can be helpful to challenge assumptions, reframe problems, and think outside the box. For example, instead of starting with a predefined set of graphs, you could start by asking open-ended questions about the business problem and exploring different visuals and analysis techniques that might be relevant.

Brainstorming Techniques: Generating Ideas and Insights

Brainstorming is a classic creativity technique that can be especially useful in the data-driven decision-making process. To get the most out of brainstorming, it's important to create a supportive and non-judgmental environment where everyone's ideas are valued and respected. Some tips for effective brainstorming include setting clear goals and objectives, encouraging diverse perspectives and experiences, and using visual aids and other tools to spark ideas.

I have two moments when designing dashboards in which I apply the brainstorming technique:

1. When discussing the content and information structure of the dashboard. I ask all stakeholders to come up with as many ideas as possible regarding their dashboard desires. Don’t talk, don’t edit, just keep generating ideas on sticky notes. After this initial brainstorming, we take the time to filter duplicates, find the best ideas, organize, and prioritize. But that’s the next step…
2. The second brainstorming moment is when I need to discover which chart type suits the message and data best. What I teach participants in my design course, is to try at least three graph types for one final visual. Just quickly draw the graphs with pencil and paper, so you’re not limited by the possible lack of technical skills or distracted by the numerous custom visuals. First find out WHAT you need to make, before finding out HOW.

Creativity in the real world

A while ago one of my clients called me with a very specific information request and couldn’t find the right chart to show the information. The request was to show the time spend productively in a berth (docking station of ships ??) and where time got lost over a day. There were about five stages during the day in which time could be spent productively or got lost (for instance, when cleaning was needed, or a ship was delayed and therefore the berth remained empty for a while). During this phone call, I already wrote down four chart types. After the call, I created a mini dummy dataset and started experimenting on paper first. I came up with an alluvial, icicle, sunburst, and Sankey diagram. Pretty quickly I saw that some were more likely than others to provide the required insights. In the end, we chose the Sankey diagram, which I quickly could make in Power BI as a concept.

Thinking Like a Designer: Putting Creativity into Action

Design thinking is a powerful methodology for putting creativity into action in the data-driven decision-making process. By approaching problems from a user-centered perspective and using iterative and collaborative processes to design solutions, data professionals can create more user-friendly and impactful outcomes. Some key principles of design thinking include empathy, prototyping, and testing, all of which can help data professionals generate new ideas and insights and translate them into meaningful business outcomes.

So, what do you do during each of these phases? Some suggestions:

1. Empathize: Understand the user's needs by gathering information through observation and interviews and putting oneself in their shoes. For example, you might talk to end-users to learn about the challenges they face in understanding data.
2. Define: Analyse the information gathered in the previous phase to define the user's problem statement, needs, and constraints. For example, based on the interviews, you might define the problem as "end-users struggle to understand where more profit can be made, and costs reduced."
3. Ideate: Generate a wide range of ideas to solve the problem, without judging them. For example, you can brainstorm several ideas such as creating interactive charts or designing a dashboard with fewer metrics. This is also the phase where pencil and paper might come in handy.
4. Prototype: Build a simple, scaled-down version of the solution to test and refine the idea. For example, you might create a prototype of the dashboard with a few key metrics to test with end users. You don’t need the actual data just yet, a smaller dummy dataset might work just perfectly. By first testing the prototype, you can save a lot of time and money on the engineering side of dashboard development.
5. Test: Test the prototype with end-users and gather feedback to improve the solution. For example, you might test the prototype with a few end-users to gather feedback on the dashboard's usability and usefulness. Obviously, you need to be very clear about the fact that you’ve been working on a dummy dataset.

?Let’s get this creativity thing rolling…

By embracing creativity in the data-driven decision-making process, you can create more impactful and user-friendly outcomes that drive business success. So next time you're facing a challenging problem, don't be afraid to break out of the box and unleash your creativity.

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