Creativity and data are often regarded as conflicting concepts. This means that embracing one would imply the abandonment of the other. However, few people see the possibility of embracing both at the front lines of business.
Creativity is the process of generating novel and useful ideas. It helps companies to compete in an uncertain, fast-changing, dynamic business environment. Data analytics is the process of collecting and analyzing information and facts. It functions as the cornerstone for developing and growing new business opportunities.
Although both are important, creativity and data analytics are often seen as incompatible. People see creativity as a “hot” process, driven by intuition, imagination, and fantasy. In contrast, they see data analytics as a “cold” process, drawing on rationality, logic, and structured procedures.
But, are creativity and data analytics exclusive? In this article, I will present where they can complement each other in business settings.
Where can data enhance creativity?
To understand how data can help creativity, let’s first take a look at the creative process. The creative process has several stages.
A creator must first identify a business problem needing creative solutions. Then, they need to search for relevant information to analyze the problem. Afterward, the creator needs to generate potential ideas and solutions for the problem. Finally, the creator chooses and presents the most creative idea. The sequence of the stages is not rigid; the creator may travel back and forth between the stages.
- Data analytics help problem identification. Creativity arises when we need to change or improve something but we are not happy with the existing solutions (if there are any). Customer or employee data can signal us new problems or situations that demand creative solutions or new changes.
- Data analytics help information searching. To generate creative ideas, one must first gather relevant information about the problem. Data analysis can provide hidden insights into a problem. Those insights are difficult to reveal with the creator’s imagination or intuition.
- Data analytics help idea generation. Even creative people find it difficult to think “outside of the box”. Existing frameworks and knowledge can limit our ability to generate original ideas. Data analysis results can help creatives by showing unusual associations between concepts. For example, the data may show a creative design of a product decreases customers’ intention to buy. This information can motivate the creatives to focus on a different aspect.
- Idea selection and communication. After generating ideas, the creator needs to choose the best from the available ideas. Data simulation techniques are useful to compare and assess different ideas. Besides, data can be helpful to communicate the pros and cons of the new idea to relevant parties.
Where can creativity help data analytics?
To understand the role of creativity in data analytics, let’s talk about the steps of data analytics. An analyst needs to:
- define a question
- develop a hypothesis
- test the hypothesis with data;
- and draw conclusions.
These steps are also iterative. The analysts can go back and forth between different steps in the analysis process.
Creativity helps define a business question. How to define a problem often determines the solution we will have. Asking the right question is the start to find the right solution. Albert Einstein noted that “If I had only one hour to save the world, I would spend fifty-five minutes defining the problem, and only five minutes finding the solution”. Because creatives are good at looking at a problem from divergent angles, they can help the analysts define a better question to start with.
Creativity helps develop a hypothesis. Creativity can help data professionals to develop original hypotheses. We often develop hypotheses based on our most available experience and knowledge. This makes hypothesis-testing a process of confirming what we have already known. Creatives can think beyond the obvious and ask counterintuitive questions. They can help data analysts think of new associations and relationships.
Creativity helps test with data. Data can be very complex so that we cannot analyze them using the single tool we are most familiar with. Creativity helps make novel combinations of different tools for effective data analysis. Sticking to old routines may lead to insufficient analysis and an inadequate understanding of the data.
Creativity helps draw conclusions. Creativity can promote data visualization which facilitates drawing correct conclusions. For instance, the creative use of colors, texts, tables, and figures can help us understand the essence of the results and draw correct conclusions.
On a final note
Seeing data analytics and creativity as conflicting is limiting. Instead, we need to think about ways in which they can work together and benefit each other. One good way to this to hire candidates who excel in both creative thinking and data analytics skills.
It can be hard to find those “ambidextrous” employees, but it is definitely not impossible. Or, managers could build teams consisting of both analysts and creatives. Encouraging the exchange of ideas and collaborate together within the team is another path to the great integration.