Intelligent risk-taking

It’s April 1985. Coca-Cola has been losing market share to Pepsi, and extensive taste-testing data has revealed that a new, sweeter version of the iconic drink is preferred over the original. Confident in this data, the company introduced the change, expecting a surge in sales. Instead, thousands of complaints rolled in, forcing Coca-Cola to revert to the classic formula after just 79 days.

The company had focused too narrowly on a single data point – taste preference – while overlooking the emotional connection consumers had with the original product. Coca-Cola’s CEO at the time, Roberto Goizueta, saw the ‘new Coke’ decision as a bold but necessary gamble, a prime example of intelligent risk-taking. When Coca-Cola reintroduced the classic formula, it sparked headlines, and sales skyrocketed.

What began as a short-term failure ultimately fostered long-term brand loyalty. The lesson here? Data can inform risky decisions, but a more holistic view – including the capacity to pivot when needed – can lead to even bigger rewards.

What can the arts learn from this? Should we abandon data analysis in favour of intuition? Not exactly.

Like Coca-Cola, cultural organisations must balance data with creativity and audience engagement, using data to inform intelligent risks while being ready to adapt when things don’t go as planned. The story of new Coke underscores the importance of understanding both data and the emotional landscape of your audience, a lesson especially relevant in the arts.

Moving beyond data-driven: Why data-informed is better

In my last article, I examined the limitations of a purely data-driven approach. In the cultural sector, where experiences defy easy measurement, intelligent risk-taking involves going beyond the numbers.

While being data-driven implies a rigid reliance on metrics, a data-informed approach values both data and intuition. As one industry professional succinctly put it: “Data isn’t telling us anything… data-informed is better.”

This is at the heart of intelligent risk-taking – decisions based on robust insights but flexible enough to adapt when needed. As another professional I spoke with put it: “Data [is] a tool for exploration, but people lead the way.”

How data-informed strategy encourages intelligent risk-taking

1. Combine quantitative and qualitative insights: A data-informed approach combines hard data with qualitative insights. V&A’s integration of the Taylor Swift: The Eras Tour trail highlights this, using cultural trends data to engage younger audiences by embracing pop culture.
2. Encourage creativity and risk-taking: By not being bound solely by data, organisations can take creative risks. War Horse at the National Theatre was a major risk with no historical precedent but became a phenomenal success.
3. Think long term: Data reflects past performance, but intelligent risk-taking involves considering long-term strategic goals. Organisations must think about what revenue generation models will look like 10, 20, 50 years from now, adapting to the rise of younger, more diverse audiences. Cultural institutions that focus solely on current trends risk missing the shift in audience demographics and preferences, as demonstrated by the rapid growth of immersive, social-media-friendly experiences like Lightroom and Frameless, that are leaving traditional museums behind.
4. Stay flexible: One of the most critical aspects of intelligent risk-taking is the ability to adjust when things don’t go as planned. Coca-Cola’s course correction with new Coke is a perfect example of this. Similarly, in the arts, combining data from box office reports, audience surveys and artistic input can help organisations tweak decisions in real time and avoid continuity bias – the assumption that what worked in the past will always work in the future. It’s impossible to predict everything that will happen when you announce your season a year in advance. Instead build flexibility into your plans, so you can adjust and respond to what unfolds in the real world. Define clear objectives, but remain flexible in execution.
5. Look beyond existing audiences: Learning from current audiences will only tell you about those already engaged. To understand the full market and future opportunities, organisations need to look beyond their databases into broader cultural trends, consumer behaviour and external data sources like market reports and digital platforms. Embracing external data and insights will help identify new audiences and potential opportunities.
6. Avoid the outlier trap: It’s easy to get distracted by vocal complaints or overwhelming feedback on specific issues, but these often come from a vocal minority. As one professional noted, “there’s a feeling that we get lots of complaints about this” but it might only reflect a tiny fraction of the overall audience. A data-informed approach requires critical thinking to avoid overreacting to these outliers while staying focused on the broader trends. This is crucial in the arts, where passionate feedback often represents the opinions of the most vocal, not the majority.

All organisations have access to a wealth of data; the challenge lies in using what you have more creatively. You don’t need to capture everything. Often, it’s about making the most of existing data and topping it up with external sources.

This approach ensures that any organisation, regardless of size, can be data-informed without needing vast resources. Small cultural institutions, for example, can leverage public data, industry benchmarks, or even insights from peers to enhance their decision-making.

Smart risks, big rewards: A framework for data-driven risk

1. Begin with the big picture: Ask the right questions: Start with the end in mind. Define your strategic objectives and consider how data can best support them. It’s easy to fall into the trap of asking questions that are purely descriptive, like “how important are members to us?” – which can lead to answers that are only surface-level. Instead, shift the focus to bigger-picture thinking by asking “why are members important?” This approach leads to a more strategic use of data, where every question is designed to drive insights that move the organisation closer to its broader mission and vision.
2. Contextualise your data: Data must be interpreted within context. For example, if ticket sales are declining, simply raising prices to sustain revenue could backfire, losing more volume. In such cases, the solution might lie in taking a broader look at your business model and exploring alternative strategies to drive volume or reaffirm your value proposition.
3. Broaden your perspective: Use multiple data sources: Don’t rely on a single source for information as seen with the new Coke example. Instead, combine quantitative and qualitative data, benchmarks and insights from multiple channels. This multi-source approach helps to understand both risks and opportunities from different angles, making it easier to spot where creative risk-taking could succeed.
4. Foster cross-departmental collaboration: Data silos can prevent the kind of broad understanding that drives intelligent risk-taking. One organisation is developing a cross-organisational framework to break down these silos, creating forums where data can be discussed and debated from multiple perspectives, ensuring that data, creativity and expertise combine effectively to inform decision-making.
5. Build data literacy: Improve data literacy across the organisation by ensuring staff can understand, question and apply data effectively. This means not just interpreting numbers but knowing what data is relevant, spotting biases and combining insights with human expertise. When staff can confidently engage with data, decisions become more risk-aware and impactful.
6. Challenge assumptions: Don’t let the data confirm what you already believe. Use it to test long-standing assumptions. One theatre organisation discovered through data analysis that increasing ticket prices didn’t negatively affect sales in a part of the house they thought was undesirable. But it only sold when demand was high and therefore could take a higher price – a finding that allowed them to be more flexible in their pricing strategy, ultimately driving revenue.
7. Create a ‘What If?’ space: Encourage a sandbox mentality where anyone in the organisation can propose bold “What if?” ideas such as turning a foyer into an artist space or letting under-25s take over programming. Data can then be used to explore and refine these ideas without fear of failure, turning creative risks into strategic opportunities.

Guided by data, driven by innovation

Data should guide, not constrain, acting as an essential launchpad for taking intelligent risks that push organisations beyond the status quo. The lesson from new Coke is clear: don’t rely solely on one metric, and always leave room to pivot when bold ideas don’t pan out. Missteps can create opportunities for even more impactful successes.

The future belongs to those willing to take risks. By blending data with creative intuition, long-term thinking and flexibility, cultural organisations can take calculated risks that drive deeper audience engagement and financial sustainability.

Intelligent risk-taking is about more than just playing it safe – it’s about leading the way, innovating, redefining what’s possible and not being afraid to challenge conventional thinking when the data doesn’t tell the whole story. Data isn’t the answer, but it’s an essential part of the process.

In the final article of the series, I’ll explore how emerging technologies and data trends will further shape the future of strategic decision-making in the arts, helping organisations balance creativity, audience engagement and long-term sustainability.