Over the holidays I watched the 1988 Tom Hanks film ‘Big’, in which a young boy’s wish to be “big” transforms him into an adult overnight. He eventually lands a job as a toy company executive, where his childlike perspective proves invaluable in an industry that had lost touch with its core audience.
For me this premise offered a surprisingly relevant caution about the over-reliance of data being used to drive the ideation and design of new products or features. As I will explain, I am not advocating against the use of data but in the context of seeing this movie I do think that, especially if you are trying to bring change to a business problem, you need to use design and qualitative insights to widely ideate new successful outcomes.
The Voice of the User vs. The Voice of the Metric
In ‘Big’, Josh Baskin (played by Tom Hanks) succeeds because he actually understands what makes toys fun. While his colleagues analyse market trends and sales projections, Josh simply asks, “But would a kid want to play with it?”. This fundamental question can be skipped and get buried under mountains of analytics in some product development process.
Modern product teams can find themselves in a similar position to the film’s out-of-touch executives. Armed with sophisticated analytics tools, A/B tests, and user metrics, they risk forgetting that behind every data point is a human experience. Just as the toy executives couldn’t quantify “fun,” today’s product managers might struggle to measure delight, emotional resonance, or the kind of magic that makes products truly memorable.
The danger of playing it safe with data
The film’s toy company executives represent the “safe” way of thinking — analytical, market-driven, risk-averse and often disconnected from the end-user’s true needs. Today’s data-driven approach to product design can fall into the same trap. When we begin with and over-index on metrics, we risk creating products that optimise for goals and metrics rather than genuine user value in the form of good outcomes. We may even fall into constrained thinking that prevents us from ideating a wider range of possible ideas before you commit to a direction.
Consider Josh’s reaction to a transforming building toy in the film. While the data might have supported its market viability, Josh immediately identifies that it’s not fun — it’s just a building that turns into a robot. His childlike perspective cuts through the market analysis to expose a fundamental flaw in the product’s conception. You might say that Josh represents both the end user as well as the insights you can learn from good qualitative research and design intuition.
Finding Balance in Modern Product Design
The lesson isn’t that data is bad — it’s that data alone is insufficient. Just as the toy company needed both Josh’s intuitive understanding and traditional business acumen to succeed, modern product design requires a balance between quantitative evidence and qualitative understanding.
Another way of thinking about this is the difference between a data-driven approach as to a data-informed approach. You will probably be more effective at analysing your data if you are clear on what your design hypothesis is.
Some key takeaways for successful product teams:
- Maintain direct contact with users, not just their data
- Create space for research and experience-based decision making
- Not everything valuable can be understood by metrics alone
- Use data to inform design and validate hypotheses
Also published on Medium.
Full disclosure: I used Claude.ai to generate a first draft of this post, but the majority of the text is now largely my own writing. A first experiment for me!