Of course real data is necessary for testing and building data-driven products and features, but it is far from sufficient. At Thoughtworks, we’ve had a lot of success in early stage discovery and planning by simulating products with synthetic data. This allows us to test in a lightweight way many aspects of a product, just not its actual predictive or optimisation performance. With only the general shape of the data we expect, we can align stakeholders on how we will measure success, explore and uncover dependencies in the end-to-end process, prototype the user experience, and even run sensitivity studies to quantify the benefits of future data curation! While we aim to make real data really easy to access, this isn’t always the reality for many organisations exploring data-driven products. If you’re in this situation, talk to us at Thoughtworks about how to get more from exploration with synthetic data.
Disclaimer: The statements and opinions expressed in this article are those of the author(s) and do not necessarily reflect the positions of Thoughtworks.
