Every startup strives to use data more effectively to make faster decisions, ship better products, have happier customers and ultimately generate sustainable growth. When it comes to leveraging data, a startup's objectives can be summarised into four Jobs-to-be-Done. The order of importance will vary by type/maturity of business, but these four JTBDs broadly capture what almost every startup wants to do with respect to its data:

1. Use data to enhance the intelligence and utility of its products/services

2. Improve the accessibility and reliability of data/insights available to its teams

3. Increase the quality and speed of decisions being made by its teams

4. Build data infrastructure that is easy to manage and designed to scale 

 

Most startups have an ambitious vision for how they'd like to use data. Defining this vision is hard enough, but the real challenge lies in making the complex and nuanced decisions necessary to bring this vision to life. Getting these seemingly-trivial choices right can have a huge compounding impact on the future trajectory of a business - often in unforeseeable ways (see Butterfly effect).

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Below is a subset of the most common data-related challenges I see startups wrestling with: