The right reactions for your digital strategy
Before you begin any data quality exercise, you need to know what you’re trying to achieve with your data.
If you set out to make flat bread, but follow the recipe for a bloomer, you’re going to be disappointed: yes, you might get a ‘perfect’ loaf, with all the right chemical reactions, but it’s not what you needed or wanted. And it will make a rubbish kebab.
Once you have a vision and commercial objective for your data, you can assign data quality policies that facilitate that goal. Setting out your data quality agenda before you’ve taken this step just doesn’t work: you won’t know what ‘good data’ looks like until you know what that data should be working towards. For example, if your primary data goal is to improve marketing personalisation, your data quality direction is going to be very different to if your goal is to create a more user-friendly e-commerce platform.