Who do you trust in your life? For many people the answer would probably depend on what for!
You might trust a friend with a secret, but perhaps not to repair your car. You might trust a doctor to diagnose your illness, but not to invest your savings. You might trust a colleague to help you make a decision, but not their ability to prepare an accurate report.
When it comes to data, asking, ‘who do you trust’ is important. And the answer, ‘for what?’ is equally as important.
Which services do we trust to give us data-informed decisions we can rely on? Which companies do we happily share data with? Which teams in our company do we trust to look after data?
In a world where data underpins everything from generating insights into shopping habits, to using those insights to create targeted advertising campaigns, being trusted with data creates a virtuous cycle where customers are more likely to:
- Use your services
- Share data with you.
Being trusted with data means funders, regulators, and activists respect your methods. Being trusted with data means employees are comfortable that their work and values are reflected in your organisation’s public perception. Being trusted with data means people will use your services, or contribute the data you need to make your services work.
The fast-paced, automated decision making ecosystems many organisations are building need sophisticated, hi-tech data infrastructure. What they often lack is a robust approach to making sure this infrastructure is trustworthy.
This is why businesses big and small, are looking for ways to improve trust in their use of data. The approach that many are taking is called data assurance, which is actually a combination of existing practices like data ethics and data governance, but applied in ways that build trust.
What is data assurance?
Data assurance is a set of processes and practices that together help organisations build confidence in the ways they use data.
The purpose of pursuing data assurance is to improve perceptions of an organisation’s ability to create data-powered services, and data-informed insights that can be relied on. And that the organisation is trusted to look after the data it collects, uses, and shares.
The result? For many businesses, from supermarket retailers like the UK’s Co-operative Group to advertising giant WPP, being ‘trusted with data’ is a source of brand value.
What’s involved in data assurance?
Data assurance embraces a range of practices that happen across the lifecycle of how data is used by an organisation – from the way it (and its partners) collect data, to how data is stored, to how its finally used.
This requires looking at both the technical and human aspects of data, trying to understand how data supply can become reliable, and whether the data itself and the insights people take from data can be relied on.
Data assurance therefore brings together a range of existing practices, from data governance to data ethics. These practices include:
- Data strategy. Data strategy guides how an organisation uses data in support of it’s wider business goals, directing both use of data and investments in data. Increasingly data strategies integrate trust concepts – for example, making improvements to data infrastructure to ensure the reliable supply of data.
- Data governance. Good data governance is critical to ensuring that people and systems have appropriately controlled and secured access to data, following company policies and relevant external regulations. Data governance plans are however not sufficient on their own, as they often neglect the more human components of data infrastructure such as ethics and culture.
- Data ethics. Finding the balance between delivering value from data whilst avoiding harmful impacts on people or organisations is the purpose behind data ethics practices. Data ethics is about not just relying on regulations like the GDPR to avoid problems, but about doing work with data that doesn’t contravene societal and organisational values.
- Data culture describes the ways of working and thinking that support the effective use of data. Culture is tricky to change, often taking years of hard work. But there's one feature of an effective data culture that is easy to grasp and easier to implement – decision making. If you can embed better data-informed decision making into your organisation, then you’ll build trust in what you do and raise the profile of data assurance practices that themselves support decision making. For example, ensuring data flows to the right people, and ensuring that everyone understands how to use data ethically.
Many organisations already include these sorts of practices in their work. Data assurance is all about focusing on trust as an outcome for each one.
