Organizations are increasingly data-driven organizations no longer exclusively managed, shared, or processed within a central team. Whether you work in marketing, finance, product development, support, sales or even HR – data and business insights are no longer an afterthought but a priority to drive the decision-making process across more roles within organizations. Whether this is to measure individual KPIs, a team’s ROI, or find new avenues for growth, data is all around us and the quality of business insights can only be as good as the quality of the data on which they rely upon.
As a result of this shift, the question of responsibility and accountability is becoming increasingly common. On the one hand, the lines are increasingly blurred on who’s responsible for collecting and managing the data. On the other hand, with more and better solutions available to turn data into insights, there’s often confusion as to who is responsible to ensure insights are often accurate across the organization. What’s more, with different teams within an organization often relying upon one repository of data which is then turned to insights with different tools (and often different metrics), it’s not unusual to find surprises further down the line when results are not consistent across the business.
Usually, there are three main ‘gatekeepers’ for data accuracy in an organization:
1. Data Teams: whether you have an Insights, BI, or Research team – they are the ones that live and breathe data. It is their responsibility to ensure the data is collected and stored correctly. Besides that, they need to think hard to ensure that the data they’re gathering and sharing is in line with business priorities, metrics, and KPIs.
2. CIO: many companies have a Chief Information Officer and in some occasions a Chief Data Officer or Chief Insights Officer. This role is an increasingly important one. It’s not only responsible for data quality and accuracy across the organization but should also orchestrate all the data efforts to drive the business forward in a way that strategically makes the most of the data available.
3. Everyone: with the explosion of data, analytics, and business insights over the past decade, every employee is to an extent responsible to manage and manipulate data and insights which are relevant to their function or their broader team. While a decade ago many of us would have been tempted to point the finger at our data analyst or BI team when there’s an issue, today we’re often responsible for many of the data flaws we see in our own insights. As a result of this, everyone in an organization needs to step up, and become increasingly responsible for the quality of the data or insights used to evaluate their work.
Often there isn’t a straight answer for who is responsible for data quality. This is why in most cases it’s a joint organizational effort. Data systems and processes need to be carefully established so there’s ongoing data testing and the right quality checks along the way. And most importantly, everyone managing or using data needs to take ownership of their work – especially as data is no longer in the domain of a central team and we’re moving into a world where most roles will require a degree of data analysis and expertise.