Shifting data quality to the C-suite: here’s how to take ownership
How many times have you been told that data is the ‘lifeblood’ of your organisation? Does it contain all the information your business needs for success?
Well, although your data can unlock invaluable insights and help organisations reach their goals, the truth is that many businesses are struggling with inaccurate and untrusted data. In fact, a recent study by HFS Research found that business leaders think only 60% of their data is usable. And that paints a very different picture of data’s role in business success. Instead of opening up opportunities, poor-quality data is slowing down decision-making, impacting customer experience, and ultimately affecting the bottom line.
That’s why I’m making the case for bringing responsibility for data quality into the C-suite. As a leader, so much of what you do is driven by data, from setting direction and strategic decision-making to improving performance and managing risk. If data accuracy isn’t already in your remit, now’s the time to ask yourself why.
How to get started
Understanding the value of data quality and knowing how to improve it are two different things. I regularly work with leaders going through data quality initiatives, often during major digital transformation programmes, and the advice I give is straightforward. Engage and take ownership. Here’s how:
1. Assemble a data quality crack team
Data quality initiatives should not be dumped on the IT team. To get the balance right, you need a mix of people from around the organisation who understand how to achieve data accuracy as well as the frustrations of working with inaccurate data and a knowledge of the blockers to overcome. Find people who are passionate about this - and I promise there will be some - and you’ll see real progress.
And if you choose to appoint a Chief Data Officer (CDO), which I recommend, give them the remit to drive all your data-related changes. Ideally, they will report to the CEO, giving them much more authority to make the changes your organisation needs.
Reporting to a CIO or CFO is not always effective, and, in my experience, many CDOs don’t report to the C-suite at all, which can really limit their effectiveness.
2. Get to know your data
Focus effort on business-critical data and the data that must be as accurate as possible. Understand how that data links to your organisation’s business objectives, how it supports decision-making, and where poor data accuracy has the most impact. And then, drill down into how accurate that priority data is now, find out who owns it, and to what extent your business is being impacted by inaccuracy.
3. Set meaningful goals
We’d all love 100% accurate data (and actually, some data does need that level of accuracy), but as data is ever-changing, it may not be possible to guarantee that every single piece of data is correct. What level of inaccuracy can your business tolerate?
I recommend that the C-suite owns these goals, it demonstrates that you’re taking them seriously, and it encourages the rest of the organisation to work towards them, too. Buy-in at all levels, where everyone understands they have a stake, significantly increases success rates.
4. Get your governance right
For your data to remain accurate, consistent, and complete long-term, you need clearly defined rules, roles, and responsibilities for data creation, use, and storage. Appoint an owner, and include your data quality goals and the scope of data covered.
Think about how often you’ll measure data accuracy against your targets and decide what will happen if data accuracy falls below an acceptable level. Consider using a framework like Six Sigma to highlight how far your data deviates from your target so you can quickly take appropriate action.
5. Role model behaviour
There is a clear link between good data quality and leaders demonstrating how they use key data to make business-critical decisions. And it makes sense; by making the connection between accurate data and good business outcomes, you’re helping the rest of the organisation understand why they should be prioritising data quality.
So, spend time explaining how you used data to help you come to a decision and what the outcome has been. Consider other ways to engage your people: demonstrate how trust in data helps with compliance in the GDPR and CCPA space, for example, or highlight examples of how accurate data has helped your business succeed.
They say the only constant is change, and this is absolutely true for your data. Your data isn’t static and is always changing, so improving your organisation’s data quality cannot be a one-off project. Instead, take a “data first” approach, making data quality your highest priority because your success depends on it. And be prepared to be in this for the long haul, but be confident that what you’re doing will benefit the business and the people who work there.