Every growing organisation hits the same wall. The systems work, the data flows, the reports get generated. Then someone asks a question that requires combining data from three different sources and nobody can agree on which numbers are correct. That's the moment you realise your data has outgrown your governance.
What You Need to Know
- Data governance isn't a technology problem. It's an ownership problem. Someone needs to be accountable for data quality in every system
- Start with the data that matters most to decisions, not with a full audit of everything
- The NZ Privacy Act 2020 has raised the stakes on knowing where personal data lives and how it moves
- Governance frameworks that start small and grow work better than exhaustive policies that nobody follows
The Growth Problem
When you're a 20-person company with two systems, data governance is simple. One person probably set up both systems. They know where everything is. If numbers don't match, they can track down why in an afternoon.
At 100 people with eight systems, that model breaks. Different teams own different tools. Data gets duplicated across platforms. Field names don't match. "Customer" means one thing in the CRM and something different in the billing system. Nobody has the full picture.
68%
of organisations say they cannot fully trust the data they use for business decisions
Source: Harvard Business Review Analytics Services, 2021
This isn't a failure of technology. It's a failure of governance. The systems are doing exactly what they were configured to do. The problem is that nobody configured them to work together.
Where to Start
The instinct is to do a complete data audit. Map everything. Document every field in every system. Create a master data dictionary.
Don't. That takes months and by the time it's done, it's already out of date.
Start with decisions instead. What are the five most important decisions your leadership team makes regularly? What data do they need for those decisions? Where does that data come from? Is it reliable?
That's your starting scope. Govern the data that drives decisions first. Everything else can wait.
Step 1: Identify your decision data
List the reports and metrics your leadership team actually uses. Not the ones they should use, the ones they look at. Revenue dashboards, customer pipeline, project status, financial forecasts. Trace each metric back to its source system.
Step 2: Assign ownership
Every data source needs an owner. Not an IT person, a business owner. Someone who understands what the data means and can tell you when it's wrong. The finance team owns financial data. The sales team owns pipeline data. This sounds obvious, but in most organisations we work with, nobody has explicitly accepted this responsibility.
Step 3: Define quality standards
What does "good enough" look like for each data set? 100% accuracy is aspirational. Define what's acceptable. For financial reporting, the tolerance is low. For marketing analytics, it can be higher. Write it down. Share it with the people who produce the data.
The most effective governance we've seen isn't the most thorough. A three-page policy that everyone reads beats a fifty-page document that nobody opens.
Dr Tania Wolfgramm
Chief Research Officer
Step 4: Build simple checks
Automated data quality checks don't need to be sophisticated. A weekly report that flags records missing key fields. A monthly reconciliation between your CRM and billing system. A quarterly review of data access permissions.
You'd be surprised how much governance you can achieve with a scheduled SQL query and an email alert. Graduate to proper data quality tooling when the simple approach runs out of room.
John Li
Chief Technology Officer
Step 5: Review and adjust quarterly
Data governance isn't a project with an end date. It's an ongoing practice. Review your framework quarterly. What's working? Where are the gaps? Which new systems have been added? Which data sources have changed?
The Privacy Dimension
New Zealand's Privacy Act 2020 isn't just about consent forms. It requires organisations to know where personal data is stored, how it moves between systems, and who has access. For organisations with eight or ten systems that share customer data, this is a governance question as much as a compliance one.
42%
of NZ organisations surveyed said they were not fully confident in their compliance with the Privacy Act 2020
Source: Office of the Privacy Commissioner, Annual Report 2021
If you can't trace a customer's data across your systems, you've got a governance gap that's also a compliance risk.
Keep It Simple
The organisations that get data governance right share one characteristic: they keep it simple enough to maintain. A lightweight framework that the team understands and follows will always outperform a exhaustive one that lives in a document nobody reads.
Start small. Govern what matters. Expand when you need to.