Your housing association has big ambitions, and management's demand is clear: "We need to do more with data." Terms such as "predictive maintenance" and "complex management information" are being used more and more frequently. As IT manager, you feel the pressure to deliver quick results. It is therefore very tempting to take the shortest route: you connect Power BI directly to the ERP system.

It seems like the most logical step. The ERP is the beating heart of the organization; after all, all transactions, from rent payments to repair requests, are processed there. Within a few weeks, you will have your first set of dashboards. The project seems to be off to a flying start.

But then, after a few months, things start to falter. Managers complain that the figures don't add up. Departments present different results. Confidence in the dashboard wanes and employees revert to their old, familiar Excel sheets. The project loses momentum and gets bogged down in discussions about the reliability of the data. Welcome to the data pitfall. And the cause is that the project did not start with the first step, but with the second.

The crucial mistake: starting with the transaction

The error lies in a fundamental misunderstanding of how data works. The ERP system is primarily designed for transaction processing, while the value of that transaction is entirely dependent on the data to which it is linked: the master data.

A repair request (transaction data) is useless if the object data (master data), such as the year of construction or the dimensions of the property, are incorrect. A rent payment cannot be analyzed if the tenant information is incomplete or outdated.

Master data and transaction data complement each other: master data provides meaning, while transaction data records events. Without good master data, transaction data loses its value; without transaction data, master data remains static and without context. If you start analyzing and reporting directly on transaction data without first ensuring the quality of your master data, you are building a house on quicksand. Every analysis you produce is, by definition, unreliable. The result is not only a failed BI project, but also growing distrust in the use of data throughout the organization.

The only way forward: start with the foundation

The solution is as simple as it is crucial: always start with the foundation. Before you build a single dashboard, the focus should be on validating, cleaning, and managing your master data. This may feel like a delay, but in reality, it is the only sustainable acceleration.

This means:

1. Validate the quality of your master data: Is your real estate and tenant data complete, up-to-date, and accurate? And ensure that the data remains of high quality.
2. Set up governance: Assign clear owners for each data domain and make clear agreements about definitions and maintaining the master dataset.
3. Create a single source of truth: Ensure you have one central, reliable source for your master data that is used throughout the entire organization.

When your master data is in order, you have a solid starting point for everything you want to do with data later on. It not only makes reports and dashboards more reliable, but also much easier to build. It takes some time to set this up properly at the beginning, but you will more than make up for that time later on because your analyses will be faster and you will have less to correct or discuss in terms of definitions.