More and more housing associations are making the move to data-driven operations. In doing so, they often run into similar challenges that slow down the development. In this blog, we discuss the three biggest pitfalls of this transition and how to avoid them.

The challenges

The housing association sector faces significant challenges. Demand for affordable, sustainable housing is increasing, while resources and capacity are under pressure. At the same time, corporations must make sustainability improvements to reduce energy costs for tenants and comply with a growing body of regulations and legislation.

Consider new laws such as the Affordable Rent Act and the revised Housing Corporation Governance Code 2025. On top of that come general data standards such as the AVG, the Data Act and the AI Act. This requires strict compliance.

Standardization is also growing within the sector. Via Aedes, initiatives such as SBR, RGS, CORA, VERA and the Regiegroep Data Standaarden are being rolled out. At the same time, more and more open data is becoming available through government sources, such as the Land Registry and the Digital System for the Environment Act.

A common misconception is that data-driven work is primarily something technical and that data belongs to IT. One quickly thinks of dashboards, data platforms and BI tools. Often a data-driven work process is also started from the IT department, because "data belongs to IT, right?". But this is a fallacy that leads to problems such as:

1. Data initiatives do not align with practice.
2. Employees do not feel involved or do not know what is expected of them.
3. A gap is opening up between "the data department" and the rest of the organization.

But data does not belong to IT any more than money belongs to Finance. Data belongs to the entire organization and especially to the departments that work with it. IT is an important partner, but the business determines what data means, why it is important and how it is deployed. That requires ownership from the business.

For housing associations, this is especially important. Not only do they have to comply with all kinds of data standards, but they can also extract a lot of value from external sources such as open data from the government. Control over data should therefore lie with the business - not with the IT department or IT vendor.

As an organization, how do you take ownership of data?

1. Start with a data strategy. Link data to your organizational goals, such as customer satisfaction or sustainability.
2. Solve real problems. Use concrete business questions as a starting point. Policy follows after that.
3. Collaborate with other departments. Involve departments such as rental, maintenance and customer contact in using data.
4. Invest in data skills. Not everyone needs to be a data analyst, but basic knowledge is essential.

Only when this foundation is in place can you think about tools and platforms in a focused way. Without ownership and clear requirements from the business, data-driven work remains an IT project - and that's exactly what you want to avoid.

Pitfall 2: Building without a foundation = unreliable data 

A common mistake in data-driven work is skipping the basics: good data quality and clear agreements on data usage. Without reliable data, analyses are not only useless, but can also lead to wrong decisions. Yet many housing associations are still working with outdated, incomplete or inconsistent data, with all its consequences:

1. Trust in data is declining, causing employees to fall back on their gut feelings.
2. Decisions are made based on false assumptions.
3. Reports - both internal and external - are unnecessarily time-consuming and error-prone.

How do you prevent this?

1. Invest in a solid data foundation. Get your foundation in order before you start analyzing data.
2. Start small. For example, start with real estate or customer data. Make that clean, standardized and well-structured.
3. Establish responsibilities. Assign data roles: who owns what data? Who is allowed to make changes? And who monitors quality?
4. Implement data governance. Establish processes for data management and control, including policies for privacy, security and legislation such as the AVG.

Without a solid foundation, every data-driven initiative collapses sooner or later. Want to build a future-proof organization? Then start with the basics.

Pitfall 3: Without a data culture, it remains just pretty dashboards

Even with the best tools and reliable data, success is not a given. The biggest challenge? Culture. Do managers and employees dare to let go of their intuition and really trust data when making decisions? Or does it remain a nice dashboard that is hardly ever used?

Especially in management boards and boards of directors, intuition often stands in the way of data-driven decision-making - as my colleague Jeroen Kuijlen wrote in the blog "Your intuition stands in the way of data-driven decision-making. But similar beliefs are also prevalent in the workplace:

1. "We rely on experience, not numbers."
2. "This analysis probably isn't right - it doesn't fit with what we always do."
3. "The data is not complete or reliable anyway."
4. "That's how we've been doing it here for years."
5. "Not everything has to be measurable."

How do you break through this?

1. Make data-driven leadership visible. Use data actively in consultations and decision-making. Managers are role models, let them lead by example.
2. Create a "data-challenge culture. Make sure dashboards connect to real-world situations and encourage employees to question decisions critically - based on data.
3. Measure and reward data-driven behavior. Make visible where data makes a difference and value teams that use data effectively.
4. Include the human side. Culture change requires attention. Support the transition to data-driven work with proper guidance.

From data to action

Working data-driven is not an end in itself, but a means to operate smarter, faster and more effectively as a cooperative. By investing in a solid foundation, ownership from the business and a culture in which data is really used, you lay the foundation for sustainable impact. Especially for housing corporations this is necessary within the complex playing field. Valid already supports several housing associations and other organizations in the transition to data-driven operations.