Please don't do your census or large customer surveys before you've read this!

The Importance of Forward Planning in Census Data Integration for Cx Housing System

Introduction

Census data collection within housing associations is essential for understanding tenant demographics, improving service delivery, and ensuring compliance with regulatory requirements. However, too often, the surveys are collected and passed over to someone to load in to a system with no involvement to data and the task of unravelled the ball of wool begins!

Get it wrong, and it leads to data inconsistencies, technical roadblocks, and even legal complications. Don't plan, and the effort and time waste is collosal.

This article is directed at those involved in the process, emphasizing the need for a structured approach when handling census data. We explore the risks of poor planning, the importance of proof of concept testing, and key considerations for successful data integration into Cx Housing System.

The Challenges of Census Data Integration

1. Poorly Designed Census Questions

One of the first hurdles in census data integration is the quality of the data collected. Poorly designed questions lead to data that is difficult to interpret and integrate. For example:

• Ambiguous or irrelevant questions – What does the organization plan to do with the data? If there's no clear business purpose, should it be collected at all?

• Lack of standardization – Free-text responses in fields meant for numerical data (e.g., age, income) can result in unusable entries.

• Incorrect or missing lookup values – If the new system lacks corresponding lookup values for responses, data must be mapped or discarded.

2. Unclear Data Update Policies

Once data is collected, what should actually be updated? Some key considerations include:

• Updating Names: If the census data contains a name change, do you overwrite the existing name? If the tenant’s agreement is in another name, should legal documents be updated?

• Title Changes: In Cx, the title field shares the same row as the name field. If a title is changed, should the existing name remain unchanged or be updated as well?

• Handling New Records: Should new tenants be created from census responses? How do you ensure duplicate records are not introduced?

3. Technical Considerations for Data Loading

Data can be imported broadly via 2 main routes

• Direct SQL Injection – While quicker, this method can lead to incomplete updates. For example, if updating a Name field, should you also update SearchName?

• Web Services API – More rigorous but requires extensive testing. API-based imports may enforce validation rules, ensuring better data integrity.

4. Dependencies and Data Consistency

• Does updating the FormattedName automatically update FormattedResponsibleNames?

• If tenants move between properties, does historical census data remain tied to the previous address?

• Are date fields properly formatted to prevent errors in future queries and reports?

The Importance of a Proof of Concept (PoC)

Proof of concepts are amazing! Doesn't matter how clunky it is, you just need to try and simulate the process end to end. Not end to 'nearly-the-end'...but end to end.

A PoC allows teams to:

• Test the Import Process: Can the data be loaded correctly without errors?

• Refine the Questions: If responses are ambiguous or problematic, they can be adjusted before full deployment.

• Validate System Fields: Ensuring lookups exist and data aligns with the system’s constraints.

• Minimize Legal and Compliance Risks: By testing in a controlled environment, data integrity is preserved.

Steps to a Successful Proof of Concept

1. Define the Scope and Objectives

Before loading any data, clearly define:

• What data will be updated?

• What records will be created?

• What existing data should remain untouched?

2. Prepare a Sample Dataset

Take a subset of census responses and simulate the import. Identify potential data conflicts and correct them early.

3. Validate Data Before Import

• Standardize fields (e.g., proper case formatting, correct numerical values)

• Identify and handle missing or incorrect values

• Ensure lookup values exist in Cx

4. Perform a Test Import

Load data into a test environment first. Evaluate:

• Were names updated correctly?

• Were dependent fields (e.g., FormattedResponsibleNames) updated automatically?

• Were new records created correctly?

5. Review and Adjust

After the test import, analyze the results:

• Were there unintended changes?

• Were any critical fields missed?

• Are there formatting inconsistencies?

If issues are found, reword or restructure census questions to improve clarity before proceeding with a full integration.

Choosing the Right Data Import Method

While SQL injection is often seen as the quick solution, it carries risks. If used, additional validation scripts should be written to confirm dependent fields are correctly updated.

Final Recommendations

For a smooth and efficient census data integration into Cx Housing Systems:

1. Plan Ahead – Before collecting census data, ensure questions are meaningful and structured correctly.

2. Test Before Deployment – A PoC helps catch issues early and prevents costly mistakes.

3. Choose the Right Import Method – Web services APIs offer better data integrity but require additional effort.

4. Consider Dependencies – Ensure that updates to key fields also reflect in related system tables.

5. Ensure Legal and Compliance Alignment – Be mindful of agreements and legal documents before updating names and tenant records.

By investing time in careful planning and testing, housing associations can prevent errors, maintain data integrity, and ensure the census data serves its intended purpose effectively.

Conclusion

Census data is a valuable asset for housing associations, but without careful planning and structured integration, it can create more problems than solutions. By adopting a methodical approach, housing managers, IT teams, and system administrators can ensure that data is not only accurate and useful but also legally compliant and system-friendly.

Taking the time to proof the process before full implementation will save significant time, effort, and frustration in the long run.

If you're stuck on where to begin, give me a shout.