Streamlining Success: A Guide to Nonprofit Data Cleanup

Rashida A. Brown

Senior Consultant

Rashida has worked exclusively with nonprofit organizations for over 20 years on improving the use of their technology, on projects including CRM implementation, business analysis, business process workflow development, and more.
October 17, 2023

Data is a valuable resource for nonprofit organizations. It drives decision-making, donor relations, and program effectiveness. However, maintaining clean and accurate data can be a daunting task for many organizations. Over time, data can become cluttered, inconsistent, and riddled with errors, making it challenging to leverage this information effectively. In this blog post, we will explore the importance of data cleanup for nonprofits and provide a guide on how to streamline your data for better outcomes.

Why Data Cleanup Matters

  • Improved Decision-Making: Clean data ensures that your organization is making informed decisions based on accurate and up-to-date information. This leads to better resource allocation and program planning.
  • Enhanced Donor Relations: Accurate donor records and communication history are vital for building strong donor relationships. Clean data helps you personalize interactions and engage donors more effectively.
  • Efficient Fundraising: Accurate data helps you identify potential donors, understand donor behavior, and tailor fundraising campaigns to specific audiences. It also reduces the risk of sending duplicate appeals or outdated information.
  • Resource Optimization: By eliminating duplicate and irrelevant data, your organization can save time, reduce costs and liability, and operate more efficiently.

 Nonprofit Data Cleanup Starter Kit

Audit Your Data:

Start by conducting a comprehensive audit of your data. This helps you examine the overall health of your organization’s data. When conducting a data audit, common issues to look for are:

  • Repetitive code values: Codes that serve the same purpose. These can be confusing for data entry staff and cause export/analysis frustrations. For example, the codes for phone type can include both “Work” and “Business” and may be hard for data entry staff to interpret how to code a constituent’s employment phone number.
  • Improper use of fields: Code values that do not belong within the associated field and should be located elsewhere in the database. For example, constituent attributes that include solicit code or attendance data.
  • Mixed-use code values: Code values within the same field that have different purposes. This can make it challenging for staff to easily analyze, report on or convert data.
  • Data entry errors: Code values created by mistake, typically due to data keying errors or duplicative codes.
  • Missing code values from records: Records that do not have a code value associated with them.
  • Codes that are no longer relevant: Codes that may reflect strategies of earlier users or programs, but lack purpose, value or meaning to current users or the organization’s current overall strategy.

Implement Audit Findings

Once you’ve completed your data audit, you’ll want to tackle issues gleaned from that deep dive into your system. Common recommendations include:

  • Data Standardization: Create clear guidelines for data entry, ensuring consistency in formatting, abbreviations, and categorizations. Documented policies and procedures around basic record management can serve as a reference tool for users. Consistent, clean data results from a shared understanding among users on how data is entered, used, managed, and maintained.
  • Data De-duplication: Use your system’s data de-duplication tools or manual checks to identify and merge or inactivate duplicate records. Establish system business rules that alert users to the possible creation of a duplicate record. Reducing the number of duplicate records prevents sending multiple communications to the same donor and improves data accuracy.
  • Regular Maintenance: Data cleanup is an ongoing process. Establish audit queries and reports that can be run and reviewed on a regular basis. Assign responsibility for data maintenance. This could be a dedicated data manager/administrator or a staff member with data management responsibilities. This will ensure data quality over time.
  • Training and Documentation: Once an audit is conducted, identifying error prone areas where users may need additional training is key to reducing future errors. Regularly train staff and volunteers responsible for data entry and maintenance to keep them updated on policies and procedures. Create clear documentation and guidelines to ensure consistent data practices. Documented procedures should outline all required fields, active code values and the protocols for usage.
  • Data Governance: Establishing a data governance framework can help align your data strategically to your organization’s mission and objectives.

Effective data cleanup is a vital aspect of nonprofit management. It empowers your organization to make data-driven decisions, strengthen donor relationships, and optimize resource allocation. By following the steps outlined in this guide to nonprofit data cleanup and adopting a proactive approach to data management, your organization can harness the full potential of clean and accurate data. Remember, data cleanup is an ongoing process that pays dividends in the long run, ultimately leading to greater impact and success in your mission.

Jumpstart Your Data Audit

Optimization of your CRM starts with organizing your data coding structure. Our Codes Frequency Report (CFR) automates auditing your CRM. The CFR identifies and counts every code value used within your existing system, revealing which codes can be deleted, consolidated, or cleansed. Work with one of our expert consultants on spot cleaning your data.

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