Data Analytics

How Nonprofits Can Achieve a Data Center of Excellence

A strong data strategy is nonnegotiable. Here’s why.

J.P. Pressley is a contributing writer to BizTech magazine and an editor at Manifest.

A Florida-based nonprofit had seven business functions that stored information across myriad siloed systems, resulting in data challenges that negatively impacted productivity and budgets. Specifically, it hampered job-related activities for over 1,000 employees across more than 20 locations, while simultaneously piling up monthly charges and colocation fees.

Fortunately, the nonprofit’s IT team was able to work with CDW to find a customer relationship management system that was not only compatible with its Amazon Web Services platform but also could also integrate with its AWS-hosted advanced analytics platform. With the implementation, the organization gained one cloud-based solution that all operational functions could access at any location or on any mobile field device.

The result? A completely transformed data environment at a fraction of the cost of the original one. Here are a few best practices for cultivating data excellence in your organization.

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The Foundations of a Nonprofit Data Strategy

Today, nonprofits of all shapes and sizes are collecting large amounts of raw data. Data strategy is about determining what you’ll do with this data, how you will do it and why.

A good data strategy has two key aspects: The first is data governance and security. Nonprofits handle sensitive data, such as donor information and financial records, so the strategy must include clear, ethical policies for data privacy and access control, and it must be compliant with regulations such as the General Data Protection Regulation or HIPAA.

The second aspect is data integration. Nonprofits often use multiple platforms for fundraising, volunteer management and outreach. A good data strategy should focus on integrating these systems, ensuring data is centralized and easily accessible for decision-making, reporting and improving operational efficiency. This approach enables better insights and program outcomes.

EXPLORE: Nonprofit technology solutions that can expand your organization’s impact.

Preparing Your Data for Analysis and Generative AI Applications

Once all of the data is captured, IT leaders need to classify it and clean it ahead of further analysis or its use in any AI applications. AI and machine learning only work if the data is of high quality. “Garbage in, garbage out,” writes Simon Jelley, general manager for SaaS protection, at Veritas Technologies, in Forbes.

Skipping this step can have serious repercussions. “The storage giant Seagate estimates that organizations capture just 56% of the potentially valuable data they create,” Jelley continues. “And recent research commissioned by my company found that 77% of the data organizations capture is either redundant, obsolete or trivial (ROT), or altogether unclassified. That leaves only 23% ‘good’ data out of the already relatively small amount being captured for your AI-driven business processes to train on.”

In short, the cleaner the data, the more IT leaders can trust their insights and make decisions with confidence.

Best Practices for Cultivating Data Excellence

The right data strategy will lead to a modern data ecosystem, good data governance and a robust data culture — the three pillars of data excellence. Here are a few ways nonprofit IT leaders can get there:

Conduct a comprehensive data audit. This will help pinpoint the sources, locations, and current uses of data. Evaluating data usage can also help IT leaders prioritize initiatives that have the greatest positive impact, such as improving donor engagement or measuring the effectiveness of programs.
Develop clear data governance policies. Define who owns the data, who has access and how it will be secured. Document and communicate these policies across the organization to ensure the data’s trustworthiness and consistency.
Partner with data experts. Seek out expert guidance or consider managed service providers who can help optimize and streamline your data transformation efforts.
Invest in staff training. To create a culture of data-driven decision-making, it’s essential that nonprofit staff members routinely upgrade their data skills through ongoing training.
Allocate a budget for ongoing maintenance. It’s crucial to plan not only for the initial data transformation but also for continuous maintenance and updates. After all, data management is an ongoing process.