Data Health and Integration Fundamentals for Foundations

In a recent letter to the editor published in The Chronicle of Philanthropy, two former foundation officials decried the ‘staggering’ redirection of charitable dollars for ‘bloated foundation staff’ and administrative expenses.  Of course, most community and independent foundations operate with lean staffs and can’t (and wouldn’t) repurpose donor intent.  But it stands to reason that foundations’ leadership will still continue to leverage operational efficiencies and generate cogent reporting from a ‘single source of truth’ to ensure that charitable dollars are used as intended.

Foundations can proactively jump on this bandwagon by better using technology to support their business activities and, by extension, to further their vision and mission.  And, as foundations take better advantage of technology, effective data management becomes not only advantageous but downright essential.

Effective data management will certainly bolster operational efficiencies on the one hand and comprehensive reporting on the other. To a great extent, this is predicated on three interdependent pillars, all of which can be strengthened by the right nonprofit-specific technology:

• Data health
• Data integration
• A data ‘system of record’ designed to serve as a foundation’s single source of truth

What is Data Health?

While data health at the most basic level is understood by most foundation professionals – e.g., donors’ and grant applicants’ contact information have to be free of errors, amounts and dates have to be accurate – there’s more to data health than error remediation. If the pandemic has taught us one thing, it’s that staying healthy is more about preventing illness than it is about curing illness. The same is true for data. Healthy data is more about prevention than about correction. We look at data health along three key dimensions:

• Currency
• Cleanliness
• Completeness

Current data are fresh data. The currency of a foundation’s data will inform how it’s perceived by all stakeholders, including grant recipients.  For community foundations, this means that contributions need to be recorded in a timely fashion so that so that donors are thanked expediently and fund balances are up to date.  Distributions should be recorded in a timely fashion for the same reason. For independent foundations (and most community foundations as well), investment income and asset revaluation need to be reflected expediently, so that fund managers have the information they need to do their jobs.  This becomes a much more challenging issue when this information resides in online applications and then needs to be reentered or otherwise transmitted to your main CRM and/or finance system.  If that process is broken or delayed, data in the system of record may rarely, if ever, be current.

Clean data support your foundation’s credibility, but unhygienic data can depreciate it just as easily.  This includes everything from erroneous biographical and mailing information, to duplicate donor or applicant records, to names and addresses with improper casing (e.g., scarlet oneill rather than Scarlet O’Neill).  As a baseline, biographical and mailing data should be accurate.  Names and addresses should be spelled properly.  Incorrect email addresses will certainly bounce back.  With more and more biographical data coming into main systems from external online sources, very often it’s the grant applicants or donors themselves who unintentionally mistype their own information:  when entering it into an online form or when updating their contact information online.

Complete data tell a complete story of – and to – your foundation’s stakeholders.  When data are maintained in different siloes, such as various online portals, nobody at the foundation will have a complete picture applicants, donors, or advisors.  By effectively consolidating data from various source systems into a single unified system of record, those across the foundation will be afforded a comprehensive, thorough picture of every stakeholder. Wouldn’t you want to know that a scholarship applicant is somehow connected to fund advisor? Or that the executive director of grant-recipient agency is she, herself a DAF donor? Of course you would.

What is Data Integration?

Data integration is the process that consolidates data from different sources into a unified and cohesive information system, typically your main system of record.  Foundations today have a great need for data integration.  This is because, more and more, software applications are deployed that support one particular aspect of Foundation operations very well but weren’t necessarily designed to transmit data to (or collect it from) larger, centralized information systems on which all foundation stakeholders depend.

This technology concept is known as ‘best-of-breed’ and postulates that while the backbone of the organization’s data repository is its main system, certain satellite applications generally provide a better solution for certain key business needs, with richer functionality, and a better user experience both for the foundation team and its stakeholders (applicants, fund managers, awardees, donors, leadership, etc.). That can often lead to not one, but several repositories of relevant data spread across the organization.

Historically, data integration was done manually, ie, by keying data into database forms or batches.  An integration solution is a technical, computer-based platform or application that automates the various components of the data consolidation process (or processes).  Many contemporary integration solutions leverage application programming interfaces (‘APIs’) that further automate data-mapping and the exchange of data between naturally corresponding locations within the source and destination systems.

Sometimes end-users think that an import tool is the same as an integration solution.  Technically, importing data is only one part of true integration. A comprehensive integration solution consumes information from a data source and might standardize it, correct it, and/or transform it before mapping it to the corresponding destination fields.  It might create different record types in the destination depending upon the source data.  It might score and match incoming records against existing records so that duplicates are not created. Finally, using those APIs discussed above, an integration solution is able to actually connect the source system to the destination system so that data can be exchanged directly – eliminating the need for data files and manual intervention (although some aspect of human monitoring and control is always recommended).

Suffice it to say that importing is useful – saves time and effort – but a true integration solution is ‘smarter,’ built to be more intuitive, and will result in current, clean, and complete data flowing on demand between all applicable systems that are part of a foundation’s overall data ecosystem.

How Does Data Integration Support Data Health?

Data integration can directly support data health, but not in a vacuum or on its own.  Rather, it has to be part of data health strategy that includes human decision-making and sensible focus on which data from which systems need to be integrated, and in which directions. The technology does the ‘heavy lifting’, and addresses reducing effort and inefficiency, but foundation professionals still need to be responsible for identifying which data need to be integrated, how often, and who is accountable overall.

That said, data integration technology supports data health in several ways, all generally focused on data and systems becoming and remaining current, clean, and complete:

• Automation means that data get exchanged routinely and quickly, so that information remains fresh and up-to-date. For community foundations that process gifts to donor-advised as well as community-focused funds, this means that both balances are current and donors can be stewarded expediently. But the same is true for applicant data, award data, and, perhaps especially, disbursement data. If satellite online portals are capturing this information initially, automated integration will ensure that a foundation’s main CRM and/or financial systems are as current as possible.
• Standardization features ensure that data remain clean and accurate – that donor, applicant, and awardee contact information is properly spelled, properly cased, and complies with your data requirements. As stated above, data standardization and transformation address a multitude of errors that stakeholders enter themselves in online forms.
• Sophisticated data matching algorithms ensure that records being integrated from one system don’t create duplicate records in another (e.g., proper integration can ensure that duplicate records aren’t created when importing new gift or application data from existing stakeholders).
• A common integration platform serves as a hub and facilitates the integration of data from the variety of a foundation’s best-of-breed applications, so that your main system(s) are complete and provide the proper ‘360-degree view’ for all stakeholders – internal and external.

Technology can play a crucial role in foundation operations, especially during times where increased scrutiny, accountability for lean efficient staffing, and the demand for timely reporting are front and center. Data heath and integration technology in particular can effectively work for you at the intersection where information and foundation operations don’t collide, but rather, support each other and allow you to accomplish your mission with more impact.

Read Part Two: Operational Imperatives for Foundations. The second part of this two-part series on data health and integration for foundations examines foundations’ main operational data flows. This article focuses on the most important integrations for foundations, how integrated data can be leveraged, and how quality data enhances the long-term stakeholder experience.