How a leading university took ownership of its implementation projects.

A high governance bar the team wasn't willing to compromise

The team's priority was keeping critical alumni data moving reliably between systems while holding to strict governance standards, and they wanted integrations that lived up to both.

Their existing integration platform gave them the controls they valued: separate sandbox, UAT, and production environments, auditability, and stakeholder visibility. Operating it, though, called for specialized technical expertise, so each change ran through the development team.

That made each workflow update and new implementation a developer-led effort, with larger projects running for weeks or months. The team wanted to move faster while keeping every one of those controls in place.

In short: they wanted to implement and maintain these workflows themselves, without giving up an ounce of governance.

The same operating model, owned by the team

Using superglue, the team rebuilt its alumni data workflows while preserving the operating model required by the institution.

• Business users became implementation owners. Instead of writing connector code, the team defined the desired workflow and data movement. superglue handled connectivity, authentication, transformations, and system-specific logic across its CRM, fundraising platform, on-premises database, and file shares. Work that previously required developer intervention could now be implemented and maintained by the broader team.
• Governance stayed intact. The team maintained separate sandbox, UAT, and production environments, each with isolated credentials and controls. Changes could be tested safely before promotion, ensuring production data remained protected throughout the implementation process.
• Stakeholders gained visibility without risk. Admins, builders, and read-only stakeholders each received access aligned with their responsibilities. Read-only users could monitor implementations and review results without the ability to modify workflows or data.
• Every implementation became auditable. Each workflow execution records the exact configuration that produced it. Teams can review changes, compare versions, identify the source of issues, and restore previous configurations when needed.
• Safe deployment became standard. Changes are validated before promotion, with clear diffs showing exactly what will change between environments. Implementations move from testing to production through a controlled review process rather than manual deployment steps.

• New workflow implementations that previously took months now take days.
• The broader team can implement and maintain data workflows without relying on developers.
• Governance requirements were preserved without compromise.
• Every change is traceable, reviewable, and reversible.
• Critical data operations became faster to deliver and easier to maintain.

A repeatable way to own critical data processes

The university transformed how it delivers data initiatives. Instead of treating every new workflow as a technical integration project, the team now has a repeatable way to implement, operate, and evolve critical data processes themselves. The result is faster execution, lower dependency on engineering resources, and a foundation that scales as new systems and requirements emerge.