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On August 17 at 3 pm ET, Sania Khan, SVP of Product & Strategic Innovation at Ellucian, will be live on this subreddit for 60 minutes answering your questions about student success technology, higher ed ERP, AI on the Ellucian platform, and where the product is headed.

Whether you're an admin, an IT lead, an implementation partner, or just someone who's never had a direct line to ask, this is your chance! We'll share the AMA link here when it goes live.

August 17, 2026 | 3 pm ET | r/Ellucian

This is different from the general "what makes migrations go well" question. Timeline specifically. Projects that deliver on time tend to share a few characteristics that projects running over don't, and they mostly come down to decisions made in the first 60 days of the project, not decisions made at go-live.

• Scope was defined and protected before configuration started. The single most common driver of schedule slippage in SIS projects is scope change during the configuration phase. Every "while we're at it" request costs time, and the cumulative effect of small scope additions can push a timeline by months. Institutions that lock scope formally and require a change request process for anything added after kickoff stay on schedule at a much higher rate than those that treat scope as flexible.
• Data readiness was assessed before the project started, not during. Data migration is typically on the critical path, and data quality problems found late in the project create cascading delays. Institutions that run data audits before contracting, or at least in the first month of the project, can make realistic timeline commitments. Institutions that discover data problems during migration testing are renegotiating timelines they already committed to.
• The governance structure had real decision-making authority. SIS projects touch enough departments that disagreements are inevitable. Projects with a steering committee that can make binding decisions quickly stay on schedule. Projects where every cross-departmental dispute escalates to a slow consensus process don't.
• Testing involved the people who do the actual work. UAT run exclusively by IT teams misses the functional edge cases that frontline staff in financial aid, the registrar's office, and advising know about. Involving those users in testing, with enough lead time to address what they find, prevents go-live surprises that extend timelines.

What decision early in a migration project do you think had the biggest impact on whether it stayed on schedule?

Higher education technology decisions rarely fail because the technology was wrong. They stall, get reversed, or underdeliver because of the conversations that happen inside the institution before, during, and after the decision.

A few situations that come up repeatedly in this community: the CFO who needs a financial justification that the technology team isn't positioned to build on its own. The faculty governance process that surfaces objections late in an evaluation that had been running for a year. The department that agrees to a shared system in a steering committee meeting and then builds a workaround the week after go-live. The president who endorsed a modernization initiative and then changed institutional priorities six months in.

These aren't edge cases. They're part of how technology decisions work in higher education, where governance is distributed, timelines are long, and the people accountable for technology outcomes often don't have direct authority over the stakeholders who determine whether adoption succeeds.

What's the hardest internal conversation your institution has navigated around a technology decision? Not looking for vendor critiques, more interested in the organizational dynamics and what you did or wish you'd done differently.

St. John's University ran a full institution-wide SaaS migration covering student, finance, HR, and financial aid systems under a project they called Project Genesis. Running all four value streams through a coordinated migration rather than a phased approach by system is less common, and the St. John's case is worth looking at because of how they managed the complexity.

A few things that came out of the project: system reliability improved measurably after the move, with fewer outages and faster recovery when issues did occur. The move to continuous SaaS updates removed the manual patching cycles that had been consuming IT staff time. Mobile-friendly experiences replaced interfaces that had been designed for desktop workflows in a different era, and support request volume dropped as staff adapted to systems that required less workaround.

The broader outcome the case study points to is one that comes up consistently in SaaS migrations: the value isn't just operational efficiency after go-live. It's the reduction of accumulated technical debt that had been limiting what the institution could do. On-premises systems that have been customized over years become harder to change, harder to integrate, and harder to support. The migration freed up capacity that had been going into maintenance.

Full customer story here: https://www.ellucian.com/resources/st-johns-university-modernizing-institutional-transformation

For institutions that are weighing whether to phase a migration or coordinate it, the St. John's approach is a useful reference point for how the coordinated path can be managed.

The "good enough" argument for legacy systems is genuinely hard to counter with feature comparisons, because the CFO is right that the current system does most of what it needs to do. The argument that tends to work is a risk and cost argument, not a capability argument.

A few framings that land better in budget conversations:

• Maintenance cost is not flat. On-premises systems get more expensive to maintain over time, not less. As the vendor shifts investment toward SaaS, on-premises support gets thinner. Custom integrations multiply. Staff who know the system retire or leave. The cost to keep the current system running in year eight is higher than the cost in year three, and the gap keeps widening.
• AI readiness requires a modern data foundation. If the institution has any interest in deploying AI-powered advising, retention analytics, or financial aid automation, those capabilities are significantly harder to build on a fragmented on-premises environment than on a unified SaaS platform. This isn't a theoretical future issue. Institutions that started SaaS migrations three years ago are now deploying AI features. Institutions that didn't are starting from a harder position.
• Third-party validation reduces approval risk. The Forrester Total Economic Impact study on Ellucian Colleague SaaS showed a 133% ROI for institutions that made the move. Ellucian also has a free ROI calculator at ellucian.com/value-calculator that produces institution-specific projections. Both are useful in a CFO conversation because they shift the framing from "this is what we want" to "this is what the numbers show."
• Peer examples close the argument. St. John's University and Excelsior University have both published case studies on their SaaS migrations. An institution that can point to peers in similar situations who made the move and got measurable results is making a different argument than one that's presenting projections alone.

Where is the SaaS modernization conversation stalling at your institution?

The standard approach to training during a technology implementation goes something like this: schedule sessions before go-live, walk staff through the new system, document the key workflows, and move on. The problem with that approach is that training retention drops off sharply when there's a gap between when people learn something and when they actually need to use it. By the time go-live arrives, a significant portion of what was covered is already gone.

Ellucian Academy's model addresses this through a combination of on-demand learning and role-based training timed closer to when staff will apply it. The distinction matters because the goal isn't just to cover the material. It's to build the kind of working confidence that means staff can handle edge cases, train colleagues informally, and troubleshoot without escalating every issue.

The broader argument in Ellucian's post on this topic is that training isn't a line item on an implementation checklist. It's what determines whether the investment in a new system actually produces the outcomes that justified the investment. An institution that deploys a modern SIS but has staff who are uncomfortable with it will get worse outcomes than it should, and will often misattribute the problem to the technology rather than the adoption.

A few things the post covers that are  worth knowing: how on-demand learning supports continuous adoption rather than one-time training events, how role-based training improves both speed and depth of adoption, and how institutions are using Academy to accelerate onboarding when staff turns over after a go-live.

You can read the full post here: https://www.ellucian.com/blog/how-ellucian-training-improves-student-experience

The FAFSA simplification changes reduced the number of questions on the application and streamlined the student-facing experience. That was the intent. The downstream effect for financial aid offices is that earlier FAFSA submissions and higher completion rates are generating more applications earlier in the cycle, which increases volume before institutions have necessarily expanded capacity to process it.

The operational pressure this creates is specific. Earlier submissions mean earlier expected processing times. Higher completion rates mean more files moving through verification workflows. More complex eligibility rules, which the simplification changes didn't reduce on the back end, mean more staff time per file on the cases that require human review. The combination is a meaningful increase in workload concentrated in the early part of the award cycle.

Ellucian published a breakdown of what the 2026 FAFSA data actually shows and what it means for aid office operations: https://www.ellucian.com/blog/fafsa-2026-data-financial-aid-offices

The post covers where institutions are finding the most operational pressure, what automation is doing to address verification triage and student communication, and what a digital-first aid office workflow looks like in practice. If your institution is still processing more of this manually than it should be, the timing argument for automation investments has gotten stronger.

Integration marketplace is a phrase that shows up in a lot of SIS and ERP vendor pitches right now. The presence of a marketplace is easy to verify. Whether it actually reduces integration work for your specific institution requires a more specific set of questions.

A few things worth asking before the marketplace becomes a decision factor:

• How many of the connectors cover systems you actually use? A marketplace with 200 integrations is only useful if the 200 includes the LMS, the identity provider, the payment processor, the CRM, and the other systems your institution runs. Ask for a list and cross-reference it against your current environment before assuming coverage.
• Who maintains the connectors when either system updates? Some marketplace integrations are community-contributed and maintained inconsistently. Others are vendor-maintained with defined SLAs. The difference matters a lot when a system update breaks a connection in the middle of a term.
• What does the implementation process actually look like? Pre-built doesn't always mean plug-and-play. Some marketplace connectors require significant configuration to map to your data model. Get a realistic estimate of implementation time from an institution that has done it, not from the vendor.
• What's the escalation path when something breaks? If a marketplace integration fails, it's worth knowing whether support goes to the SIS vendor, the third-party vendor, or somewhere in between. That answer determines your actual response time in a production incident.

The Ellucian Marketplace is a useful reference for what a mature higher ed integration library looks like. You can learn more about it here: https://www.ellucian.com/blog/ellucian-marketplace-pre-built-integrations-higher-education

What integration has been the hardest to maintain at your institution, and have you found a pre-built solution for it?

One of the consistently underestimated costs of technology modernization in higher ed isn't the system itself. It's getting the people who work in it every day back to full effectiveness after a major change.

The standard approach, train before go-live, document the key workflows, and move on, works well enough for the initial deployment. It tends to break down over time. Staff turn over. Systems get updated. New features roll out. A year after go-live, a meaningful share of users are working with a knowledge gap that wasn't there on day one, and the formal training infrastructure from the implementation has usually wound down by then.

A few approaches institutions are taking to address this.

• Building role-specific learning paths in an LMS or training platform that stay current with system updates
• Naming department-level super users who get early access to new feature training and are responsible for passing it along
• Using on-demand training resources rather than scheduled sessions so staff can learn when they have an actual question rather than when a session happens to be scheduled

None of those solve the problem entirely. Training close to go-live still gets forgotten without reinforcement. Super users leave. On-demand resources only work if people know they exist.

What has worked at your institution for keeping staff proficient after the initial go-live period? And where are the gaps that are still showing up?

Custom integration development is expensive, slow, and creates ongoing maintenance obligations. Every custom connector is something that has to be updated when either system changes, debugged when it breaks, and documented so the person who built it isn't the only one who can work on it. For higher education IT teams that are already stretched, this is a real operational cost, not just a one-time build expense.

The Ellucian Marketplace is a centralized library of pre-built integrations between Ellucian and third-party platforms commonly used across higher ed institutions. The value isn't just faster deployment, though that matters. It's that the maintenance obligation shifts away from your team. Pre-built connectors supported through a marketplace are updated and validated by the vendor when underlying systems change, which removes one of the more tedious and time-consuming parts of integration ownership.

The practical benefit for Banner and Colleague shops is that a lot of the point-to-point connections that institutions have historically built in-house, things like connections to payment processors, learning management systems, identity providers, and communication platforms, are already available as tested, documented integrations. That frees up development capacity for work that actually requires custom solutions.

Ellucian put together an overview of how the Marketplace works and what kinds of integrations are available: https://www.ellucian.com/blog/ellucian-marketplace-pre-built-integrations-higher-education

If you're evaluating what to keep building in-house versus what to pull from a marketplace, this is a useful reference for what's already there.

Configuration, data migration, integrations, and testing usually receive the most planning and budget. But the biggest risks often show up earlier, when project teams, business stakeholders, and end users aren't working from the same expectations.

Ellucian published a post on what the partnership between Project Managers, Solution Architects, and Change Managers actually looks like in a well-run implementation. The framing is worth understanding even if you've been through migrations before, because the specific division of responsibility between those three roles is where a lot of institutions have structural gaps.

The post uses Prosci's change management framework as a reference point, which is useful because it gives language to something that often stays informal: how you communicate what's changing, to whom, and when. That communication architecture, not the go-live checklist, is what determines whether staff actually use what you build.

A few things the post covers that tend to get underestimated: the role of the Solution Architect in reducing ambiguity early so change managers aren't managing confusion that should have been resolved in the design phase, how structured planning at the front of a project reduces the cost of mid-project corrections, and why user adoption should be measured and managed from the start rather than treated as a post-launch concern.

Full post here: https://www.ellucian.com/blog/alignment-advantage-people-centered-saas-implementation

Advising gets a lot of attention. Early alert systems get a lot of attention. Academic planning, the actual structure of how students understand what they need to take, in what order, and by when, tends to get less. That gap shows up in outcomes.

The research is consistent: students who have a clear academic plan and check it regularly are more likely to persist, more likely to graduate on time, and less likely to get blindsided by a requirement they missed until it was too late. The mechanism is simple. A student who knows what comes next can make better decisions about course selection, work schedules, and when to ask for help. A student navigating an opaque degree map is guessing.

Three habits show up consistently in students who use academic planning well. First, understanding the actual course sequence, not just the degree requirements listed in a catalog, but the order those courses have to be taken given prerequisites, availability, and major-specific constraints. Second, tracking progress against graduation benchmarks on a regular cadence rather than only at registration time. Third, building in monthly check-ins for deadlines and grades so nothing accumulates into a crisis.

The technology side of this matters because it determines whether these habits are even possible at scale. A degree planning tool that surfaces real-time progress, flags prerequisite conflicts, and connects to advising creates the conditions for these habits to form. A static PDF checklist doesn't.

Ellucian put together a piece on what this looks like from the student side, worth passing along to advising and student success teams: https://www.ellucian.com/blog/planning-matters-staying-track-graduation

What's your institution doing to close the gap between degree requirements and students actually understanding their path to graduation?