Exploring technology and data systems consolidation in higher ed

Addressing the challenges of consolidating technology and data systems in higher education is an...

Addressing the challenges of consolidating technology and data systems in higher education is an ever-evolving and complex topic - especially as the pace of technology increases. Integrating various technology solutions and ensuring interoperability is complex, and the larger the institution, the more complex interoperability is. 

Within integrations, colleges and universities typically deal with any, all, or a combination of these seven challenges:

Diverse systems

Higher education institutions often have a variety of technology systems in place, including student information systems, learning management systems, financial systems, and more. Integrating these diverse systems can be challenging due to differences in data formats, standards, and technologies.

The prospect of pulling any or all of these systems together into one cohesive working solution is a complex and time-consuming task. And having the necessary staff and in-house expertise to execute it well is another challenge altogether. 

Diverse systems create too much siloed data and disparate reporting and analytics, which blunts decision-making for deans and university leadership. The colleges and programs within the universities are often already siloed enough, limiting opportunities to share resources and collaborate on strategies to meet institutions’ overarching goals. 

Getting these systems corralled into a central platform is ideal, even when faced with the daunting task of reviewing them to determine how to integrate them. 

Legacy systems

Many institutions have legacy systems developed years ago - often from companies who are not innovating their current solution and don’t have much interoperability with other systems. Integrating these with newer, more modern systems can be difficult due to compatibility issues and the need to preserve existing data.

Data migration from these sorts of systems often requires a custom solution to get it into a more modern platform. Not every legacy system is built the same, and data standards can fluctuate.

Data silos

Data is often stored in separate silos across different departments. Integrating these silos can be challenging as it requires breaking down barriers and implementing a unified data strategy. This involves many team members, a thorough forensic assessment of the data, and prioritizing which data silos can be more easily overcome than others. 

Some of the data silos breaking can be a months long endeavor depending on how normalized the data is and what leadership is wanting to integrate that data with.

Data costs money. In order for colleges to have an edge in courting new students and making the student experience enjoyable and effective, data silos must become less of a barrier to the school. 

The end goal of embracing big data is for deans and university leaders to truly be data-driven — that is, to benefit from data in a consistent, university-wide manner. But so few can build a suitable infrastructure from scratch, so the burden becomes figuring out a way to get there in an incremental way.


Institutions often require customization of their systems to meet specific needs. Integrating customized systems can be more complex as it requires careful consideration of how these customizations interact with other integrated systems.

Interoperability becomes another challenge when facing all these different systems and having to make them talk to one another in a lucid manner. 

Data standards

Different systems might use different data standards and formats. Establishing common data standards can facilitate interoperability by ensuring that data can be easily shared and understood across systems.

This is normally something difficult to police in an environment where tens of different schools are functioning within a university environment, and not all staff are savvy in using technology appropriately.

This can create a heavy burden on the data and analytics team to ingest data and standardize it for large-scale analysis. But data standards, which creates data hygiene, is how an initiative like technology consolidation and data systems works.

APIs and middleware

Application Programming Interfaces (APIs) and middleware can act as bridges between different systems. Ensuring that these APIs are well-documented, secure, and capable of handling the necessary data flows is essential for interoperability.

When using disparate systems, APIs can be inconsistent. Not every technology tool has a robust API system, nor does it have a fast enough middleware system to port data quickly or accurately enough across systems. 

Data mapping and transformation: 

When integrating systems, data often needs to be mapped and transformed from one format to another. This can lead to data loss or inaccuracies if not handled carefully. 

This especially is problematic when like-data is arrayed differently, like when a class size in one system has a range of 1-15 and the other a range of 1-25, or when data collection is qualitative in nature and has to be aggregated in order to be usable. 

The process of normalizing these kinds of data challenges is a huge task requiring special migration skills, data lakes, BI tools, and coding. Not every college nor software partner is equipped to handle this kind of project, and oftentimes, it requires a third-party partnership in order to facilitate doing this effectively.

Benefits of consolidating tech systems

Streamlined operations

A centralized platform can provide a single point of access for various functions like student records, preceptor records, and student evaluations. Users can have a holistic view of administrative processes, which can lead to more efficient decision-making.

Data-driven decisions

Centralized platforms often offer robust reporting and analytics capabilities with real-time data on student performance, program outcomes, and resource utilization, enabling data-driven decision-making to improve academic programs.

Enhanced collaboration 

Centralized platforms foster collaboration among different departments and colleges within the institution. This helps facilitate cross-disciplinary initiatives, share resources, and coordinate efforts more effectively.

Consistent student experience 

Centralized platforms can lead to a more consistent student experience across different departments and programs. 

Improved resource allocation 

With better visibility into resource utilization, universities can allocate resources more strategically. This can include faculty assignments, funding allocation, and facility management.

Drawbacks and risks

Complex implementation 

Implementing a centralized platform can be a complex and time-consuming process, considering the potential disruption during the transition period and ensuring that staff and faculty are adequately trained.

Resistance to change 

Staff and faculty might resist the change due to new workflows and processes.  It's important to manage the change effectively and provide support to mitigate resistance.

Vendor reliability 

Dependence on a single platform vendor can create risks if the vendor experiences technical issues or discontinues support. Ed tech decision makers should assess the vendor's reputation, longevity, and commitment to ongoing updates and support.

Customization challenges 

Some centralized platforms might not fully meet the specific needs of individual departments or colleges. It's vital to assess the level of customization available and the platform's flexibility to accommodate unique requirements.

Factors to consider when vetting vendors


Can the technology accommodate the institution's growth and changing needs over time? 

You will want to get a hold of use cases, talk to current and similar clients, and get information from them about how they scale with their customers. Have people in the room - your CIO, your IT leaders, and your DevOps personnel, to vet the answers and ascertain whether they are suitable.


Does the platform integrate well with existing systems and data sources?

Initially, any centralized platform will need to port into other systems and extract the data. Whether they port into a data lake or the technology itself is a question and strategic decision to make with both the implementation team at the university and the vendor. 

User-friendly interface 

Is the platform intuitive for both staff and students to use?

This is where it’s crucial to get stakeholders feedback. Key faculty and members of student leadership need to be involved in order to get feedback on the user-friendliness of any centralized tool like this. It has to be viable and agreeable at the faculty and student level in order for it to be viable at the leadership level.

Data security 

How does the platform ensure data security and compliance with relevant regulations?

HECVAT assessments and SOC2 compliance, among other factors, are key here. Any history of breaches, what cybersecurity tools they use to protect the platform (firewalls, threat intelligence, etc.), and how much staff they dedicate to things like threat remediation and vulnerability management are key items to know and be comfortable with.

Support and training 

Does the vendor provide comprehensive support and training during and after implementation?

You also will want to understand ongoing training and support and how that cost is factored into the cost of the platform. 

Ideally, you will be a champion user within your key stakeholder group who is proficient in the platform, works out of it almost exclusively, and can facilitate training needs when required.

Long-Term viability 

What's the vendor's track record and financial stability? Is the platform likely to be supported in the long run?

Get information about their customer base, funding, runway, churn rate, etc. These can be difficult things to extract during the sales process, but once you get to a negotiation, as you whittle down to just a couple of vendors, this can be distinguishing information to know and have.


Can the platform be customized to accommodate the unique requirements of different departments?

Every department will prioritize usage and data differently. Knowing your centralized system has the flexibility to support those needs is something you will want to be proven by a Proof of Concept with the vendor. These types of pilots are very similar to what manner cybersecurity tools do to prove their systems work and create a tangible benefit. Given the time and cost expenditure at stake here, it wouldn’t be out of the ordinary to request a similar arrangement.


Consider the upfront costs, ongoing maintenance fees, and potential hidden costs.

Cost matters, of course, and ROI isn’t also something that is super tangible. Determine what the factors of success will be for the university and weigh this against any cost. In terms of hidden costs, make sure you understand the upcharges, if applicable, for things like new users, a growing student body, server load, etc. 

A lot of these variables impact the bandwidth of the vendor, and you will want to understand the cost variables at play.

You also will want to know their pricing history and whether you would be impacted by a change in their pricing. Have language in the contract that can grandfather you in, if possible.

Consolidating technology systems offers numerous benefits for universities in terms of streamlined operations, data-driven decision-making, and enhanced collaboration. 

However, they also come with potential drawbacks and risks that need to be carefully considered. When evaluating options, focus on factors such as scalability, integration, data security, support, customization, and long-term viability to make informed decisions.

CORE Higher Ed Team


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