The Business Intelligence Engine Fueling Higher Ed Today

In a budget-challenged higher ed sector marked by fierce competition to survive, Business Intelligence (BI) has never been more critical to institutional success. In fact, analysis missteps are something few can afford today. A shrinking student pool driven by demographic shifts and increasing applicant scrutiny surrounding college degree value, coupled with an accelerating volume of college closures in recent years make BI-informed decision-making a mission-critical directive.

If the macro-environment threats du jour plaguing the sector weren’t enough, operational data collection and analysis challenges also abound for those sourcing the peripheral technology, translating the raw data, and innovating the solutions. Conversion, consolidation and examination of increasingly large volumes of data also represent their own challenges which can be detrimental to an institution’s performance and longevity. Keeping pace to remain responsive and competitive requires decision-makers to have full visibility to nuanced BI challenges, emerging technology trends and valuable cost-saving hacks.

Key business intelligence challenges

To craft a solid framework for success, its necessary to first understand the full depth of BI challenges. Chief among them are:

Unwieldy data volume

While no shortage of seemingly useful data exists in the higher ed space, data management remains a tall order. Most of the world has failed to fully harness the value of Big Data, and the higher ed space is no exception.

“An enormous amount of data exists in higher ed,” says academic IT and information system veteran, and Trinity University Chief Information Officer, Jim Bradley. He reports that data is commonly stratified across a number of mediums in higher ed, with no clear enterprise software winner to manage and distill meaningful insight from it. “There are almost limitless ways to store data in a university environment across a number of platform combinations. Core institutional intelligence, student information, HR data, and college departmental content can be stored across a number of systems, spanning enterprise resource planning systems with a variable number of functional software modules, student information systems, PeopleSoft, Jenzabar and others. Add to that intelligence heap the large volumes of institutional paper data that has always existed. When the highest goal of the university is assembling actionable intelligence to drive student success, the question quickly becomes ‘how do you extract meaning from the collective?’” 

Beyond data volume hurdles, data consistency is also an issue. “Normalizing the data is a real challenge,” adds Bradley. “If you have 50 years of data, a lot of change has happened over that time. Clear differences in what is being measured, and variances in format and reporting periods adversely impact data utility for comparison to present day benchmarks.”

Limited access

Next challenge: the widespread lack of centralized databases and analytic dashboards making both standard and custom reports inaccessible to many university department leaders. The absence of this vital intelligence often leads to time sensitive financial decisions made in the dark on gut instinct alone.

“I’m a big fan of automated reporting systems that leverage real-time data,” says Assistant Director of Institutional Research at TCS Education System, Sibali Dutta. A central contributor to the successful launch of an automated reporting system designed for the University of Nebraska, Lincoln, she speaks from experience. “Without centralized data access and comprehensive platform training, time sensitive decisions are often made in a vacuum. Institutions should empower key individuals at every layer of the organization to access the critical information they need through centralized resources at the moment they need it to make decisions. For some institutions this access and training can be the difference between identifying a time sensitive budget cut imperative in the middle of the night and financial calamity.”

Inadequate speed

Another BI woe? The ever-present challenge of extracting meaning from large scale data in a timely manner. While emerging technologies are making headway to accelerate the speed of data-driven decision making, the road is long.

“Today the challenge is not a shortage of data, it’s efficiently leveraging it to be successful,” says Kathy Walsh, Greenlake & Pointnext Services Partner Manager at HP Enterprise Solutions in Chicago. “Moving at light speed to fully leverage all the data available today is really a tough thing. From opt-in surveys to tracked online user behavior from mobile devices – large volumes of data are consistently being collected and stored everywhere. But here’s the reality: Few companies know how to effectively analyze and benefit from it. Even though everyone is scrambling to move with speed and leverage the data, the lion’s share of collected intelligence isn’t being used.”

Seemingly prohibitive cost

The cost of institutional research technology and talent can be substantial. That said, each yield actionable data with discreet returns in the form of more strategic academic programming, increased graduation rates and vast reductions in student loan default rates. They are a non-negotiable cost of institutional sustainability.

Infrastructure obsolescence can be another cost, reveals Walsh. “No matter the sector, technology becomes dated, and can be a cost prohibitive proposition for many institutions. Not unlike purchasing a car, the moment you drive it off the lot – equipment loses value and almost becomes obsolete. While inventive solutions are emerging in response to this, that’s a real institutional consideration today.”

Beyond back-end hardware infrastructure, enterprise software is also an expensive proposition for colleges. “Whether public, private, profit, nonprofit, two-year junior college or four-year university, the challenge is universal,” shares Dutta. “Business intelligence is considered an expense—not an investment. There’s no shortage of great BI tools, but few colleges think they can afford them. While it’s expensive, the truth is that it takes an investment to deliver strong analytics capable of driving sound decision making.”

Prevailing strategies for BI success

So where should a college start in its valiant pursuit of winning business intelligence solutions in the face of these pervasive challenges? Following is what our subject matter experts from the front line in the space have to say.

Adopt a spirit of cooperation

According to Dutta, the primary ingredient to a successful business intelligence model is a cooperative alliance between higher ed senior leadership, institutional research and information technology. With good communication and a seasoned project leader that can speak to each concern’s distinct interests, a clear roadmap that effectively serves the university is attainable.

“At the highest level, integration requires a collaborative, cross-discipline effort. Clearly articulated leadership goals and a commitment to IT advancements are paramount to the effort.  So too are seasoned institutional research professionals that ask the right questions and effectively respond with data model, dashboard and report development and design.”

Explore digital transformation

The sheer volume of available data promises to continue expanding in tandem with the growing sophistication of online portals and web-based apps. Effectively managing behemoth volumes of data and its exceedingly prohibitive cost will require institutional transformation.

“Speaking from the business side of emerging technology and what it can accomplish across all sectors, I’m placing my money on managed services,” shares Walsh. Akin to a Netflix subscription, she characterizes ‘IT Consumption’ as a compelling service to bank on.

“Introduced last summer, the model focuses on two things right now: data management and physical infrastructure. In addition to offering institutions the option of leveraging outsourced IT personnel to manage institutional data centers on their behalf, it also features a subscription-based model to resolve the matter of equipment maintenance and obsolescence. Adopters no longer own expensive server, power, heating and cooling equipment, or other peripheral hardware or software. Each of these assets and their ongoing maintenance are provided as part of the consumption service by an outside company, freeing university talent to innovate for their respective institutions.”

A particularly timely benefit for the growing population of colleges that are merging or being consolidated with other higher ed institutions – the IT consumption model also offers responsive cloud-based data storage options to streamline university integrations and shave costs. “While adjustments to cloud storage bandwidth can be very expensive and require customers to wait a month to adjust their data bandwidth up or down, adjustments can be instituted in real-time under the consumption model with users only paying for what they’ve used. In M&A environments that are economically dependent on institutional integration speed, the flexibility of this model is tremendous,” reports Walsh.

Pursue platform integration

“Integrated data can be the direct path to improving the student experience,” says Dutta. “The challenge, of course, is that data is rarely integrated or properly managed in the higher ed space. While institutions collect more than enough data to predict and mine for key student changes, more often than not, they find themselves pulling from multiple databases, overlapping software programs, and enormous volumes of paper data to simply run a static report. That leads to time-consuming, one-off data consolidation into spreadsheets, user error inconsistencies and a rampant duplication of efforts at far more cost. Expert platform integration eliminates that with a single, clean intelligence source that automatically detects data error, can be trusted institution-wide and saves time.”

She adds, “Preadmissions data spanning college prep courses completed, incoming GPA and financial aid package details are indicators of not only future student success, but also risk factors capable of derailing that success. By integrating this data on a single platform, you get the complete picture. An assessment team positioned to examine these trends through centralized platforms can then perform predictive analytics to indicate where students are going. 

Bradley expands on the value of platform integration by sharing, “Equipping individuals from every department across the institution to become well-informed agents of the university makes every single touch point a rich and valuable experience for the student. For example, centralized student intelligence within a single platform could prompt an IT help desk representative to initiate a student conversation with the financial aid department in the course of an unrelated help desk call in response to a red flag on their tuition account. That singular exchange could literally be the difference between the student dropping out and their persistence to graduation.”

Invest in research & analysis

While large scale spending might seem counterintuitive in a cash strapped sector, meaningful investments in research and analysis may well be the most salient of strategies for higher ed success. Beyond an expense line on a university financial statement, strategic spends on these initiatives can be leading drivers of student success and enrollment growth.

“Take student retention as an example,” says Dutta. “Through well-placed investments that facilitate real time student data collection and alerts, a college can pinpoint the precise moment a student begins to struggle, and intervene to drive a better outcome. At the end of the day, universities can drive substantial retention rate increases through such investment.”

Characterized as what she refers to as “proactive analytics,” this data collection begins before a college student even begins their program. By collecting discrete data from the stage of recruitment, spanning SAT scores to first-generation college student status, data correlations can be made to drive student success. Human intervention throughout the entire student life cycle can be strategically facilitated with great results based on these investment-fueled insights.

Pointing to enhanced resource allocation stemming from such investments, Dutta adds, “Accurate real-time demand analysis for online versus ground courses can also be conducted to save the institution untold costs. For example, if course demand is low or high a few weeks before a term start, faculty can be reassigned to more profitable opportunities. The ability to nimbly redirect in this way can save smaller colleges and universities with little budget margin for error from underpopulated classrooms. On the flip side, investments in this analytics model can dramatically drive graduation rates by providing non-traditional students with the flexibility of high-demand online courses they require to remain in school.”

Explore custom apps development

A prime opportunity exists for application development to fully harness the value of big data.

“To my mind, artificial intelligence (AI) is going to be the groundbreaking technology that changes everything for higher ed,” says Bradley. “While we read and process information in a linear way, AI can digest, process, and develop suggestions based on data we’re unable to fathom. For a sense of this potential scale, consider this: scientists leveraging AI are generating more actionable data in a day than we can consume in a lifetime.”

According to the One Hundred Year Study on AI published in 2018 by Stanford University in partnership with the University’s research arm SRI Consulting, McKinsey, and Harvard University, most companies pursuing an AI-focused analysis path aren’t yet fully leveraging its power.

Reflecting the infancy of this exciting technological opportunity, study contributor Michael Chui of McKinsey & Company and the McKinsey Global Institute shares, “We found widespread adoption of different AI technologies across sectors, functions, and geographies around the world. About half of all companies had embedded AI into a corporate business process. However, it’s still early. Most had not yet adopted the complementary practices necessary to capture value from AI at scale.”

Master cost containment

Not having a global telecom service provider-sized budget doesn’t have to be the end of the business intelligence development story for higher ed institutions. Several cost-cutting hacks exist for those not in a position to make substantial investments in sophisticated solutions.

Institutions lacking dynamic reporting capability can integrate multiple systems on a shoestring budget by leveraging the slicer tool found in Excel, reveals Dutta. “The discovery of little-known tools can change everything for a university. Microsoft offers a BI solution for schools with limited budgets that provides quick and easy data filtering in an interactive way. With no investment and nearly no training based on the simplicity of the technology, the dynamic reports it seamlessly enables are a huge return on minimal time spent acclimating yourself to the slicer.”

Whether or not fully integrated, proprietary platforms exist internally, universities would also be well advised to consider training a finite group of “power users” on in-house institutional research tools, suggests Dutta. “Enrolling the dean and one delegate of each college program for training to build their own custom reports can yield dramatic cost- and time-saving results. It’s an unrealistic expectation for canned report templates to serve every academic department’s discreet needs. Recruited delegates with deep insight to department requirements are empowered to build exactly what they need in less time and cost. Institutional consistency can be achieved through the deployment of data dictionaries detailing report tables and fields used university-wide.”

Don’t forget competitive analysis

An extension of cost containing approaches fueling well-informed decision-making, this BI success strategy lies at the opposite end of the technology spectrum. As CIO Jim Bradley explains, competitive analysis conducted through good old fashioned, cooperative peer exchanges continue to offer high value returns against the backdrop of technological advancements.

“As you work to help the university accomplish its goals, it’s a good idea to look at what others are doing and learn from that—remembering not everything is a computer system,” says Bradley. “Building great relationships with vendors and other CIOs, cooperatively benchmarking, and performing secondary competitive research are all essential strategies for remaining competitive. As good stewards of finite resources, many colleges are willing to share data on a reciprocal basis, disclosing return rates on a number of strategic institutional initiatives.”

Highlighting the depth of secondary research available to those in higher ed for benchmarking, he adds, “Tons of associations regularly collect high value member data. For the IT higher ed set, EDUCAUSE publishes a CORE Data service and conducts a fairly comprehensive lineup of studies spanning staff reporting relationships to spending volume that all study contributors can access, while public information on student enrollment and a myriad of other useful metrics is available from the Department of Education’s IPEDs data service.”

As data proliferation and advents in new technology continue at warp speed, so too does access to creative solutions for colleges and universities hoping to compete. While challenges abound, the higher ed sector remains well positioned to respond at every institutional budget level.