Roadmap for implementing business intelligence systems in higher education institutions

Business intelligence (BI) systems are processes and tools for gathering and analyzing data to gain insights about an organization and inform strategic decisions. Effective BI systems are invaluable in higher education, where disparate data centers make it challenging to access an institution-wide or even program-wide perspective for centralized decision-making processes.

Implementing business intelligence solutions at your institution can help administrators harness data from numerous sources to enhance every area of institutional performance, from student recruitment, enrollment, and retention to financial management, faculty success, and accreditation.

Before investing in a cutting-edge business intelligence system for your higher education institution, consider the positive impact you can expect from an effective solution. Leveraging BI can improve every area of institutional performance, including:

1. Student recruitment: BI tools can analyze student demographics and survey feedback data to identify the prospective student populations your institution appeals to and those less drawn to it. These insights can help tailor targeted marketing campaigns to attract more high-quality applicants.
2. Admissions and enrollment: BI solutions can streamline admissions and enrollment workflows by automating data processing tasks. For example, BI software can automatically populate forms, flag incomplete applications and highlight next steps, send enrollment task reminders to students and administrators, and generate real-time dashboard tracking for application statuses and key enrollment metrics.
3. Retention: Higher education BI tools can harness predictive analytics to alert support staff of at-risk students and recommend timely interventions. They can also provide insights based on student engagement and satisfaction data to help personalize student support. These functions help your institution provide each student with the support they need when they need it to promote retention and boost graduation rates.
4. Financial forecasting: BI software can analyze revenue and spending data to enhance financial forecasts and budgeting. This supports better cost management and targeted resource allocation to advance institutional KPIs.
5. Curriculum planning: Higher education BI solutions can analyze student performance data to detect learning gaps. These insights can guide curriculum changes and help create personalized learning paths that meet individual needs while aligning with the course outcomes.
6. Faculty success: BI data analysis can help uncover key improvement areas to target with professional development initiatives, and provide objective feedback on progress toward career goals.
7. Accreditation: BI reporting can provide evidence to support accreditation self-studies, demonstrating your institution’s alignment with accreditation standards based on KPI data.

The positive impacts of business intelligence in areas like recruitment, retention, and financial forecasting come from the tangible benefits BI solutions unlock for higher education institutions. These benefits arise from innovative software features empowering institutions to know more and do more in less time.

1. Increased administrative efficiency

BI solutions can automate potentially time-consuming administrative tasks like data entry and reporting. This frees up your team to focus on high-value activities for institutional performance like strategic planning, student support, teaching, and research. The Harvard Business School reports that 64 percent of surveyed organizations leveraging data analytics, the heart of BI, have seen improved efficiency and productivity.

2. Optimized resource allocation and cash flow

By analyzing current resource utilization and financial performance KPIs, BI solutions can generate insights to help institutions allocate funds where they will make the greatest impact. BI analysis can also expose areas of overspending or underutilization of available funds to inform budget adjustments. Through strategic financial decisions based on these insights, institutions can manage their budgets and cash flow for financial stability amid economic fluctuations.

3. Elevated teaching quality

BI tools equip teaching faculty with data-driven insights into student performance and engagement. Analysis of student survey feedback, assessment grades, and attendance can help lecturers adapt their lesson plans and teaching methods to improve student satisfaction and academic performance.

4. Effective assessments

Using BI-powered analysis and data reporting, your institution can gain valuable insights into assessment data. These insights include alignment with course objectives and lesson content, common areas of difficulty, and disparities across courses or demographics. Leveraging these assessment data insights, your faculty can develop formative and summative assessments that better support student success and program goals.

5. Enhanced student progress monitoring

BI software pulls back the curtain on student progress in real time. At any moment, faculty can access institution-wide views of student performance metrics or zoom into individual student progress using centralized business intelligence dashboards.

BI tools generate these reports by continuously tracking student participation and achievement data. They can even send automatic alerts to faculty when a student is at risk of falling behind and recommend supportive interventions using predictive and prescriptive analytics.

6. Institution-wide KPI tracking

BI dashboards give administrators and faculty members real-time updates on the KPIs most relevant to institutional goals. These KPIs could include application conversion rates, student satisfaction scores, graduation rates, engagement metrics, and research output.

7. Improved decision-making

In higher education, a strategic decision is only as good as the data informing it. Data integration, analytics, and visualization tools in BI software can help administrative leadership make more effective decisions in every area, from curriculum development to marketing and financial planning.

How can your institution unlock improved decision-making with business intelligence systems? You can employ reliable BI best practices that enhance efficiency, personalize student interactions, sharpen recruitment efforts, and enhance student success. Follow these seven steps to bring your institutional decision-making process into line with best practices.

1. Define your goals and KPIs

When your institution is faced with an important strategic decision, like how to distribute donated funds across your programs, outline the goals and objectives you intend your decision to achieve. For example, improving graduation rates could be a primary goal.

Once you understand your goals, you can define the KPIs necessary to measure progress toward them. If your institution is aiming for higher graduation rates across all programs, these KPIs will include year-on-year retention, student engagement and satisfaction scores, and average grades. Tracking these KPIs at institutional and program levels will be relevant to your decision.

2. Choose your tools

With your goals and KPIs defined, ask whether your institution has the BI software it needs to track the relevant KPIs. In our example, you would need a software tool kit that can collect and analyze student feedback, enrollment, engagement, and performance data.

If your institution lacks the necessary software or you are unsatisfied with your existing system, explore the available BI solutions. Focus on software designed for higher education contexts with the necessary capabilities to monitor KPIs related to your institutional goals.

3. Collect and analyze your data

Armed with state-of-the-art BI tools, collecting and analyzing data relevant to your decision will be easy. These tools can automate data collection from multiple sources, including attendance records, LMS gradebooks, and online course evaluations. Then, they can employ data visualization, reports, and predictive analytics to show where your key metrics are now and where they are projected to be a year or four from now.

For example, you may find that some programs consistently yield higher grades and satisfaction scores than others. Investigate further, and you may find that some modules within the underperforming programs show the lowest assessment grades, and course evaluations from those modules express dissatisfaction with the teaching methods. These insights could be vital in shaping your funding allocation.

4. Consider your options

Most major strategic decisions at higher education institutions involve collaboration and stakeholder engagement. This presents an opportunity to consider diverse perspectives regarding how to achieve an institutional goal like improving graduation rates through strategic funding distribution. Centralized BI dashboards give each participant in your decision-making process access to the KPI data they need to make an informed contribution.

With our example goal of allocating funds to improve graduation rates, these contributions could be proposed distributions. In some cases, team members could also consult prescriptive analytics within the BI software for an objective, data-driven view. This combination of collaboration and software-powered analysis brings the best of human perspective and technological innovation to bear on your decision-making process.

5. Plan and execute interventions

After conducting data analysis and collaborating on possible solutions, it’s time to choose, plan, and implement a strategic decision. In our example, your decision may be to invest the bulk of donated funds into professional development within underperforming programs to help lecturers master innovative teaching methodologies for improved student engagement and comprehension.

6. Monitor and evaluate performance

As you implement your decision, monitor your KPIs to evaluate whether it serves the intended goals. If you invested in innovative teaching workshops to improve graduation rates, look for improvement in student satisfaction scores and grades by the end of the following semester, and improved year-on-year retention after the next academic year’s enrollment cycle. If you see these improvements, your solution is likely successful and should yield improved graduation rates in the long term.

7. Implement changes as necessary

If you do not see the anticipated improvements in your KPIs, you may need to adapt or pivot from your initial decision. In our example, further data analysis can help guide you as you explore whether to adapt your professional development initiatives, focus on other areas of student success and engagement in those programs, or reallocate funds to other programs.

Data collection and analysis is the engine driving business intelligence and the reason it is such an effective vehicle for institutional excellence. Whether your institution is focusing on student outcomes, support services, or diversity and inclusion, the BI solutions you consult to inform your decisions will leverage data collection and analysis to aid you.

BI data analytics for diversity and inclusion

Your institution can use BI data analytics to cultivate a more diverse and inclusive campus in several ways, including:

• Sorting through application and enrollment data to identify demographics your student recruitment campaigns could better target.
• Organizing student survey feedback by demographic to understand disparities in the student experiences of diverse populations.
• Comparing academic outcomes and persistence between demographics to provide support and accessibility services for the students who need them most.

BI data analytics for personalized student support

Your institution’s student support services can be the difference between students persisting to achieve their potential and dropping out. However, each student has unique needs in the classroom and beyond, and adapting your support services to meet those needs can help maximize their satisfaction and success. You can leverage BI data analytics to personalize student support through:

• Early alerts that use prescriptive analytics to guide interventions for each at-risk student’s needs.
• Course data analysis to identify challenging modules for targeted tutoring and mentorship.
• Student survey feedback analysis to find underserved needs, like mental health services or child care.

BI data analytics for enhanced retention and graduation rates

Competition for enrollment is heating up, as the coming five years are predicted to see a 15 percent reduction in the number of high school graduates. This means retention is more vital than ever to your institution’s stability. Retention also fuels healthy graduation rates — a key metric for institutional success and prestige.

Strategies for improving retention and graduation rates through BI data analysis include:

• Using predictive analytics with early alerts to focus retention efforts on at-risk students.
• Tailoring academic advice and mentorship to each student’s strengths, weaknesses, and goals using comprehensive data-based student profiles.
• Evaluating and improving current retention strategies by monitoring KPIs like attendance and satisfaction scores.
• Automating personalized communications to check in with students, remind them of tasks, and offer support.

As a vehicle for institutional success, BI’s value also derives from its potential to steer crucial data from disparate sources across your institution to a centralized, accessible hub. This integrative capacity lends itself to deeper insights and streamlined decision-making. Several strategies exist to optimize data centralization through BI solutions.

Why data centralization is crucial

Higher education institutions are complex organizations with data arising from numerous sources across multiple departments and programs. This means data becomes siloed by default, making it challenging to generate a comprehensive view of institutional performance or conduct cross-departmental comparisons and collaborations. BI platforms can solve this problem by integrating data from dispersed locations, provided your team uses your institution’s BI software effectively.

How to structure analytics and BI functions for centralization

One of the best practices for effective data centralization is to establish a BI team at your institution. How can you set this business intelligence analytics team up for success?

The ideal structure is a centralized team for coordinated, institution-wide analysis, as well as department-specific units staffed by faculty who understand departmental priorities and teaching subjects. For optimal performance, your BI team needs:

• Analytics expertise: Whether your institution has the resources to hire dedicated BI personnel or is appointing current IT or administrative staff members to BI roles, prioritizing analytics expertise is key. User-friendly BI software tools can analyze and report data in ways all faculty members can understand. However, analytics expertise is still helpful in informing which questions to ask and using the available tools to their full potential.
• Clear role divisions: The units should focus on department-specific analysis, while the centralized team manages institution-wide analytics and coordinates cross-departmental collaboration. This frees the central and departmental components of your team up to focus on their areas of expertise while streamlining operations.
• Solutions for integrating decentralized processes: If this guide’s strategies for optimized BI in higher education are new to your institution, your departments may have separate data management processes with limited coordination. In this case, overcoming data silos will require close communication between central and departmental team members. With the centralized team’s coordination, units can collaborate on protocols to make departmental practices more compatible with system integration for data centralization.
• Standardized data management practices: Departmental system integration protocols can empower each department’s BI unit to adopt standardized data management practices. The centralized team’s responsibilities include ensuring each unit adheres to cohesive practices for collecting, analyzing, and reporting data.
• Centralizing software: Invest in BI software tools that simplify every aspect of data centralization. The ideal solutions are those designed for higher education institutions with capabilities to integrate with existing digital infrastructure and pull data from numerous sources across your institution. When these tools can also automate data collection and generate intuitive reports, they make data-driven insights accessible to all faculty members and help automate data management best practices across your departments.

Equipped with the right business intelligence tools and processes, your institution can make progress in every area of higher education excellence. As you employ the business intelligence strategies in this guide to achieve your institutional goals, remember these six fundamental best practices:

• Define KPIs: For every institutional goal, define measurable KPIs for your BI system to track, such as annual enrollment, enrollment conversion rates, retention rates, or publications per faculty member. Ensure your BI tools can measure KPIs relevant to your goals. These KPIs will vary as your goals and strategies evolve.
• Centralize data: Invest in a business intelligence platform that provides a unified view of data from SIS and LMS platforms and dispersed departmental sources. Establish protocols to ensure departmental data management practices feed into this centralized system.
• Harness predictive analytics: Choose BI solutions with predictive analytics to anticipate student needs and focus timely interventions where they are most needed for retention. These capabilities equip faculty members and support staff to serve growing student populations efficiently.
• Visualize data: Opt for a BI platform with user-friendly data visualization functions. These functions empower all stakeholders to understand data and make informed contributions to strategic decisions.
• Conduct competitor analysis: Study institutions comparable to your own. Where they have the lead in a key institutional success metric, use BI data analysis to explore how your institution could seize opportunities for improvement. For example, if BI reveals your institution lacks adequate support resources for a challenging course, investing in these resources could make your graduation rates more competitive.
• Develop targeted strategies: When BI detects a key area for improvement, adapt your institution’s existing strategies to target that area. For example, discovering disparate enrollment rates between student demographics could highlight a need for student recruitment campaigns targeting that demographic.

Conclusion

Applying business intelligence in higher education can help overcome data silos and support strategic decision-making with data-driven insights. Institutions can realize the greatest benefits from BI by investing in solutions optimized for higher education that offer:

• Integration with existing infrastructure.
• Automated data collection.
• Predictive and prescriptive analytics.
• Intuitive reporting and visualization.

Administrators can use these solutions to track KPIs related to institutional goals and inform the strategic decisions that drive excellence. Interested in learning more about data analysis software for higher education business intelligence? Explore how Watermark software solutions can help your institution gain BI insights.