From Data To Decisions

On many campuses, decisions support teams struggle to encourage campus members to make data-informed decisions. This study provides guidance on how to improve the user-friendliness and accessibility of self-service analytics resources for the campus community.

Download the complete publication or explore the table of contents to learn more about how institutions such as the University of Kentucky, Bucknell University, and York University implemented data-informed decision making on campus.

A key challenge: The growing demand for data

Decision support teams (e.g., Institutional Research, Business Intelligence) often struggle to provide true decision support to campus members largely because they are overwhelmed with one-off, low-level requests. Decision support is unable to focus on higher-level tasks, such as how to improve predictive modeling and ensure that people and divisions have the data they need to make informed decisions. Additionally, campus members can get stuck in “analysis paralysis,” unable to identify the data they should use or how to use it.

This study tackles this conundrum in two ways. First, we present strategies for helping non-experts use data effectively through easier access to the data they need and the creation of intuitive, digestible summaries of that data. Second, we describe how to create a team of effective decision-support experts through the process of upskilling existing employees.

Section 1: Enhancing the user-friendliness of self-service resources

Central decision support teams are often inundated with ad hoc data requests, in part due to skill deficits, data presentation issues, and uncertainty of how to use decision support resources across campus. Although these hurdles to self-service are challenging, they present opportunities for decision support teams to improve the user experience.

• Tactic 1: Institutional Facebook Configurator
• Tactic 2: Pop-Up Data Presentation Prompts
• Tactic 3: Role-Based Recommendation Engine
• Tactic 4: Crowdsourced Report Use Guides

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Section 2: Promoting single versions of the truth

Undisciplined requests consume a significant amount of decision support teams’ capacity, and some of these requests occur because of campus members’ desire to rationalize their assumptions. A significant difference exists between data investigation and rationalization—the former seeks to learn something new, while the latter tries only to prove an already-held belief.

• Tactic 5: Data Quality Assurance Certification
• Tactic 6: Demand-Driven Report Maintenance
• Tactic 7: Standardized Program Evaluation Metrics
• Tactic 8: Semi-customizable Department Scorecard

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Section 3: Distributed analytics staff

Most institutions struggle to achieve the benefits of centralization and decentralization, with decision support staff typically generalists in a central office or disconnected from institutional technical systems knowledge in a campus unit. Centralized decision support staff forge partnerships with distributed units to ensure that analysts across campus possess the right skills to provide adequate decision support to campus leaders.

• Tactic 9: Analytical Competencies Road Map
• Tactic 10: Matrix BI Reporting Lines
• Tactic 11: Business Analyst Cross-Training
• Tactic 12: Data-into-Action Awards
• Tactic 13: Just-in-Time Expert Networks

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Supporting tools: Find helpful templates, worksheets, and dashboards in our Implementation Toolkit.

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