Executive Summary

Overview

The AIU Digital Ecosystem Audit set out to identify the AIU’s applications, data management and reporting tools and internal information warehousing sites, and the interrelationships among them, and to propose recommendations for improvement Unit (2023). The project ran through spring of 2024 and entailed focus-group conversations with internal departments and teams within each of the four AIU divisions, followed by a full cataloging of data systems, data integrations, and process needs identified along the way. Key findings and recommendations are shared below and are explored in further detail in the full report sections for each recommendation area.

Methodology

The project team adopted the following workflow for information collection and analysis:

  1. Internal Information Collection: Technology Services staff conducted an internal review of known systems, integrations, and data flows. Because this department manages or supports a large proportion of AIU systems, beginning the ecosystem cataloging process here provided a strong foundation and context for more focused conversations in Phase 2.
  2. Focus Groups: Team-specific interviews were then completed with staff across each division* to understand data system usage, needs, and reporting processes. A general interview outline was used to ensure consistent information gathering across program teams–this included questions about each team’s scope of systems, integrations, pain points, access and ownership, reporting obligations, and general data needs.
  3. Data Ecosystem Documentation: The project team cataloged all data systems indicated through focus group conversations using a relational database system (see report appendices), helping to structure information about the relationships between systems, allowing analysis of strengths and gaps in system capabilities, and laying the groundwork for future data documentation at a more granular level.
  4. Early Phase Projects: Many staff teams described, during focus group interviews, low-lift/high-urgency projects that could improve operations in the short term. The project team began or completed several of these projects while conducting the Data Ecosystem Audit to ensure that documentation of the problems to be solved did not stand in the way of progress towards a solution.
  5. Reporting & Presentation: Initial findings were reviewed with the Executive Leadership Team (ELT) on April 2nd, 2024. ELT members shared reflections on the findings, recommended additional staff teams to interview, and discussed the impacts of high-level recommendations such as centralized data management. Resulting follow-up work and drafting of this executive summary and its companion report sections was completed in April and May 2024.
  6. Recommendation Implementation: The most important phase of this project is the work that follows: ongoing efforts to implement the recommendations put forth at the staff team, division, and organizational levels.

Key Findings

  1. The AIU Data Ecosystem is large, varied, and complex, with at least 203 applications/systems in use. The natural organizational structure of an intermediate unit, with a large number of small teams serving specialized purposes (compared, for example, to a school district, with a smaller number of comparatively larger teams serving more interrelated purposes), results in a correspondingly vast network of application systems, often procured in isolation and specialized for each team’s needs. This data ecosystem composition presents unique challenges in terms of interoperability, security, application support, and analytical capability.
  2. Flagship systems (Oracle, Entra ID) have enabled significant interoperability in core AIU systems. Despite the ecosystem complexity indicated above, recent system implementations such as Oracle Fusion, ClassLink (both the Launchpad user portal and the OneSync rostering and automation platform), and Microsoft Azure and M365 resources (such as Entra ID and SharePoint) have greatly increased the number of connections between systems–an improvement in both operational efficiency and cybersecurity. For a specific example, Oracle Fusion has existing data connections to 32 other systems (24 of which are automated, while 8 involve manual uploads), greatly reducing the staff time required to manage information exchange across these connections.
  3. Many data resources and processes are replicated across teams, often working independently of one another. While each AIU team serves a specialized purpose, many teams gather similar data resources–for example, student demographic information, program participation, and enrollment details–sometimes even on behalf of the same students from the same districts. There will always be certain data collection and reporting needs unique to each team; however, efforts to consolidate data collection, validation, storage, and reporting processes can greatly improve operational efficiency, returning staff time to the daily program implementation work that serves AIU learners.
  4. Manual data entry and manual data integrations represent the most common pain point across teams. This finding applies across team functions–some teams indicated bottlenecks in data collection and management processes, wherein the same information is requested multiple times or key-entered separately into multiple internal systems; other teams identified similar challenges with reporting portals, wherein the lack of bulk upload processes forces staff to double-enter records in AIU source systems and state or federal reporting portals (see following item).
  5. (State and federal) Reporting obligations dictate most teams’ data ecosystems and practices. This is particularly true for homegrown and custom-built systems, and its impacts reach from data collection (“we ask users for this data because we report on it”) to data management (“we use this storage option to accommodate regular program audits”) to data-out mechanisms (“we developed these queries and reports to pre-check our data submissions”). This is not a negative disposition, per se; rather, it helps to explain the driving force behind current system architectures.

Recommendations

The Data Ecosystem Audit’s resulting recommendations fall generally into three “parent recommendation” categories:

  1. Build toward centralization, standardization, and interoperability of data resources.

    This focus area recommends approaches to standardize and centralize data resources where possible in order to (A) enable holistic analysis of organizational data, (B) improve efficiency and effectiveness of data processes across teams, and (C) empower shared use of both data resources and technical resources across the organization in order to better serve AIU students, families, and districts.

  2. Implement organization-wide data governance structures.

    Many teams identified a need for improved documentation, data management, training, access controls, or process management–all of which fall under the larger umbrella of “data governance.” This focus area recommends establishment of AIU Data Governance operations and proposes several specific recommendations that would naturally be addressed by a data governance committee.

  3. Advocate for more streamlined data reporting solutions.

    While this focus area encompasses the fewest sub-recommendations, it represents perhaps the largest pain point described by staff in all four AIU divisions: compliance and accountability reporting processes. These swallow considerable staff time, which must be diverted from more direct-service work and often involves tedious or inefficient data entry (sometimes double-entry) better spent in service to learners. Data reporting is very important for accountability and transparency; this recommendation proposes advocacy for more efficient and effective data collection and reporting processes (typically for state-level reporting) in order to improve the reliability of reported data and to return valuable staff time to program teams.

*The following teams were interviewed in step 2:

  • Adult Education (Family Literacy)
  • Alternative Education Program (AEP)
  • Blind and Visually Impaired Support Program (BVISP)
  • Continuing Professional Ed (CPE)
  • Deaf/Hard of Hearing Support Program (DHHSP)
  • Early Head Start (EHS)
  • English as a Second Language (ESL)
  • Evaluation, Grants, & Data (EGD)
  • FACES/TEAR
  • Finance
  • Head Start (HS)
  • Human Resources (HR)
  • Legal/Advocacy
  • Marketing & Strategic Communications (MarComm)
  • Non-Public Schools Program (NPSP)
  • Preschool Early Intervention (PEI)
  • Remake Learning
  • School-Based Access Program (SBAP)
  • School Improvement (ATSI/CSI)
  • Special Education Schools (SEPS)
  • Speech and Language Pathology (SLP)
  • Training & Consultation (TAC)
  • TransformED
  • Waterfront Learning (WFL)
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References

Unit, Allegheny Intermediate. 2023. “Strategic Plan 2021-2026.” https://www.aiu3.net/cms/lib/PA49000033/Centricity/Domain/13/StrategicPlan-Full-ADA_23-098-5D.pdf.