Development and Implementation of an Automated Web-Based KPI Management and Dashboard System at «Astana IT University»

Project leader: Zhuldyz Basheyeva , PhD, Assistant professor Department of Computer Engineering

Project Goal: Development of an automated web-based system for tracking, verifying, and analyzing the Key Performance Indicators (KPIs) of faculty and staff at Astana IT University to enhance transparency, efficiency, and data-driven decision-making.

According to the overall goal of the study, the specific objectives are:

1. Conduct a literature review on the research topic, including an analysis of existing KPI management systems, performance dashboards, and faculty assessment methodologies in higher education.
2. Develop a functional model that accurately reflects the end-to-end process of KPI submission, verification, and analysis, defining the specific roles and workflows for Teaching Staff, the KPI Commission, Department Heads, and the Rector.
3. Design and describe algorithms to automate the university’s business processes for KPI data collection, validation, and reporting, thereby eliminating manual inefficiencies and enforcing compliance with institutional policies.
4. Develop a mathematical model to formalize the KPI evaluation process, including the programmatic implementation of institutional formulas for calculating KPI scores and the modeling of workflow dynamics to quantify efficiency gains.
5. Test the developed system and its underlying models using university data to assess its effectiveness in terms of accuracy, efficiency, reliability, and compliance with the established KPI regulations.
6. Compare the performance of the new automated system with the previous manual process to identify and validate the advantages of the new model, such as reduced administrative workload and enhanced data transparency.
7. Publish the research results in relevant academic venues.

The core of this research project is to develop a comprehensive system for managing faculty and staff KPIs at Astana IT University, which automates and improves the entire performance evaluation lifecycle. The project developed functional and mathematical models that take into account the specific criteria and formulas of the university’s official KPI regulations. It is expected that this new system will significantly improve the quality and transparency of performance evaluation, reduce the labor costs of the verification process, minimize human error, and optimize strategic decision-making through integrated analytical dashboards.

1. A detailed analysis of existing systems and methodologies for performance management in academia was carried out. The review included modern approaches to automating Key Performance Indicator (KPI) tracking, the use of analytical dashboards in higher education, and frameworks for digital transformation
2. A functional model has been developed that reflects all business processes of KPI tracking, submission, and validation at the university. The model defines the distinct roles and workflows for the four key stakeholders: Teaching Staff, KPI Commission, Department Head, and Rector. It was designed to be in full compliance with the specific institutional policies and organizational structure of Astana IT University. The end-to-end workflow of this functional model is visualized in Figure 1

Figure 1. Full workflow of KPI tracking and validation in the automated system

A user-centric interface design was developed for the automated KPI management system, which takes into account all necessary criteria for an effective and enjoyable user experience (UX). The design optimizes the complex process of performance tracking by creating an intuitive and efficient workflow for all stakeholders.

This UI/UX framework was developed based on key criteria, including:

• Role-Specific Functionality: The interface is dynamically tailored to each of the four user roles (Teaching Staff, KPI Commission, Department Head, Rector), ensuring users only see information and actions relevant to their tasks.
• Simplicity and Clarity: The platform was designed to be simple and clear, with built-in validation features to minimize submission errors. This directly addresses the complexity and high risk of human error found in the previous manual process.
• Data-Driven Dashboards: The system features interactive dashboards with clear data visualizations, allowing for easy interpretation of performance trends and enhancing data-driven decision-making.

This design approach minimizes cognitive load for users and is intended to create a satisfying and pleasant user experience, a conclusion supported by high user satisfaction ratings recorded during testing.

Figure 2: Example of an individual performance analytics dashboard, showing a comparison of scientific achievements between the current and previous trimesters.

Figure 3: The KPI selection interface for teaching staff, allowing users to choose performance indicators from different categories like scientific work and social activities.

Figure 4: The data entry form for a selected KPI, where a user provides detailed information and uploads supporting documents for their achievements.

Figure 5: An alternative view of the data entry interface for the ‘Social activity’ category, showing fields for event details and evidence upload.

Figure 6: The submission section of the data entry form, including fields for additional information and action buttons to save a draft or submit for review.

Figure 7: The monitoring dashboard for the KPI Commission or a Department Head, providing a comprehensive overview of all employee submissions with filtering options and status indicators.

Figure 8: An example of a high-level analytics dashboard for management, displaying publication statistics, database indexing ratios, and year-over-year comparative analysis.

Figure 9: Department Head dashboard view, showing aggregated statistics for departmental achievements, such as total publications and competition wins.

One (1) scientific article was submitted to a peer-reviewed scientific journal in the scientific field of the project

Zhuldyz Basheyeva

Project Leader, PhD, Assistant professor Department of Computer Engineering

Dinmukhammed Oralkhanov

Project Executor, 3rd year student of Astana IT University

Orazov Tairlan

Project Executor, 3rd year student of Astana IT University