Operational Excellence: Optimize enterprisewide processes and operations 

System: Business Intelligence Platform, Data Matching Process, Workload Management Tool

Actor: End Users, Data Analysts, Fraud Analysts, Project Managers

Scenario:

End users in an organization want to customize their business intelligence platforms to discover relevant data more efficiently and reduce user effort.

End users have access to a variety of data sources and want to customize their dashboards and reports to display the most relevant and actionable information for their specific needs.

They utilize the customization features of the business intelligence platform to personalize their data views, configure alerts for important metrics, and automate data refreshes.

By customizing the business intelligence platform, end users can optimize their data discovery process, minimize manual efforts, and focus on analyzing insights for informed decision-making.

Use Case

Use Case Name: Customize Business Intelligence Platforms for End Users to Discover Relevant Data and Reduce User Effort

Primary Actor: End Users

Goal: To customize business intelligence platforms to discover relevant data more efficiently and reduce user effort.

Pre-conditions: End users have access to a business intelligence platform with customization capabilities.

Post-conditions: End users have personalized data views, configured alerts, and automated data refreshes to enhance their data discovery process and reduce manual efforts.

Operational Excellence: Optimize enterprisewide processes and operations 

System: Business Intelligence Platform, Data Matching Process, Workload Management Tool

Actor: End Users, Data Analysts, Fraud Analysts, Project Managers

Scenario:

Data analysts and fraud analysts in an organization want to replace manual data-matching processes with algorithms that detect anomalies and fraud.

The current manual data-matching processes are time-consuming and prone to errors, limiting the efficiency and effectiveness of fraud detection.

Data analysts and fraud analysts work together to develop and implement algorithms that can automatically identify anomalies and potential fraud patterns based on predefined rules and statistical models.

By deploying automated data-matching algorithms, the organization can improve the accuracy and speed of fraud detection, enabling timely mitigation of risks.

Use Case

Use Case Name: Replace Manual Data-Matching Processes Using Algorithms that Detect Anomalies and Fraud

Primary Actor: Data Analysts, Fraud Analysts

Goal: To replace manual data-matching processes with algorithms that detect anomalies and fraud.

Pre-conditions: Manual data-matching processes for fraud detection are in place.

Post-conditions: Automated data-matching algorithms are deployed, improving the accuracy and speed of fraud detection processes.

Operational Excellence: Optimize enterprisewide processes and operations 

System: Business Intelligence Platform, Data Matching Process, Workload Management Tool

Actor: End Users, Data Analysts, Fraud Analysts, Project Managers

Scenario:

Project managers in an organization want to deploy an automated workload management tool to improve task allocation and project management.

The current task allocation and project management processes are manual and decentralized, leading to inefficiencies and coordination challenges.

Project managers research and select a suitable workload management tool that can automate task allocation, facilitate resource management, and enable better collaboration among team members.

By deploying the automated workload management tool, project managers can streamline task allocation, optimize resource utilization, and improve overall project management efficiency.

Use Case

Use Case Name: Deploy an Automated Workload Management Tool to Improve Task Allocation and Project Management

Primary Actor: Project Managers

Goal: To deploy an automated workload management tool to improve task allocation and project management.

Pre-conditions: Manual and decentralized task allocation and project management processes are in place.

Post-conditions: An automated workload management tool is deployed, enhancing task allocation, resource management, and overall project management efficiency.