Prescriptive Analytics for Performance Indicator Forecasting
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Solution Overview
Problem
Businesses face challenges in predicting and managing performance indicators (PIs) that deviate from established criteria, leading to potential problems or opportunities that are not adequately addressed by existing systems, which struggle to provide timely and effective solutions.
Innovation Solution
The implementation of Prescriptive Analytics techniques that use predictive analysis, optimization, and root cause analysis to forecast future issues and opportunities in business processes, allowing for the determination of desirable actions to maintain compliance with business criteria by analyzing relationships between performance indicators and influencers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional monitoring systems are used to track performance indicators, then basic data collection is achieved, but timely prediction and prevention of deviations from business criteria cannot be provided
Solution Approach 1:
The system performs preliminary actions by predicting future deviations in performance indicators before they actually occur. Using historical data and predictive analytics, the system forecasts potential compliance issues and triggers early warnings, allowing businesses to take preventive measures rather than reacting after deviations have already happened.
Solution Approach 2:
The system implements continuous feedback loops where performance indicator data is constantly monitored, analyzed, and fed back into the predictive model. This feedback mechanism enables the system to learn from actual outcomes and improve its prediction accuracy over time, while also providing real-time alerts when deviations are forecasted.
2Loss of information
If comprehensive performance monitoring is implemented across all business processes, then complete visibility into all metrics is achieved, but system complexity and resource requirements increase significantly
Solution Approach 1:
The system extracts only the most critical and relevant performance indicators for monitoring and prediction, rather than attempting to track every possible metric. By identifying and focusing on key performance indicators that have the greatest impact on business criteria compliance, the system maintains comprehensive visibility into essential metrics while avoiding the complexity of monitoring all possible data points.
Solution Approach 2:
The system applies different monitoring and analysis approaches to different business processes and performance indicators based on their specific characteristics and importance. Rather than using a uniform monitoring approach across all metrics, the system tailors its predictive analytics and data collection strategies to the local requirements of each business process, reducing overall system complexity.
3Difficulty of detecting and measuring
If detailed analysis of all performance data is performed, then complete understanding of root causes is achieved, but processing time and computational resources are excessively consumed
Solution Approach 1:
The system extracts and focuses analysis on the most significant factors and variables that contribute to performance indicator deviations. Rather than analyzing all available data in equal detail, the system identifies key drivers and root causes through predictive analytics, concentrating computational resources on the most impactful factors while still achieving accurate root cause detection.
Solution Approach 2:
The system performs partial analysis by focusing on the most critical performance indicators and their primary drivers, rather than conducting exhaustive analysis of all data points. This selective approach provides sufficient root cause understanding for effective decision-making while significantly reducing processing time and computational resource requirements.
Data Source
AI summary
A method of determining a set of future actions includes providing an interface to a user, the interface including an adjustable element associated with a future value of an influencer. The influencer is associated with an action. The method further includes receiving via the interface an adjusted future value of the influencer, projecting a future value of a performance indicator based at least in part on the adjusted future value of the influencer, and providing a results interface to the user indicative of the future value of the performance indicator.