Return Network Simulation System for Retailer KPI Prediction
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Solution Overview
Problem
Retailers lack a method to predict the impact of changes in their return network on key performance indicators (KPIs) such as return shipping costs, lost sales, and gained sales without making actual adjustments, which can be costly and time-consuming.
Innovation Solution
A simulation system that receives test parameters defining changes to the return network, simulates return orders, updates inventories, predicts virtual sales, and generates KPIs based on historical data, allowing for the evaluation of changes without physical implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a retailer makes actual changes in the return network to measure impact on KPIs, then the effect on performance can be identified, but the approach requires substantial investment and the effect cannot be measured until months later
Solution Approach 1:
The patent applies preliminary action by simulating return network changes in a virtual environment before implementing them in the actual network. The simulation system allows retailers to test different return network configurations and predict their impact on KPIs in advance, eliminating the need to wait months to see the effects of actual changes. This enables decision-makers to evaluate multiple scenarios and select the optimal configuration before committing resources.
2Measurement precision
If a retailer makes actual changes in the return network to measure impact on KPIs, then the effect on performance can be identified, but the approach requires substantial investment
Solution Approach 1:
The patent applies copying by creating a virtual replica of the return network that mirrors the actual network's structure and operations. This digital twin allows retailers to conduct experiments and measure KPI impacts without physically changing the real network. The simulation copies historical return data, inventory levels, and network configurations to recreate realistic scenarios, enabling cost-free evaluation of potential changes.
3Loss of energy
If a simulation system is implemented to predict KPI changes, then the need for costly adjustments is reduced, but the system complexity increases
Solution Approach 1:
The patent applies universality by designing a simulation system that handles multiple functions within a single platform. The system can simulate various return network scenarios, track inventory across multiple locations, predict KPI changes, and evaluate different what-if situations all through one integrated system. This multi-functional approach reduces the need for separate tools and systems, making the complexity manageable while providing comprehensive analysis capabilities.
Data Source
AI summary
Embodiments herein describe a return network simulation system that can simulate changes in a retailer's return network to determine the impact of those changes. Advantageously, being able to accurately simulate the retailer's return network means changes can be evaluated without first making those adjustments in the physical return network. Doing so avoids the cost of implementing the changes on the return network without first being able to predict whether the changes will have a net positive result (e.g., a positive result that offsets any negative results). A retailer can first simulate the change on the return network, review how the change affects one or more KPIs, and then decide whether to implement the change in the actual return network. As a result, the retailer has a reliable indicator whether the changes will result in a desired effect.