From Bots to Intelligent Agents: Unlocking Next-Level Problem-Solving with IA in Returns Management

It's important to understand the difference between bots and IA’s. Bots' capabilities, as you have experienced, quickly fall off. They lose context and fail to give the conversation a meaningful and improved outcome. Most are algorithmic and logically bound, lacking the ability to adapt beyond their programmed capabilities. In contrast, IA’s can learn from our ML models, advance the conversation to the most advantageous outcome, ensure that the pathway was followed, hit the target, and then take credit and accumulate the savings.? Because our IA’s impact our behavior and are held accountable for improvements, you could say IA’s are goal-driven, enriched via the ML model powering it. ?While bots might have a place somewhere it’s time to take it the next level with IA’s for collaborative complex problem-solving, as seen in the Tallgrass RevLogix Returns Management solution.

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Features of an ‘IA’ Intelligent Agent

One of the standout features of our IA’s is their ability to conduct automated triaging. When a product return request is initiated, the agent can assess key data points, such as warranty status, product history, and potential repair cost to determine whether a product should be repaired, refurbished, or recycled.

Some improved outcomes:

1.??????? SLA alignment: Can read workbench testing telemetry supplied during an RMA creation event ensuring the unit was operated within technical bounds.

2.??????? SLA alignment: Supplying a predicted out-of-warranty PO for known past cost results in fewer abandoned repairs and wasted diagnostic time while managing expectations of time and energy.

3.??????? Sales opportunity: Can leverage the valuation of the digital passport to compel retirement or release for sales credit on newer products and services. ?

4.??????? RMA reduction: compel in warranty units with NTF predictions via past RMA stat’s from that customer and model. Alert repair team should the risky RMA move forward. Provide stat’s to improve NTF SLA relationship.

5.??????? Repair optimization: Prescribe ECO’s and ERO (engineering repair orders) so that repair processes can best start and stop within the most efficient repair pathway.?

This kind of data-driven decision-making helps our clients make more sustainable choices and reduces unnecessary processing costs. In cases where warranty scenarios are unclear, the IA’s autonomously navigates the complexities of In-Warranty, Out-of-Warranty, and Voided Warranty situations to direct the product to the most suitable path.

Another key feature of our IA’s is continuous learning. These agents leverage historical returns data to recognize recurring patterns in failure points or customer complaints. This learning enables the IA’s to improve over time, enhancing decision-making and optimizing the returns process. By analyzing vast amounts of data, the IA’s can identify opportunities for improvement, provide recommendations for reducing failure rates, and assist Contract Manufacturers (CMs) by providing insights that minimize repair times and improve overall product quality.

The Process of IA’s

The process of IA’s in the Returns Management workflow can be broken down into several stages:

1.??????? Data Collection: The IA’s gathers relevant information regarding the return request. This includes product details, customer information, warranty status, and product usage history. The data is collected from multiple sources, such as CRM systems, warranty databases, and IoT devices.

2.??????? Analysis and Assessment: Using advanced machine learning algorithms, the IA’s analyzes the collected data to assess the condition of the returned product. It evaluates factors like potential repair cost, likelihood of defect, warranty coverage, and the product's residual value. This analysis helps determine the best course of action for the returned item.

3.??????? Automated Triage: Based on the assessment, the IA’s categorizes the return into different paths—repair, refurbishment, recycling, or return to stock. This triaging is done autonomously, reducing manual intervention and speeding up the decision-making process.

4.??????? Decision-Making and Recommendation: The IA’s makes informed decisions regarding the next steps for the product. For instance, if a product is under warranty and repair costs are minimal, the agent recommends repair. If the product has reached the end of its useful life, it may be directed towards recycling. The agent also provides recommendations to CMs and logistics partners for optimal handling.

5.??????? Learning and Optimization: After the return process is completed, the IA’s stores the outcome in its database, continuously learning from the results. This learning is crucial for recognizing patterns in return reasons, improving the accuracy of future assessments, and providing insights to manufacturers to enhance product design and reduce return rates.

6.??????? Feedback Loop: The IA’s provide a feedback loop to the company by generating reports and insights. These insights can be used to refine product quality, adjust warranty policies, and identify common issues that lead to returns. This feedback loop ultimately helps companies make data-driven improvements across their product lines.

Furthermore, our IA’s continuously learn from historical returns data, recognizing recurring patterns in failure points or customer complaints. This learning allows them to assist Contract Manufacturers (CMs) by providing insights that can minimize the repair time and improve overall product quality. By reducing NFF returns, they help prevent unnecessary transport, handling, and inspection costs—all of which contribute to a more sustainable returns operation.

In essence, Tallgrass’ IA’s don't just manage returns—they add value throughout the product lifecycle. By reducing processing times, ensuring accurate triage, and supporting sustainability goals, they turn what was once a burdensome process into a powerful opportunity for customer satisfaction and cost optimization.

Tallgrass does so more - interested to see where we can serve you in your Circular Logistics efforts?

Contact us: [email protected]

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