Streamline Warranty Claims with Decision Intelligence

Automotive manufacturers have spent billions of dollars on digital transformation initiatives over the last 20 years, but the ratio of warranty costs to revenue has not shown any significant improvement. Those Industry 4.0 investments went primarily into production operations and provided a ~15%-20% average improvement in overall equipment efficiency (OEE), but quality and warranty have not significantly benefited. One major reason for inefficient warranty claims is the time lag between receiving warranty claims data and initiating problem solving.

It’s important to understand the difference between express and implied warranties when considering warranty claims. The Magnuson-Moss Warranty Act of 1975 sets standards for consumer product warranties, protecting buyers from fraud and misrepresentations. An express warranty is a guarantee from a seller or manufacturer to a buyer that the purchased product will perform according to certain specifications, and these promises are typically documented in writing. An implied warranty, on the other hand, is a guarantee that the product functions as designed, even if not explicitly stated. The implied warranty ensures that a product is fit for its general purpose and functions as expected, unless specifically excluded. Warranty terms and conditions must be fully and clearly disclosed in writing to the buyer before they buy a product, ensuring legal enforceability and clarity.

For example, if a consumer buys a new car and the product fails due to a manufacturing defect within the warranty period, the buyer can file a warranty claim to have the issue repaired or the product replaced according to the terms set out in the written warranty. Express warranties are specific, documented promises made by manufacturers or sellers, and having these warranties in writing is crucial for legal protection if disputes arise.

Lags in warranty claims resolution occur due to manual assessment processes. The warranty claims process starts when a customer files a claim under the warranty policy. Customer claims data requires transformation and normalization, and it takes time to collect plant quality data (like corrective action implementation dates) for validation. Manual assessment often requires gathering original purchase receipts, warranty agreements, serial numbers, and maintenance records. Repairs must be reported immediately, as delays can result in denied claims if the issue is deemed a result of neglect. Companies often deny claims if maintenance history cannot be proven according to manufacturer guidelines. Other causes include complex manual workflows, the need for manual data entry and file uploads, and disparate data systems that require integration. Here’s how the process works:

• Businesses must check and validate claim details—often through an audit check—to ensure the product is within the warranty period and meets policy conditions.
• After validation, businesses assess the issue to determine if it falls under the warranty's coverage.
• Once the assessment is complete, the business processes the claim, including documentation and communication with the customer.
• It typically takes several weeks from receipt of initial customer claims until problem solving is initiated – time that could be spent solving the problem and preventing future claims.

Streamlining warranty claims impacts multiple facets of the business, from supply chain to operations. A good warranty provides assurance to consumers that the goods they purchase are as advertised, offering a structured recourse should issues arise. But ignoring data lags and continuing with the status quo results in a number of negative consequences, including financial and brand burdens. The result of inefficient warranty claims can undermine consumer trust and satisfaction.

• Locked capital: When claim resolution is delayed and warranty costs exceed accruals, profits suffer and can impact stock price.
• Higher labor costs: Delayed claims require more employee time to manage, which increases labor expenses.
• Delayed reimbursements: For both manufacturers and their service providers, a slow claim process means delayed reimbursement for repairs and parts.

• Customer satisfaction: When a warranty claim takes an extended amount of time, customers become dissatisfied and may question whether the manufacturer stands behind their products.
• Public perception: Warranty data lags do not allow a manufacturer to get ahead of a significant problem, which could turn into a global recall of a product or component.

But streamlining warranty claims is easier said than done. There are significant data challenges that hinder the process. These include data lags, inconsistent data reporting, missing or incomplete data, unstructured text data, and data quality issues. There are additional challenges that auto manufacturers face in their warranty claims processes including vehicle technology complexities, evolving component reliability, usage, and environmental factors, supplier inconsistencies, and changing regulations.

Streamlining warranty claims data analysis requires the integration of disparate quality and operations data, and AI-enabled decision intelligence. By automating data preparation and reporting, manufacturers can gain immediate analysis of customer warranty claims resulting in faster time to issue resolution. By leveraging real-time quality data, claims reserve predictions are more accurate. For example, reducing the time it takes to prepare and assess customer claims data and begin problem solving by four weeks equates to an 8% annual cost reduction. To put that number in perspective, in 2023 (the most recent year for which numbers are available), worldwide automakers made total warranty accruals of $65 billion. At 8% cost reduction, that equates to $5.2 billion in savings.

These two complementary technologies can help. They enable faster data integration, harmonization, and sharing across supplier networks.

InterSystems Supply Chain Orchestrator™ is an AI-enabled supply chain decision intelligence platform built to solve your supply chain problems. It unifies disparate data sources by providing a real-time connective tissue—with built-in predictive and prescriptive analytics—that’s complementary and non-disruptive to your existing infrastructure.

InterSystems Data Studio™ delivers unified and timely data, empowering supply chain practitioners to make better decisions faster. This low-code, self-service data gateway makes it quicker and simpler to integrate, harmonize, and normalize disparate data and deliver it to the right consuming users and applications at the right time and in the proper format. It serves as the front-end data gateway to harmonize and onboard data to Supply Chain Orchestrator.

• Unlock working capital: Long claim resolution cycles mean more claims and higher warranty reserves tying up capital.
• Reduce labor costs: Delayed claims require more employee time to manage, which increases labor expenses.
• Accelerate reimbursements: For both manufacturers and their service providers, a slow claim process means delayed reimbursement for repairs and parts.
• Get ahead of product recalls: Warranty data lags prevent manufacturers from getting ahead of a significant problem, which could turn into a global recall of a product or component.

Warranty is a data problem disguised as a process problem. Decision intelligence speeds up warranty claims by eliminating manual reviews, bottlenecks, and enabling real-time, risk-based decisions across dealers, OEMs, and suppliers. In the end, it transforms warranty from a reactive cost center into a predictive quality and financial control function. Learn more about streamlining the warranty claims process here.