Aftermarket data wins: How Dayco mastered ACES

Dayco secured the ACPN Receiver's Choice Content Excellence Award by mastering ACES and PIES data standards for the HDA Truck Pride Network. This isn't just a plaque on the wall; it is proof that rigorous adherence to standardized aftermarket product data drives operational efficiency for distributors and service providers. The industry has zero patience for guesswork when precise digital frameworks exist to eliminate errors in parts identification.

This analysis breaks down how the Aftermarket Catalog Exchange Standard manages complex fitment data for over 60,000 vehicle combinations across light, medium, and heavy-duty sectors. We will examine Dayco's strategic implementation of these high-quality standards to ensure completeness and communication excellence.

Reliable information flow remains non-negotiable for the more than 1,000 distribution locations supported by substantial networks. Companies failing to prioritize these digital exchange protocols risk obsolescence as partners demand the precision demonstrated by award-winning suppliers. The path forward requires an unwavering commitment to the technical details of product information management.

The Critical Role of Standardized Aftermarket Product Data

ACES and PIES Data Standards Set

The Aftermarket Catalog Exchange Standard handles fitment for over 60,000 vehicle combinations across light, medium, and heavy-duty sectors. This framework resolves Year/Make/Model compatibility so parts map correctly to vehicle configurations without manual intervention. Distinct from fitment logic, the Product Information Exchange Standard governs physical product attributes like pricing, dimensions, and materials. Now at version 8.0, PIES provides the descriptive metadata required for inventory management and logistics planning.

These two frameworks operate as complementary systems rather than interchangeable formats. ACES answers whether a part fits a specific truck. PIES defines what that part physically is. This functional division prevents the data silos common in proprietary systems, enabling smooth exchange between manufacturers and distributors. The Auto Care Association's 2026 data standards update marks a scheduled evolution in this technical framework, refining how suppliers communicate complex specifications.

High-quality data delivery directly impacts the ability of networks like HDA Truck Pride to identify correct parts quickly. Distributors and service providers require standardized information to deliver parts without delay.

HDA Truck Pride Receiver's Choice Award Criteria

The ACPN Receiver's Choice Content Excellence Award validates supplier performance through rigorous evaluation of data completeness, accuracy, delivery, and communication. Presented at the Auto Care Connect event, this recognition serves as a functional benchmark for the heavy-duty aftermarket. Unlike generic quality assurances, the criteria demand strict adherence to ACES and PIES protocols to ensure smooth parts identification across complex supply chains. The HDA Truck Pride Network uses its footprint of over 1,000 distribution locations to assess how well vendor data integrates with real-world operational workflows.

Winners like Dayco Incorporated demonstrate that high-fidelity data reduces friction between manufacturers and distributors. Suppliers must treat data governance as a core engineering constraint. Networks prioritize partners who maintain flawless digital twins of their physical inventory.

Validating Aftermarket Data Completeness and Accuracy

Suppliers adopt ACES and PIES to satisfy the completeness criteria used by substantial distributors to rank vendor performance.

Receivers evaluate submissions against four pillars: data completeness, accuracy, delivery timeliness, and communication responsiveness. This flexible approach encourages suppliers to prioritize data accuracy to maintain competitive shelf space within distributor inventories.

Programs like the Star Awards confirm that distributors are institutionalizing these metrics to filter supplier quality.

How Data Accuracy Drives Distributor and Service Provider Efficiency

How ACES and PIES Standards Prevent Part Misidentification (Mechanics Perspective)

Standardized structures remove fitment ambiguity by separating vehicle application logic from product attribute definitions. The ACES framework maps specific parts to precise vehicle configurations, while PIES manages detailed product characteristics like weight and packaging dimensions. This technical separation ensures distributors receive exact fitment information rather than generic descriptions that often lead to errors.

Dayco exemplifies this operational discipline by earning the ACPN Receiver's Choice Content Excellence Award from the HDA Truck Pride Network. Jake Telep, a Data Analyst for the network, noted that high-quality data delivery directly enables efficient operations for channel partners and end users. The Auto Care Association's 2026 data standards update marks a specific, scheduled evolution in the industry's technical framework that further solidifies these requirements. Maintaining rigorous data completeness across thousands of SKUs requires significant investment in validation tools and processes. This commitment allows organizations to achieve the deep accuracy required for award-level recognition. Precise mapping prevents logistical issues by ensuring the correct parts are identified and delivered quickly to service bays.

Resolving Delivery Errors Through Supplier Data Collaboration

Accurate part identification at distribution centers relies on thorough vehicle application logic within supplier data feeds. When ACES fitment records include specific engine codes and model years, warehouse staff can efficiently process orders without ambiguity. Reliable data streams allow distributors to maintain shipment schedules while trusting digital claims, minimizing delays in the supply chain.

Collaborative data remediation addresses potential failures by aligning supplier outputs with receiver requirements before transmission. Effective data management involves several key technical steps to ensure integrity:

• Validate engine codes against model years
• Cross-reference packaging dimensions with warehouse constraints
• Verify weight data against shipping manifests
• Confirm communication protocols for error reporting
• Audit completeness scores prior to transmission

Validating Supplier Data Against Receiver's Choice Criteria

Distributors evaluate supplier feeds based on four specific pillars: data completeness, accuracy, delivery, and communication.

These metrics form the baseline for the Receiver's Choice Content Excellence Award granted by HDA Truck Pride. Operators can deploy the following validation workflow to assess partner performance:

1. Verify ACES records contain full vehicle application logic without gaps.
2. Cross-reference PIES attributes like weight and dimensions against physical inventory.

Superior adherence to these standards directly reduces misidentified shipments at distribution centers. A tension exists between rapid catalog expansion and rigid data validation protocols. Suppliers demonstrating strong validation performance gain recognition as valued partners, while those with poor data hygiene risk operational inefficiencies. This flexible approach forces a choice between speed-to-market and long-term partner reliability. Organizations maintaining strict communication loops avoid the operational drag of manual data remediation.

Dayco's Strategic Implementation of High-Quality Data Standards

Application: Defining Content Excellence via ACES and PIES Standards

Presented at the Auto Care Connect event, the Receiver's Choice Award specifically recognizes suppliers that demonstrate excellence in data completeness, accuracy, delivery, and communication through ACES and PIES standards. This recognition honors the company's performance in delivering high-quality aftermarket product data, moving beyond basic compliance to evaluate how effectively aftermarket content receivers can apply supplier data for operational success. The HDA Truck Pride Platform defines content excellence through four measurable pillars: data completeness, accuracy, delivery, and communication.

Dustin Anderson, Dayco North America Aftermarket Heavy-Duty Sales Manager, noted that distributors rely on this product content daily to find parts quickly. High-quality data prevents costly shipping errors and reduces manual verification labor at the distribution center. Maintaining high standards requires consistent effort from channel partners to ensure data accuracy and accessibility. Suppliers aim to balance broad publishing with the precision necessary for award-level performance. Dayco's approach demonstrates that strict adherence to industry standards yields tangible efficiency gains for the entire supply chain.

Dayco's Strategic Investment in Data Accuracy and Accessibility

Dayco maintains operational velocity by investing continuously in ACES and PIES framework adherence to support daily parts identification. Distributors and end users rely on product content every day to find the right parts quickly, making data accessibility a vital component of their operations. This dependency creates a direct link between supplier data hygiene and the speed of commercial vehicle repair.

The organization treats data completeness, accuracy, delivery, and communication as interconnected pillars of supply chain performance. Evaluation by aftermarket content receivers confirms that high-quality exchanges reduce friction in the distribution network. Dayco will continue to invest in industry standards focused on content excellence, data accuracy and accessibility to meet these evolving expectations. Such commitment ensures that catalog systems receive consistent signals, preventing downstream errors in inventory management.

Ensuring new SKUs meet full ACES attribute requirements is necessary to avoid manual verification by distributors, preserving the efficiency the data aims to create. Delays or errors in this process can lead to increased support needs and slower fulfillment rates across the HDA Truck Pride System. Prioritizing validation over speed at the source eliminates these manual reconciliation steps later in the chain. This approach transforms data from a static record into an active enabler of logistics efficiency.

Receiver-Driven Validation Steps for Aftermarket Data Quality

Receivers validate supplier performance by auditing data completeness and accuracy against key criteria critical to successful data exchange. This process separates market leaders from those who merely meet minimum viability standards for catalog entries. Content receivers evaluate four distinct pillars to determine if a supplier deserves partnership status.

Top-tier networks maintain flexible delivery expectations that generic suppliers often struggle to meet. This limitation creates friction when distributors attempt rapid parts identification during service windows. The shift toward flexible exchange means static data files are increasingly insufficient for modern supply chain requirements. Suppliers ignoring this transition risk falling behind competitors who use strong protocols.

The implicit cost of non-compliance manifests as lower ranking in distributor catalogs rather than direct fines. Market access diminishes when data quality cannot support automated ordering systems used by large networks. Operators must treat data hygiene as a core competency to maintain competitive positioning. Failure to adapt results in exclusions from preferred vendor lists managed by substantial distribution groups.

Executing ACES and PIES Compliance for Supply Chain Success

Defining Receiver-Driven Data Excellence Metrics

Receiver-driven metrics prioritize data completeness, accuracy, delivery, and communication as the four pillars of supplier evaluation. Distributors like HDA Truck Pride assess these attributes to ensure parts are identified correctly and delivered without delay. The ACPN Receiver's Choice Content Excellence Award is determined by aftermarket content receivers who evaluate supplier performance across these key criteria critical to successful data exchange.

1. Verify product records match vehicle application guides using ACES.
2. Audit attribute coverage in PIES files to ensure thorough product information.
3. Monitor delivery logs for timely submission of updates and change notifications.
4. Track communication responsiveness when receivers flag discrepancies or missing attributes.

Suppliers must treat content excellence as a continuous operational requirement, not a one-time certification event. Their team consistently delivers high-quality ACES and PIES data while maintaining strong communication and responsiveness. Consistent adherence to these criteria builds trust with network partners.

Operationalizing ACES and PIES for Rapid Part Identification

Suppliers align internal catalogs with ACES and PIES version specifications to enable immediate part discovery.

This structured approach ensures that distributors and end users rely on product content every day to find the right parts quickly. The investment in maintaining compliance supports the goal of getting the right part to the right place at the right time, directly linking data quality to inventory turnover rates and reduced return costs. Companies may engage third-party services to meet the rigorous standards required for recognition.

Strict adherence helps balance speed-to-market and data perfection. Distributors evaluating supplier performance look for data completeness alongside volume, valuing vendors who provide verified fitment claims. The operational cost of fixing returned inventory due to bad data can exceed the resource burden of initial validation. Success requires treating data as a manufactured component rather than an administrative afterthought.

Supplier Checklist for Content Completeness and Collaboration

Suppliers validate data completeness against receiver schemas before every transmission cycle.

1. Cross-reference ACES vehicle records with the latest industry database version to eliminate fitment gaps.
2. Audit PIES attribute coverage to ensure no critical product specifications remain undefined.
3. Automate delivery logs for timely submission of updates and change notifications.
4. Maintain open communication channels for rapid resolution of data discrepancy tickets.

References

• AWDA’s honorees have reflected the leadership, service and innovation