Nov 14, 2023
Cleansing Data,
Classification,
Spend Rationalization,
Ecommerce,
PIM,
Taxonomy,
HVAC,
Product Data,
Service Parts,
Aftermarket Parts,
Procurement,
Digital Commerce,
Sourcing,
Mergers & Acquisitions,
Product Information Management,
Distributor,
OEM,
Data Integration,
Digital Thread,
Digital Transformation,
Acquisition Onboarding
Common OEM and Distributor Data Challenges: 2023 in Review
💪 For OEMs and Distributors, staying competitive in today's rapidly evolving digital landscape is crucial. With the rise of eCommerce and digital initiatives, customers and channel partners now expect a seamless and streamlined experience that offers accurate, up-to-date product information and inventory availability.
💡 To meet these demands, OEMs and Distributors can benefit greatly from centralizing their product and service parts data. By doing so, they can provide their customers with a holistic digital experience that drives revenue through increased sales, reduced returns, and improved customer satisfaction overall.
In this blog post, we explore some of the common challenges OEMs and distributors across many industry segments have shared with us in 2023:
| Key Challenges | Examples of Common Pain Points |
| Data Quality | Product and service parts data is incomplete, inaccurate, or outdated, making it difficult to analyze data, make decisions, or use it across teams and systems such as eCommerce, Aftermarket, and Sourcing, and Engineering. |
| Static Data Siloes | Data is stored in siloes that are not integrated and are scattered across the organization. It's common to see multiple divisions entering the same data more than once. Data is also wrangled in Excel files and PDFs across disparate teams - an error-prone and manual process. |
| Data Trapped in Legacy PIMs and Homegrown Data Solutions | Many traditional PIM solutions have rigid data models that aren't flexible or scale as business lines grow and new categories are added. Managing the data at scale and exporting it to downstream Distributors and channel partners tends to be a manual process, reliant on scripting and custom development. In addition, the longer-term maintenance of these legacy solutions is managed by in-house IT staff and systems integrators, a support structure that is typically cost prohibitive and inefficient. |
| Getting Timely Data from OEM to Distributors | While OEMs struggle to export their item data out of legacy PIM and other data solutions to downstream channels, Distributors recognize that their ease of going to market often hinges on the readiness, overall quality, and ease of receiving and ingesting data from OEMs. The data lifecycle from OEM to Distributors is typically complex and requires heavy manipulation to ultimately prepare it for customer-facing platforms. |
| Lack of Governance | The inability to optimize data input and validation means that data is managed reactively, creating change management headaches. Digital Marketing, eCommerce, Sourcing, and other teams may also struggle to find and leverage products and service parts data due to manual and inconsistent data management practices and a lack of standardized processes. |
| Meeting Customer Demand | Order fulfillment may be slow due to challenges finding the right service parts and products due to inconsistent categorization and lack of available attribution data. In addition, if relationship data is not established, the team may also struggle to identify alternative parts (if one part is not available) or related items (such as accessories) to meet order requirements. |
| Onboarding Acquisition Data | Acquisitions typically bring with them their own technology stack, data, and complexity. Most organizations struggle with onboarding the parts and products data from acquisitions and incorporating them into ERP, PLM PIM, and eCommerce systems. To achieve true economies of scale, it will be necessary to integrate operations, which includes the reconciliation of parts and product data models. |
| Supply Chain Management | The lack of timely, complete, accurate, and actionable data makes it difficult to manage inventory levels, estimate customer lead leads, meet customer demand, and foster stronger relationships with suppliers and downstream partners. |
| Managing Spend Effectively | Decentralized procurement processes and a lack of data integration across different systems, categories, suppliers, and locations can present challenges in identifying opportunities to reduce costs (which would include performing a spend roll-up, consolidating suppliers, negotiating better prices with suppliers, and optimizing procurement processes). |
Do these challenges sound familiar? If your team is looking for help or suggestions on how to tackle your data challenges, let's get in touch! ✍️