Challenge

Teledyne LeCroy manufactures electronic test and measurement instruments used across research, design, and engineering applications worldwide. Their post-sale motion includes extended warranty upsell — a revenue stream that depends entirely on having accurate, up-to-date product and asset data linked to the right customer accounts in Salesforce. The data that made that possible lived in a custom ERP. Getting it into Salesforce was a manual process: someone had to extract the product data from the ERP, clean it, transform it into a format Salesforce could accept, and load it — a cycle that took 3–4 days every time it ran. The process was not just slow. It was inflexible and error-prone. Because it relied on manual execution at every step, it was difficult to replicate consistently across different product lines or asset types. Serial numbers — the specific asset identifiers that sales needed to match a product to a buyer record and execute an upsell — were often missing or incorrectly linked in Salesforce by the time the data arrived. Sales teams trying to work extended warranty opportunities were doing so with CRM data that was days out of date and incomplete at the record level.

Solution

Teledyne LeCroy deployed Openprise to build a fully automated data bridge between their custom ERP and Salesforce. The architecture replaced every manual step in the existing sync process: Openprise pulls product data directly from the ERP, processes and transforms it through a no-code orchestration workflow, and creates or updates records in Salesforce automatically — with asset data including serial numbers correctly linked to the corresponding buyer records. The entire cycle that had taken 3–4 days now runs in 45 minutes. The process is consistent, repeatable, and requires no human intervention to execute.

The critical design requirement was not just speed — it was accuracy of the asset linkage. For extended warranty upsell to work, the serial number and product record in Salesforce had to be connected to the right buyer account. Openprise's data bridge handled that matching logic as part of the orchestration workflow, ensuring that the asset data arriving in Salesforce was not just present but correctly associated with the buyer records sales needed to act on. Within the first few months of live implementation, the bridge had created more than 30,000 new records in Salesforce — the majority being the critical asset data that had previously been missing or unreliable.

Impact

The most immediate change was speed. A 3–4 day manual process became a 45-minute automated one. That compression is not just an operational improvement — it changes what is possible in the sales motion. When product and asset data is available in Salesforce within 45 minutes of an ERP update rather than several days later, the window for extended warranty outreach opens at the right moment. Sales is no longer working from data that is days old when they make upsell contact.

The 30,000+ asset records created in Salesforce in the first few months of implementation represent the cumulative backfill of data that had been missing or incorrectly linked before Openprise. Serial numbers, product identifiers, and asset details that sales needed to execute upsell targeting were now in the system, correctly associated with buyer records, and maintained automatically as new data flowed from the ERP. The upsell motion that had been constrained by incomplete CRM data could now operate on a reliable, current picture of what each customer owned.

The elimination of the manual sync process removed an ongoing operational liability. Manual data processes do not just cost time — they introduce variability. Every manual step is a point where errors can enter, data can be lost, and consistency can break down. Openprise's automated data bridge removed those failure points entirely. The sync runs on a defined schedule, applies consistent transformation logic every time, and produces a predictable, auditable output in Salesforce. The Ops team no longer needs to manage or monitor the process — it manages itself.