CUSTOMER USE CASE
WAAT Automated Its Quote-to-Invoice Process and Saved 83 Hours in Under 3 Months
About WAAT
WAAT is a French leader in electric vehicle charging infrastructure, supporting residential co-ownerships, social housing providers, businesses, and individuals in deploying charging stations across France. Positioned at the heart of the energy transition, WAAT operates large-scale projects with high operational complexity, requiring robust, automated, and fully trackable processes.
Their Objective
At WAAT, ERP data forms the backbone of business and administrative operations. As the company grew, so did the volume of files to process, making reliable, scalable workflows essential.
They needed to automate its quote-to-invoice conversion process, while centralizing data from multiple sources and giving teams clear, real-time visibility into what had been processed, and what had not.
What was getting in the way:
- A time-consuming manual conversion process: Converting quotes into invoices relied on a sequence of manual steps requiring successive verifications, field updates, and functional checks. Each file took at least 5 minutes to process, keeping several team members tied up on low-value tasks.
- Strict and complex business rules to enforce: Processing required cross-referencing data from multiple tools, including the Sellsy ERP and third-party platforms such as Advenir, while applying very precise business rules. Consistency checks and exclusion cases made the process difficult to standardize without fine-grained orchestration.
- No reliable way to track quote status: Before ClicData, it was difficult to know which quotes had been processed, which had been excluded, and why. Teams had to run manual checks just to understand the real state of billing operations, adding overhead to an already heavy daily workload.
“It was a process that took 5 minutes per quote to convert into an invoice. There were quite a few steps, simple ones, but a large number of them. And in the end it really was 5 minutes per file, with 2 to 3 people working on it.”
Their Approach
With ClicData, WAAT rebuilt its entire quote-to-invoice workflow into a single automated pipeline, centralizing data from multiple sources and delivering daily reporting to business teams without any manual intervention.
- Full process automation from end to end: The 10 manual conversion steps were replaced by a single workflow made up of 30 robust automated tasks built inside ClicData. These tasks rely on key building blocks including API connectors, Data Flows, and data historization. Quote extraction, business rule application, invoice creation, and report distribution to teams now run every day without human involvement.
- Enriched data from multiple sources: The flexibility of the Web Service connector allowed WAAT to schedule complex scenarios via the ERP API, both in read and write mode. Quote data is enriched with information from the Advenir financing platform and charging station supervision systems, giving a complete and reliable view of each file.
- 83 hours saved in under 3 months: By eliminating repetitive manual tasks and time-consuming verifications, WAAT freed up the equivalent of more than two full working weeks in less than three months. Business teams can now focus on higher-value activities, while technical teams avoid lengthy and costly custom development.
- Clear visibility and stronger operational control: Automation systematically applies business rules with high reliability and generates a detailed processing log. Teams now have a clear view of which quotes have been processed, excluded, or flagged for correction, making daily billing management significantly easier and more trustworthy.
“By using advanced Data Flows and well-structured schedules, you can build truly complex processes with ClicData. This 38-step automation is far from simple. It is enormous in terms of data cross-referencing, multiple sources, outputs created, and API calls made. It has been running for 3 months, it is pretty robust, and the end users are genuinely very happy.”
