We built an SAP-connected reporting pipeline that automates stock data ingestion, validation, and report generation - turning a 5–6 hour manual process into a report delivered in under four minutes with data discrepancies below 1%.
The new workflow gave the plant a consistent, near-real-time view of inventory while removing the need for dedicated staff to rebuild reports. SAP-aligned validation and automated exception handling also helped ensure that only verified data reached the final report.
A manufacturing facility was managing more than 200 daily material transactions across 80+ material codes. Its operations team relied heavily on spreadsheets and manual data entry to prepare twice-daily stock reports, making the process slow, difficult to scale, and prone to errors.
Two staff spent four to six hours on it, cross-referencing handwritten intake logs against master code spreadsheets, and the report still reached management three to five hours behind reality.
We built an automated data pipeline that ingests, maps, validates and delivers the report in under four minutes. The discrepancies fell from around 13% to under 1%.
"What do the two people who used to build this report do, six weeks after go-live?"
Handling the raw materials data is one of the key processes of our business. We had hired two persons who understood the gravity of correct data entry, which worked well until we started receiving more orders that demanded diverse materials regularly. Tracking all of them across sheets and co-relating it all to identify the position and manufacturing needs were all heavily time-consuming.
Comparatively, today, those two now have the freedom to join the workforce for competing with global clients, without data loss or such issues.
Twice each day, before every shift, the plant needed an accurate picture of available raw materials and upcoming requirements. Getting this information had become a four-to-six-hour manual exercise that produced a report nobody fully trusted.
Material arrivals were logged by hand while consumption was recorded elsewhere, leaving the plant with fragmented inputs that had to be reconciled manually before each report.
The reporting team relied on spreadsheets alongside the client’s SAP ERP material master, creating duplicate reference points that had to be manually reconciled across 200-plus daily transactions.
Two staffers cross-referenced handwritten intake logs against spreadsheets, reconciled weight discrepancies, and rebuilt the same report format from scratch for every shift.
Manual cross-referencing at scale produced discrepancies in roughly 13% of the data, including mismatched codes, weight variances and duplicate entries. By the time the report reached plant management, it lagged live operations by three to five hours.
We built an end-to-end SAP-connected pipeline that ingests, maps, validates, and publishes the stock report without requiring anyone to manually rebuild it in a spreadsheet. The report is scheduled to be delivered 30 minutes before each shift starts.
The pipeline ingests extracts from SAP ERP and supporting intake sources through CSV and SFTP connectors, capturing material-arrival and consumption data in near real time. It handles 200+ daily transactions with built-in retry logic.
The engine cross-references every incoming entry against a version-controlled material-master layer aligned to SAP material codes and flags mismatches for human review. When a material code changes, the update propagates to every future report automatically.
Once entries are validated, the system compiles the report in the plant’s existing standardised format and delivers it to key personnel thirty minutes before each shift. This created a consistent reporting layer across SAP and related source data without requiring users to change a familiar report layout.
A near-real-time view of stock levels, consumption trends, and incoming material was available in one click, with visual alerts when inventory dropped below a safety threshold. Procurement no longer had to wait for a report to learn about a shortage.
Anomaly detection runs across the pipeline for mismatched codes, weight variances and duplicate entries. Flagged items go to a person while validated ones flow through. This is where discrepancies fell from 13% to under 1% without removing human judgment from cases that need it.
The engagement included staff handover training and documentation. The two people who used to build the report by hand now own the exception queue.
Manual reporting that previously took 5–6 hours was reduced to under four minutes, with the report ready before every shift and delivered 100% on time. Automated SAP-aligned material mapping reduced data discrepancies from around 13% to under 1%, while exceptions were routed for review instead of affecting the report.
| Before | After | |
|---|---|---|
| Report generation time | 5-6 hours | Under 4 minutes |
| Staff on reporting | 2 dedicated | 0 dedicated |
| Data discrepancies | ~13% | Under 1% |
| Report lag | 3-5 hours behind | Near Real-time |
| Deadline adherence | Missed | 100% on time |
| Shortage awareness | Next scheduled report | Threshold alert on occurrence |
| Master code updates | Manual, error-prone | Version-controlled and automatically propagated |
| SAP data reconciliation | Manual cross-checking across sources | Automated validation and exception routing |
We can map your current reporting workflow, identify manual reconciliation points, and scope an SAP-connected automation pipeline for faster, more reliable operational reporting.
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