SRD ENTERPRISES
SRD ENTERPRISES
SRD ENTERPRISES
From scattered sheets to one workflow: SRD ENTERPRISES's ops reset

From scattered sheets to one workflow: SRD ENTERPRISES's ops reset

From scattered sheets to one workflow: SRD ENTERPRISES's ops reset

Standardising approvals and handovers so teams work off the same numbers.

54%

Reduction in daily coordination time for auto ancillary work

54%

Reduction in daily coordination time for auto ancillary work

30%

Reduction in excess inventory across store and production

30%

Reduction in excess inventory across store and production

8→3 days

Improvement in order-to-dispatch lead time with fewer last-minute follow-ups

8→3 days

Improvement in order-to-dispatch lead time with fewer last-minute follow-ups

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About SRD ENTERPRISES

About SRD ENTERPRISES

SRD ENTERPRISES is a small auto ancillary manufacturing unit based in Pune. Their day-to-day work involves coordinating orders, material availability, production execution and dispatch commitments. Earlier, updates were shared through a mix of Excel sheets, calls and WhatsApp, which made it hard to keep everyone aligned. By moving to a centralised workflow, the team standardised handovers, reduced rework in reporting, and improved execution predictability.

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Auto Ancillary

Industry

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Auto Ancillary

Industry

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Small

Company Size

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Small

Company Size

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Pune, India

Location

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Pune, India

Location

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PO-linked production planning + vendor scheduling

Use Cases

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PO-linked production planning + vendor scheduling

Use Cases

Challenges

Job-work material sent out was tracked in registers; return quantity and shortages were unclear.

Month-end reporting became a rework exercise because data lived in multiple files and chats.

PO approvals got stuck with managers, leading to last-minute buying and frequent expedite.

Implementation: Centralised workflow with clear owners

Implementation: Centralised workflow with clear owners

Implementation: Centralised workflow with clear owners

Earlier, job-work material movement was tracked in registers and return status was unclear. This broke down on returns; shortages and rate differences led to repeated reconciliations. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Material sent out and received back was logged against job-work orders, making shortages visible immediately. For auto ancillary operations in Pune, this reduced dependence on a single person for updates. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

Earlier, job-work material movement was tracked in registers and return status was unclear. This broke down on returns; shortages and rate differences led to repeated reconciliations. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Material sent out and received back was logged against job-work orders, making shortages visible immediately. For auto ancillary operations in Pune, this reduced dependence on a single person for updates. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

Cleaning masters to make reports match reality

Cleaning masters to make reports match reality

Cleaning masters to make reports match reality

Earlier, masters and transactions were split across Excel, accounting exports and WhatsApp updates. This broke down at month-end; teams rebuilt the same report multiple times and still debated the numbers. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. Masters were cleaned once, and daily reporting pulled from the same transactions instead of manual consolidation. Over time, the team built confidence because the numbers matched what they saw on the floor. The practical outcome was smoother handovers between departments and more predictable daily execution.

Earlier, masters and transactions were split across Excel, accounting exports and WhatsApp updates. This broke down at month-end; teams rebuilt the same report multiple times and still debated the numbers. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. Masters were cleaned once, and daily reporting pulled from the same transactions instead of manual consolidation. Over time, the team built confidence because the numbers matched what they saw on the floor. The practical outcome was smoother handovers between departments and more predictable daily execution.

Reducing month-end surprises with traceable transactions

Reducing month-end surprises with traceable transactions

Reducing month-end surprises with traceable transactions

Earlier, vendor follow-ups were call-driven and depended on whoever remembered to push. This broke down during peak load—approvals got delayed and committed dates slipped without a simple exception view. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. For auto ancillary operations in Pune, this reduced dependence on a single person for updates. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

Earlier, vendor follow-ups were call-driven and depended on whoever remembered to push. This broke down during peak load—approvals got delayed and committed dates slipped without a simple exception view. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. For auto ancillary operations in Pune, this reduced dependence on a single person for updates. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

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