Prabhat Elastomers Pvt. Ltd.
Prabhat Elastomers Pvt. Ltd.
Prabhat Elastomers Pvt. Ltd.
From scattered sheets to one workflow: Prabhat Elastomers Pvt. Ltd.'s ops reset

From scattered sheets to one workflow: Prabhat Elastomers Pvt. Ltd.'s ops reset

From scattered sheets to one workflow: Prabhat Elastomers Pvt. Ltd.'s ops reset

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

47%

Reduction in daily coordination time for fabrication work

47%

Reduction in daily coordination time for fabrication work

30%

Reduction in excess inventory across store and production

30%

Reduction in excess inventory across store and production

4→3 days

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

4→3 days

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

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About Prabhat Elastomers Pvt. Ltd.

About Prabhat Elastomers Pvt. Ltd.

Prabhat Elastomers Pvt. Ltd. is a small fabrication manufacturing unit based in Valsad. 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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Fabrication

Industry

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Fabrication

Industry

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Small

Company Size

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Small

Company Size

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Valsad, India

Location

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Valsad, India

Location

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Raw material cutting plan + WIP visibility

Use Cases

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Raw material cutting plan + WIP visibility

Use Cases

Challenges

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

Vendor committed dates were verbal; delays were discovered only after repeated calls.

Store stock looked fine on paper but production bins were empty when job cards started.

Dispatch readiness built into the daily routine

Dispatch readiness built into the daily routine

Dispatch readiness built into the daily routine

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. 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. The practical outcome was smoother handovers between departments and more predictable daily execution.

Before: Too many moving parts, no single view

Before: Too many moving parts, no single view

Before: Too many moving parts, no single view

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 structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. It also made owner reviews easier because key exceptions were visible without chasing the team. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

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 structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. It also made owner reviews easier because key exceptions were visible without chasing the team. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

Vendor coordination with structured PO follow-ups

Vendor coordination with structured PO follow-ups

Vendor coordination with structured PO follow-ups

Earlier, store stock, WIP and finished goods were tracked in separate sheets and message threads. This broke down whenever priorities changed—material looked available, but the line stalled due to bin-level shortages. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. Supervisors started reviewing shortages at shift start and raised purchase/transfer requests before the line was blocked. 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, store stock, WIP and finished goods were tracked in separate sheets and message threads. This broke down whenever priorities changed—material looked available, but the line stalled due to bin-level shortages. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. Supervisors started reviewing shortages at shift start and raised purchase/transfer requests before the line was blocked. 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.

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