WESTERN ENGINEERING
WESTERN ENGINEERING
WESTERN ENGINEERING
WESTERN ENGINEERING tightened shop-floor control with a centralised workflow

WESTERN ENGINEERING tightened shop-floor control with a centralised workflow

WESTERN ENGINEERING tightened shop-floor control with a centralised workflow

Turning daily follow-ups into a repeatable workflow across departments.

48%

Reduction in daily coordination time for engineering work

48%

Reduction in daily coordination time for engineering work

25%

Reduction in excess inventory across store and production

25%

Reduction in excess inventory across store and production

6→2 days

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

6→2 days

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

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About WESTERN ENGINEERING

About WESTERN ENGINEERING

WESTERN ENGINEERING is a small engineering 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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Engineering

Industry

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Engineering

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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Quotation-to-order conversion + dispatch coordination

Use Cases

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Quotation-to-order conversion + dispatch coordination

Use Cases

Challenges

Production plan changed multiple times a day due to capacity conflicts and material gaps.

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

Same item had different names in Excel and accounting exports, so reports never matched store reality.

After: Predictable execution, fewer escalations

After: Predictable execution, fewer escalations

After: Predictable execution, fewer escalations

Earlier, the daily plan was decided in fragments—by urgency, not by capacity and material signals. This broke down as soon as urgent orders came in; jobs were half-started and WIP piled up across stages. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. Planning moved to a simple daily schedule linked to orders, capacity and material, reducing last-minute reshuffles. For engineering operations in Pune, this reduced dependence on a single person for updates. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

Earlier, the daily plan was decided in fragments—by urgency, not by capacity and material signals. This broke down as soon as urgent orders came in; jobs were half-started and WIP piled up across stages. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. Planning moved to a simple daily schedule linked to orders, capacity and material, reducing last-minute reshuffles. For engineering operations in Pune, this reduced dependence on a single person for updates. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

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 centralised workflow where each order, material requirement and update had a clear owner and timestamp. Material sent out and received back was logged against job-work orders, making shortages visible immediately. 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 centralised workflow where each order, material requirement and update had a clear owner and timestamp. Material sent out and received back was logged against job-work orders, making shortages visible immediately. 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 structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. 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 that teams stopped re-entering the same data and acted on exceptions early.

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 structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. 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 that teams stopped re-entering the same data and acted on exceptions early.

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