Teakwood
Teakwood
Teakwood
Teakwood tightened shop-floor control with a centralised workflow

Teakwood tightened shop-floor control with a centralised workflow

Teakwood tightened shop-floor control with a centralised workflow

A practical shift from WhatsApp/Excel coordination to trackable daily execution.

45%

Reduction in daily coordination time for plastics work

45%

Reduction in daily coordination time for plastics work

33%

Reduction in excess inventory across store and production

33%

Reduction in excess inventory across store and production

4→2 days

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

4→2 days

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

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Teakwood at a glance

Teakwood at a glance

Teakwood is a micro plastics manufacturing unit based in Gurgaon. 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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Plastics

Industry

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Plastics

Industry

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Micro

Company Size

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Micro

Company Size

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Gurgaon, India

Location

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Gurgaon, India

Location

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RM-to-FG traceability + mould-wise planning

Use Cases

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RM-to-FG traceability + mould-wise planning

Use Cases

Challenges

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

Teams worked off screenshots and old sheets; daily numbers drifted from what the shop floor saw.

Priority orders jumped the queue; other jobs got half-started and left in between.

Dispatch readiness built into the daily routine

Dispatch readiness built into the daily routine

Dispatch readiness built into the daily routine

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 centralised workflow where each order, material requirement and update had a clear owner and timestamp. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. For plastics operations in Gurgaon, 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, 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 centralised workflow where each order, material requirement and update had a clear owner and timestamp. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. For plastics operations in Gurgaon, 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.

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 single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Masters were cleaned once, and daily reporting pulled from the same transactions instead of manual consolidation. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

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 single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Masters were cleaned once, and daily reporting pulled from the same transactions instead of manual consolidation. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

Stabilising planning with live WIP and material signals

Stabilising planning with live WIP and material signals

Stabilising planning with live WIP and material signals

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 single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Planning moved to a simple daily schedule linked to orders, capacity and material, reducing last-minute reshuffles. 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, 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 single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Planning moved to a simple daily schedule linked to orders, capacity and material, reducing last-minute reshuffles. 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.

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