Schmancy Pack Pvt Ltd
Schmancy Pack Pvt Ltd
Schmancy Pack Pvt Ltd
Schmancy Pack Pvt Ltd tightened shop-floor control with a centralised workflow

Schmancy Pack Pvt Ltd tightened shop-floor control with a centralised workflow

Schmancy Pack Pvt Ltd tightened shop-floor control with a centralised workflow

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

56%

Reduction in daily coordination time for packaging work

56%

Reduction in daily coordination time for packaging work

23%

Reduction in excess inventory across store and production

23%

Reduction in excess inventory across store and production

5→1 days

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

5→1 days

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

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Inside Schmancy Pack Pvt Ltd

Inside Schmancy Pack Pvt Ltd

Schmancy Pack Pvt Ltd is a small packaging manufacturing unit based in Bangalore. 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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Packaging

Industry

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Packaging

Industry

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Small

Company Size

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Small

Company Size

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Bangalore, India

Location

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Bangalore, India

Location

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WIP tracking across printing–lamination–slitting–dispatch

Use Cases

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WIP tracking across printing–lamination–slitting–dispatch

Use Cases

Challenges

Payment follow-ups depended on WhatsApp threads; disputes re-opened invoices at month-end.

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

No simple view of vendor-wise delays, so the same issues repeated every month.

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, collections follow-ups were scattered and disputes reopened older invoices. This broke down on part-payments; the receivable view changed daily and escalations increased. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Collections follow-ups moved to a single list with dispute tagging so teams stopped chasing the wrong invoices. For packaging operations in Bangalore, this reduced dependence on a single person for updates. The practical outcome was smoother handovers between departments and more predictable daily execution.

Earlier, collections follow-ups were scattered and disputes reopened older invoices. This broke down on part-payments; the receivable view changed daily and escalations increased. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Collections follow-ups moved to a single list with dispute tagging so teams stopped chasing the wrong invoices. For packaging operations in Bangalore, this reduced dependence on a single person for updates. The practical outcome was smoother handovers between departments and more predictable daily execution.

After: Predictable execution, fewer escalations

After: Predictable execution, fewer escalations

After: Predictable execution, fewer escalations

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 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 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 that teams stopped re-entering the same data and acted on exceptions early.

Controlling rework through traceability and holds

Controlling rework through traceability and holds

Controlling rework through traceability and holds

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. 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. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

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