SV DESIGN STUDIO LLP
SV DESIGN STUDIO LLP
SV DESIGN STUDIO LLP
SV DESIGN STUDIO LLP improved delivery predictability with structured execution

SV DESIGN STUDIO LLP improved delivery predictability with structured execution

SV DESIGN STUDIO LLP improved delivery predictability with structured execution

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

29%

Reduction in daily coordination time for auto ancillary work

29%

Reduction in daily coordination time for auto ancillary work

13%

Reduction in excess inventory across store and production

13%

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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How SV DESIGN STUDIO LLP operates

How SV DESIGN STUDIO LLP operates

SV DESIGN STUDIO LLP is a small auto ancillary manufacturing unit based in Ghaziabad. 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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Ghaziabad, India

Location

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Ghaziabad, India

Location

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Consumable/tooling control with daily WIP view

Use Cases

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Consumable/tooling control with daily WIP view

Use Cases

Challenges

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

Rate differences and consumption variances created disputes with subcontractors.

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

Cleaning masters to make reports match reality

Cleaning masters to make reports match reality

Cleaning masters to make reports match reality

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 auto ancillary operations in Ghaziabad, 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 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 auto ancillary operations in Ghaziabad, this reduced dependence on a single person for updates. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

After: Predictable execution, fewer escalations

After: Predictable execution, fewer escalations

After: Predictable execution, fewer escalations

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 structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. Material sent out and received back was logged against job-work orders, making shortages visible immediately. 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, 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 structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. Material sent out and received back was logged against job-work orders, making shortages visible immediately. 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.

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, 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 single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Supervisors started reviewing shortages at shift start and raised purchase/transfer requests before the line was blocked. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

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 single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Supervisors started reviewing shortages at shift start and raised purchase/transfer requests before the line was blocked. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

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