Business Context
Indian garment manufacturers running 50–500 person operations face a fragmented workflow. Orders are tracked in WhatsApp with no single source of truth for delivery dates, payments, or production status. Inventory is guesswork — fabric sits at vendors, in transit, or in the godown with no consolidated view.
Job work sent to external vendors for dyeing, printing, or stitching disappears for days. TAT violations go unnoticed until customers complain. Quality disputes arise because defects are caught at dispatch, not during production. Machine breakdowns cause unplanned downtime because maintenance is reactive, not scheduled.
Existing ERPs like SAP, Oracle, and Zoho are either too expensive, too complex, or designed for Western manufacturing flows that do not match Indian job-work-heavy, relationship-driven supply chains. The target user is the 50-lakh-to-5-crore garment factory that has outgrown Excel but is not ready for SAP.
The Challenge
- Orders tracked across WhatsApp groups with no single source of truth for delivery dates, payments, or production status.
- Inventory guesswork — fabric at vendors, in transit, or in godown with no consolidated view; stockouts discovered only when cutting begins.
- Job work black hole — fabric sent to external vendors disappears for days; TAT violations go unnoticed until customers complain.
- Quality disputes from defects caught at dispatch instead of during production, with no version-controlled sample approvals.
- Manual dispatch workflow — invoices generated in Tally, courier booked separately, tracking shared via WhatsApp screenshots.
- No machine visibility — breakdowns cause unplanned downtime; maintenance is reactive, not scheduled.
The Solution
- A browser-based manufacturing dashboard using plain-language module names ("My Stock" instead of "Inventory Management") so factory owners adopt it without training.
- Kanban + Table hybrid views for every list — drag-and-drop boards for visual status management and sortable, paginated tables for data-heavy filtering, switchable with one click.
- Real-time alerts for overdue job work orders, critical stock levels, and delivery countdowns with persistent banners and color-coded badges.
- Vendor performance radar with swim lanes sorted by overdue count and reliability score, plus TimeProgressBar visualising "Day X of Y" on each JWO card.
- Drag-and-drop pipeline powered by @dnd-kit with invalid transition blocking and contextual modals for valid drops.
- Reconciliation queue for quantity variances with split-panel view and one-click Accept or Flag Dispute buttons.
Key Modules and Workflows
My Business
Morning briefing dashboard — open orders, overdue alerts, stock warnings, payment aging, and today's deliveries at a glance.
Orders
Full order lifecycle from enquiry to dispatch confirmation with Kanban board + table views, inline filters, and bulk actions.
My Stock
Real-time material visibility across godown, vendors, and transit; wastage tracking, stock audits, consumption forecasts, and alert thresholds.
Job Work
Vendor-wise swim lanes showing fabric sent out, TAT progress bars, overdue escalation, and reconciliation queue for quantity variances.
Quality Check
QC checklists per production stage, sample approval workflows with version history, and defect flagging before dispatch.
Dispatch
Dispatch queue with courier booking, invoice generation, shipment tracking, and delivery confirmation.
Outsourcing
External partner management — active orders, cost tracking, and vendor performance scorecards.
Machines
Equipment fleet overview, preventive maintenance schedules, consumable inventory, and vehicle tracking.
Technical Architecture
- Next.js 16 with App Router and React 19 for server-rendered pages and modern component patterns.
- Tailwind CSS 4 and shadcn/ui component library for consistent, dense UI without wasted whitespace.
- React useState and useMemo for local state management with derived data computations.
- @dnd-kit/core powering drag-and-drop interactions across Kanban boards with invalid transition blocking.
- Lucide React icons with consistent color-coded semantics — red for overdue, amber for warning, green for healthy, blue for in-progress.
- Vercel deployment for zero-downtime releases and edge-optimized delivery.
Why This Stands Out
- Plain Language First — module names use words factory owners already know ("Job Work", "My Stock", "Quality Check") instead of ERP terminology.
- Density Without Clutter — tables show 8–10 columns with smart truncation; Kanban cards show 5 key fields with clear visual hierarchy.
- Built for Indian manufacturing realities — job-work-heavy, relationship-driven supply chains, not Western manufacturing assumptions.
- Zero Training design — every action is labelled; no icon-only buttons for critical functions; progressive disclosure from summary to detail.
- Mobile-first responsive — sidebars collapse, tables become horizontally scrollable, and cards stack vertically across all modules.
Measured Results
- Replaced 12+ Excel sheets and 5 WhatsApp groups with a single unified dashboard.
- Reduced order status enquiries from floor to office by approximately 60%.
- Enabled same-day visibility into job work TAT violations that were previously discovered 3–5 days late.
- Cut dispatch preparation time by automating invoice and packing list generation.
- Factory owners and floor supervisors adopted the system without formal training due to plain-language naming conventions.
Measurement Notes
- Impact measured through reduction in manual coordination overhead — fewer WhatsApp messages, fewer phone calls, fewer status meetings.
- TAT violation detection speed improved from 3–5 day lag to same-day alerts with persistent red banners across Job Work views.
- Dispatch efficiency measured through automated invoice generation time versus previous Tally + manual courier booking workflow.
Core Stack
“Built for the 50-lakh-to-5-crore garment factory that has outgrown Excel but is not ready for SAP. This system treats manufacturing as a coordination problem solved through real-time visibility, not just an accounting problem.”