Esmail Arshad
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Jannat & Sadaf · Operations Manager · 2026 — Now

Rebuilding production scheduling around delivery risk

Production ran off an informal queue that took little account of garment lead time, labour capacity or promised dates. I rebuilt the sequence around which orders were most at risk of missing their date, taking on-time delivery to 98.6%.

Production planning · Capacity management · Order prioritization

Problem
Informal queue little visibility into lead time, effort or available capacity
Priority
Long-lead orders wedding work sequenced around delivery risk
Outcome
98.6% on-time delivery

Before

Order of arrival

Primarily FIFO, with capacity collisions late in the cycle

  • Promised delivery date not weighed against effort
  • Garment lead time not consistently accounted for
  • Production hours and labour availability unmodelled
  • Late wedding orders and last-minute overtime

After

Risk of missing the date

Sequenced on due date, lead time, effort and capacity together

  • Long-lead wedding wear placed first where needed
  • Remaining production effort assessed per open order
  • Overlapping high-effort orders spread across the team
  • Capacity pressure visible early enough to act on
Prioritization changed from arrival order to delivery risk, using due date, lead time, effort and available capacity.

Challenge

Production was managed through an informal queue that leaned heavily on the order in which work arrived, without consistently weighing garment lead time, the effort still required, or the labour capacity actually available.

That produced capacity collisions — most damagingly when long-lead wedding orders competed with shorter Pret and Formal work. The result was late deliveries and last-minute overtime.

What I did

  1. Mapped the production requirements of open orders, covering promised dates, garment type, expected lead time and the work still outstanding on each.
  2. Replaced the arrival-order queue with a risk-based sequence, prioritizing on due date, lead time and available capacity together.
  3. Gave long-lead wedding wear additional priority, since a delayed start there leaves far less room to recover before a date that cannot move.
  4. Balanced work across the team, using the queue to stop high-effort orders from overlapping and to surface capacity pressure earlier.
  5. Used delivery performance to tune the sequence, moving production management from last-minute recovery toward earlier intervention.

Decision

The earliest order in the queue was not always the one that needed attention first. I sequenced on the risk of missing the promised date, especially where a long production lead time left little room to recover later.

Outcome

On-time delivery reached 98.6%.

The process also reduced the reliance on last-minute recovery, because delivery risk surfaced early enough to be scheduled around rather than absorbed as overtime.

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