Content par jayen

E-commerce operations

Reference build

Stockouts down 61% across hundreds of SKUs

An agent that watches stock levels, sales velocity and supplier lead times across hundreds of SKUs, and drafts reorders before the shelf empties rather than after.

61%fewer stockouts

Aik nazar mein

Muddat
17 hafte
Team ka hajm
1 fard
Muahide ki naueeyat
Nayi tameer
Project ki qism
AI aur automation
Shoba
E-commerce aur Retail

Soorat-e-haal

Challenge kya tha

Reorder points set once go stale as velocity and lead times move. Across hundreds of SKUs nobody revisits them, so the first signal is usually a stockout.

Hum ne kya kiya

Recompute reorder points continuously from actual velocity and observed lead times, and draft rather than execute.

Wo faisle jo aham the

  • Lead times observed, not configured

    Supplier lead time is measured from delivery history rather than taken from a field somebody filled in once.

  • The agent drafts, a human commits

    Purchase orders are money. Drafting removes the work without moving the decision.

Kya badla

reduction in stockouts
61%reduction in stockouts
of reorders drafted for human approval
100%of reorders drafted for human approval

Stockouts down 61%, with every reorder arriving as a draft carrying the velocity and lead-time reasoning behind it.

Istemal shuda khidmaat

  • Continuous reorder-point calculation from live velocity
  • Observed supplier lead-time tracking
  • Draft purchase orders with reasoning attached

Hum kya mukhtalif karte

Har mansoobe mein aisi aik baat hoti hai. Ise shaya karna hi asal nukta hai — jis case study mein koi pachhtawa na ho wo saboot nahi, tashheer hai.

Seasonality was the hard part. Velocity alone over-orders after a spike, so the smoothing window mattered more than anything else in the model.

Istemal shuda khidmaat

Mazeed kaam

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