
Route to Market: FMCG Distribution Models Compared
To be able to pick the right route-to-market model for each territory by density, drop size, and credit risk, and defend the margin cascade and cost-to-serve math behind that choice.
Smarter Operations for Apparel
Industrial Engineer & Business Process Optimization Executive
Md. Salauddin Ahamed is an industrial engineer specializing in business process optimization for the ready-made garment industry in Dhaka, Bangladesh. He currently leads ERP and workflow standardization projects at Apex Holdings Ltd., having previously worked on line balancing and industrial engineering at Epyllion Group and Young Group. He holds a BSc in Industrial and Production Engineering from the University of Dhaka (NITER) and founded Apparel Diary to share practical operations research and analytics with apparel and textile manufacturing teams.

To be able to pick the right route-to-market model for each territory by density, drop size, and credit risk, and defend the margin cascade and cost-to-serve math behind that choice.

A maintenance engineer will be able to select the correct bearing type for a given load and speed, specify the right shaft and housing fit, and read a failed bearing's wear pattern to identify the actual root cause before ordering a replacement.

To pinpoint whether pretreatment, dosing discipline, or a lab-to-bulk mismatch is driving their redye rate, and calculate what each point of lost RFT is actually costing their dyehouse.

A planner will be able to assign the right replenishment policy continuous or periodic to each trims SKU, size safety stock correctly using real lead time variability, and stop applying EOQ to fabric where it doesn't belong.

You'll be able to calculate fire load density for a cutting or finishing floor, size compartment walls and fire ratings against it, and run the travel-distance and stair-flow checks that make an evacuation plan actually hold.

A planner will be able to pick the right smoothing model for a given SKU, tune alpha, beta and gamma against a holdout period instead of by feel, and know which forecast error metric to track so bias gets caught before it fills a warehouse.

A practitioner guide to standard minute value: rating, allowances, a fully worked time study, and what an SMV error actually costs a costing sheet.

To score any asset on criticality and detectability to choose the right strategy from among four options, check whether the P-F curve even makes prediction possible, and track the metrics that prove the programme is paying back.

Sizing WIP buffers between production stages from measured arrival and wait-time data using Little's Law, and defend a lower utilisation target instead of guessing rack sizes.