BIRetail empowers retailers to make quicker and informed decisions, through inferences of their own data.

BIR-MSS

The Merchandiser's Conundrum

For a Retailer, it is core to provide the right merchandise to its customers, and never let a customer return empty because of unavailability of choice or size.

Stores are constrained by space and by inventory holding costs, preventing them from holding limitless width and depth of inventory. Therefore, certain stock is held at store, and as SKUs sell, they are refilled from warehouses in a timely manner, to avoid loss of sale due to non-availability.

This process of “replenishment” gets ever more complex with the increasing number of stores and SKUs, and has now evolved into a quantitative optimization algorithm, which recommends what SKUs to keep in which store, and to what depth, which sizes matter, when to replenish and how much.

Challenges To The “Manual” Approach

When an item is required in more locations than the quantity available, a lot of manual effort is required to intelligently decide which location to send to.

When demands of items goes unfulfilled, iterative decision-making is required to allocate replacement items.

Base Stock requires frequent calibration, to be in sync with dynamically trends. Manual adjustments to Base Stock is time-consuming, hence is done far and between.

Static and standard size ratio across all Category Buckets and all Stores leads to remnant odd sizes of items at different locations.

Deciding optimal item depth is a balancing act between preventing OOS and unnecessary over-stocking. It requires frequent repeat cycles hence is often compromised.

BIR-MSS: The Merchandising Support System

Most of the afore-mentioned challenges relate to the requirement of massive data crunching for smart decision making. BIR-MSS is a prescriptive Decision Support System for Merchandisers, powered by Machine Learning algorithms and heuristic techniques, guided by deep domain knowledge.

MSS proves invaluable to a Retail Merchandiser as a single umbrella of solutions around Allocation, Replenishment, Pullback and Consolidation.

The applicability of BIR-MSS stems from its extreme configurability across various parameters, providing Retailers to tweak rules, prescribe min-max guidelines, and define different conditions for categories and locations.

What Does BIR-MSS Achieve?

Daily Dispatch List:
Prescribes daily, a curated list of SKUs and quantities to be despatched from Warehouses to Steres.

Consolidation Across Locations:
Recommends consolidation and re- allocation of broken sizes and non- performers

Dynamic Base Stock:
Ensures Base Stock guidance is on current trends and not outdated predictions.

Stock Optimization:
Intelligently replenishes and allocates merchandise to Stores with an objective to maximum Stock Turn and ROI.

Pullback Of Slow-Movers:
Pulls back non-performing merchandise to make way for new stock to be allocated frequently, ensuring consistent upkeep of store targets

Reduction Of Brokenness:
Prevents odd-size residues of merchandise in every store by recommending optimal size distribution per Category Bucket per Store:

Daily Dispatch List:

Prescribes daily, a curated list of SKUs and quantities to be despatched from Warehouses to Steres.

Stock Optimization:

Intelligently replenishes and allocates merchandise to Stores with an objective to maximum Stock Turn and ROI.

Reduction Of Brokenness:

Prevents odd-size residues of merchandise in every store by recommending optimal size distribution per Category Bucket per Store:

Dynamic Base Stock:

Ensures Base Stock guidance is on current trends and not outdated predictions.

Pullback Of Slow-Movers:

Pulls back non-performing merchandise to make way for new stock to be allocated frequently, ensuring consistent upkeep of store targets.

Consolidation Across Locations:

Recommends consolidation and re- allocation of broken sizes and non-performers.

Benefits to the Retailer

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