Making more profit is now a choice you can make

By leveraging re-distribution for the right articles at the right time

Forecasting 6 weeks ahead to identify those articles ready for redistribution.

Every night, the AI Redistributor systematically evaluates all SKU’s and forecasts 6 weeks ahead to identify those articles ready for redistribution. It assesses not only articles in the right lifecycle stage but also evaluates their potential business value

Back 2 warehouse

When inventory levels in warehouses begin to deplete while shopfloors with no demand still hold stock, you start to initiate redistribution. It clears out stock from underperforming shopfloors and calls them back to the warehouse so they can be steered to the channels and shopfloors who do hold demand.

Store 2 store

At the end of each product lifecycle, 80% of shopfloors experience significant gaps in availability, resulting in unsold inventory. To address this issue, you choose to redistribute the leftover sizes from these shopfloors directly to the top-performing shopfloors where demand still exists, allowing for better showcasing of these products and pushing end stock to a maximum level.

Making more profit is a choice you make.

leveraging re-distribution for the right articles

Every night, the AI Redistributor systematically evaluates all SKU’s and forecasts 6 weeks ahead to identify those articles ready for redistribution. It assesses not only articles in the right lifecycle stage but also evaluates their potential business value to the company

Making more profit is a choice you make.

Back 2 warehouse

When inventory levels in warehouses begin to deplete while shopfloors with no demand still hold stock, you initiate a the redistribution. This approach involves clearing out stock from underperforming shopfloor-article combinations and redistributing back to the warehouse so it can be steered to the right channels and shopfloors again.

Making more profit is a choice you make.

Store 2 store

At the end of each product lifecycle, 80% of stores having significant gaps in their available sizes, leaving much of their inventory unsold. To address this, you choose to redistribute the leftover sizes from these stores directly to the top-performing 20% of stores where demand still exists.

"The right sku's, the wrong floor: A continuous dilemma, unfolding at every moment of the season."

Out of stock 80%

400 of 2000 left

Turn rate

Based on forecast

Potential in shopfloor a

Shopfloor A

Low potential (forecast 2 pieces)

Shopfloor B

High potential (forecast 10 pieces)

Business case

$20,000 Revenue
$14,000 Margin
50% Average discount
$800 Costs to redistribute
$9,200 Won in net profit
Ratio: 12 Marging p.p: $35 Risk Factor: 5 Costs p.p: $2
Out of stock 85%

750 of 5000 left

Turn rate

Based on forecast

Potential in shopfloor a

Shopfloor A

Low potential (forecast 5 pieces)

Shopfloor B

High potential (forecast 25 pieces)

Business case

$75,000 Revenue
$52,500 Margin
50% Average discount
$3,750 Costs to redistribute
$33,750 Won in net profit
Ratio: 9 Marging p.p: $70 Risk Factor: 8 Costs p.p: $5
Out of stock 70%

500 of 1500 left

Turn rate

Based on forecast

Potential in shopfloor a

Shopfloor A

Low potential (forecast 1 piece)

Shopfloor B

High potential (forecast 6 pieces)

Business case

$100,000 Revenue
$70,000 Margin
50% Average discount
$2,250 Costs to redistribute
$47,750 Won in net profit
Ratio: 21 Marging p.p: $140 Risk Factor: 2 Costs p.p: $3

The AI delivers the optimal future state before you can click on redistribute

The core problems we solve

The fragmention problem

After pushing seasonal stock to the shopfloors it is inevitable that articles will become more fragmented overtime. We do not get alarmed pro-actively and have nu understanding how fragmented articles are and with that losing a lot of speed in sell-through-rates. These most of the time good articles need to be returned in good size bows in the right stores to don’t waste good products in a bad distributing system.

The channel stock problem

Once articles are distributed too quickly the central warehouses are depleted and there are no more options to steer the stock to the right shopfloors, digital channels or non-owned channels. Giving you no other options than discounting or seeing a big drop in turnover rate.

The ROI problem

There is no insight upon what an article could potentially gain. So why redistribute? If there is no insight in either the loss of opportunity or turn rate gain we also can not see we are actually losing results. We give both a clear understanding of the articles potential whilst being able to follow your decision and monitor the in practice impact.

The capabilities of
The AI Redistributor

The AI Redistributor delivers a 6-week forecast that covers both SKU and article aggregation. Our deep learning model identifies unique correlations among various factors—such as shopfloor activities, product types, seasonal trends, weather conditions, holidays, and visual data—to generate these forecasts. It assesses the likelihood of demand for each article across different shopfloors 6 weeks and optimizes the matching process to meet anticipated demand effectively. From that the AI can tell if an article is ready for Redistribution
01

Forecast sales with
leading accuracy:

The AI Redistributor provides a 6-week forecast, predicting the potential sales of SKUs across all shop floors. It identifies articles that still hold sales potential but are experiencing a significant decline in their selling rate due to over-fragmentation within the shopfloor network.
02

Multiple horizons
and multiple aggrations

A multimodal framework. This advancement enables the capability to simultaneously forecast across various horizons and aggregate levels. Such a multifaceted approach empowers stakeholders to precisely identify articles that, despite their inherent value, suffer from suboptimal sales velocity due to issues related to location or size mismatches.
03

Value driven and sorted by
value of businesscase

The KPI’s per article enables you to automatically see the right articles to redistribute prioritising the ones who will deliver most like the highest ROI.
Additionally the filter options make it possible to quickly scatter through your whole assortment.
04

Current state and
customizable future state of
each article

Once you have decided which article to redistribute the AI will give you the most optimal future state of the stock to gain the most. The future state is adaptable on SKU-Location level. Making it possible for you too quickly validate and adapt the ideal situation moving forward.
05

Leftover management

If the AI still has articles as a leftover you can choose what do with this. Leave them in that particular store and discount them or send them back to the warehouse.

Reasons of succes

Leading Time
Series AI model
architecture
100% automated
merchandising
Billions of extra
data via our
unified model
Zero cost
implementation
See the potential
value with a simulation
before actual implementation
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