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Pre-Season Planning: Why Successful Inventory Optimization is Vital in Fashion Retail

How can fashion retailers forecast today what their customers will demand tomorrow?

Next season forecasting in fashion retail is one of the most fascinating and elusive subjects. Every retailer seeks the perfect, holy grail, looking for innovative ways to make the “perfect forecast”.

Many retailers think that if they can get the forecasting right, all their planning and supply chain problems will go away regardless of the methods they choose. But without a crystal ball to predict the future, it is quite impossible to get the long-term forecasts precisely right.

Even if retailers use a combination of various approaches mentioned in How to Forecast Demand Accurately for the Next Season: The Billion-Dollar Fashion Retail Question, they still won’t be able to achieve high pre-season forecast accuracy. While this may sound a bit pessimistic, there is still hope. Some paths lead to better outcomes that don't necessarily depend on demand forecasting alone.  

What fashion retailers need is a reimagined approach to plan demand for a future with demand uncertainty.

In this article, we have listed 4 efficient ways for fashion retailers to help them to see pre-season planning from a different perspective and pave the way for success in next-season planning.

1. Tackle the whole, not slice by slice

Embrace the forecasting uncertainty

How fashion retailers value their planning paves the way for rejuvenation.

Once they step up their inventory optimization game, they can put themselves in a much better position today to meet the demand of tomorrow.

And it all starts with understanding the uncertainty in their demand forecasting, reimagining next season planning, and embracing a holistic supply chain view.

2. Speed up your supply chain

Say goodbye to long lead times

The farther forward a prediction looks, the less accurate it is likely to be.

For retailers, the consequences of extended lead times can go far beyond a simple annoyance; it can end up being too costly. With longer lead times, there’s the risk of running out of inventory or having higher inventory levels which can lead to markdowns.

On the other hand, flexibility and short lead times reduce the risk of buying the wrong items or carrying excess inventory. By shortening supply chain lead times, retailers can carry less stock, have less risk, and create less frustration for the end customer.

3. Improve allocation across stores, make better size planning

Allocate your inventory optimally

Immediacy has become a dominant force in fashion retail and has significantly enhanced the need for stock to be available in the right place, at the right time. As fashion retailers aim to make their customers happy in the next season while minimizing the costs to maintain margins, allocation is one area that they simply cannot afford to overlook.

But the challenge is about placing every single item in the best possible location at the right time to achieve the lowest possible cost, minimal markdown, and maximum profit in the upcoming season. It is not an easy task when every location has a unique profile.

The good news for fashion retailers is that they can take advantage of AI-powered allocation optimization solutions to allocate their inventory optimally across products, sizes, stores, channels and regions.

Even though it’s hard to predict what the demand will be for an item 6 months or a year from now on, retailers can use these new sophisticated solutions to oversee how the items will respond between stores, channels, and regions.

They can benefit from robust, allocation-specific forecasts. And they can also successfully predict the relative store share for any item before the season to allocate inventory accordingly.

4. Accelerate your size level optimization capabilities

Generate customer-centric assortments

It’s every retailers’ dream to ensure the right product is on the shelf when and where their customers want it. As diversity grows across each store with increased variation in size, it becomes extremely important to get the size distribution right and use attribute-based analysis to generate localized assortments and size profiles.

Not all SKUs perform similarly across all stores in today’s dynamic fashion world. There are many location-specific dynamics that retailers need to consider such as sociodemographics of the locations. 

To predict omni-channel demand for items across channels and locations and uncover product attributes that drive purchasing decisions of the customers ahead of the next season, fashion retailers need to assess how they optimize their assortments.

By using initial allocation during the assortment planning, overseeing local preferences and trends, retailers can create more customer-centric and localized assortments. But it requires capturing value from assortment optimization through AI-powered advanced analytics.

Once they get the size optimization and assortment right, they can enjoy higher sales, increased margins, leaner operations, and happy customers.


Every retail planning starts with demand forecasting. But forecasting itself is not nearly enough.

Retailers need to focus on the challenges they can work out instead of focusing on the big problems they can’t solve. 

By prioritizing and mastering allocation, size optimization, and assortment optimization, retailers can become more flexible, maximize profitability, and grow their businesses in the seasons to come.

Financial-profit-based optimization is the key to opening new doors to increased efficiency and profits. It allows retailers to have a betting strategy that can increase their chances of winning in the game of demand uncertainty.

It is not easy to know exactly what products will sell in the next fashion season, but it is possible to allocate inventory investment dollars in a more profitable way.

Invent Analytics

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