About MS Mode
MS Mode is an international fashion retailer with more than 200 stores in key shopping destinations across Europe. They also have a fast-growing presence on relevant online channels, including MS Mode’s own webshop and partners like Zalando and Wehkamp.
As part of the Excellent Retail Brands group (including other leading brands like America Today), MS Mode distinguishes itself by offering on-trend, affordable, and comfortable fashion for curvy women (sizes 38-54). Their customer loyalty is driven by consistently providing flattering and trendy styles, alongside friendly in-store advice and engaging experiences on digital channels.
However, the brand also operates in a diverse European retail landscape, where customer preferences differ by country, city, and channel.
To succeed in this market, they needed more than a ‘one size fits all’ approach to inventory management. This client case describes how MS Mode tackled their challenges head-on, by investing in proven AI technology solutions that continue to transform their operations.
The Challenge
Retailers know that keeping customers happy is always a challenge. Without sufficient stock availability they cannot meet customer demands and preferences. These can vary considerably across different countries and channels, making it hard to predict what inventory is needed, and where.
Trends change rapidly in today’s social media-driven commerce landscape, making it even more important to get the most value from every single SKU whenever (and wherever) it can sell. In this market, replenishment and allocation must be based on the real sales potential at each location, not guesswork.
Like many fashion retailers, MS Mode faced a familiar mix of operational and commercial pressures:
- Different demand levels per SKU, across locations and channels
- Frequent stockouts in stores where items sold fast
- Overstock in locations where demand lagged
- Planning complexity due to channel differences
- Inaccurate forecasting based primarily on experience than hard data
- High markdown pressure eroding margins
All these issues ultimately stem from one problem: the difficulty of predicting how much stock is needed to precisely fulfil demand at each location.
Although MS Mode identified this as a crucial challenge for their business, they’re also not alone in this. Demand forecasting is highlighted in McKinsey’s State of Fashion report as one of the biggest challenges for the entire industry.
Without highly accurate stock management, there is a high likelihood of stockouts, overstock, and the painful costs of markdowns and customer disappointment. Many retailers accept this as a ‘fact of life’ and, instead of fixing them, try to compensate by making efficiency savings in other areas of operations instead.
For example, retailers will commonly reduce the frequency of product picking in favor of making bulkier shipments that are more cost-effective. However, while these tactics may make short-term savings on distribution costs, they also magnify the existing problems by increasing the margin of error on stock allocation.
Instead of following the same old methods, MS Mode decided to take a fresh approach.
They realized that by investing in proven AI capabilities and data-led decision making, they could implement a highly accurate stock management solution. This approach could enable a more granular level of control and support better decision making – while relying less on ‘gut feeling’ and more on hard, real-time data.
"Inventory is one of the biggest investments for a fashion company. If you can manage it smarter, you can unlock tremendous gains."
- Dennis Mok, CEO MS Mode
Why Thunderstock
The collaboration with Thunderstock was a natural choice for MS Mode, because their sister brand, America Today, was already using their technology. Dennis Mok joined the company as CEO in 2019, and, having seen what this technology could do, it was clear that MS Mode would benefit from using the same capability. Properly implemented, they could then scale highly accurate inventory decision-making across their diverse markets.
Thunderstock stood out for several reasons:
- One of the earliest AI systems on the market with a proven track record
- Granular inventory management capabilities, down to the SKU level
- Operates using fashion’s primary levers: buying, allocation, and markdown
- Practical implementation: no disruption, intensive IT burden, or long rollout cycles
- Ability to automate allocation, replenishment, and transfers based on actual demand
The Collaboration
Close cooperation between both Thunderstock and MS Mode’s data team ensured that positive impacts were delivered in a short timescale. The first module was the inventory optimization module, which was implemented, tested, and refined step-by-step before rolling-out further modules.
Collaboration highlights:
- Implementing SKU-level forecasting (per variant, color, and size)
- Options for automated allocation, replenishment, and store transfers
- Tailoring the system to different markets and store types
- Progressive improvement of dashboards and reporting
- Supporting teams in adopting and trusting the model
As with any new technology, change management is an essential ingredient for successful adoption.
Unless they can quickly see the benefits of a new solution, merchandising and planning teams will naturally prefer to use the same systems and methods as they always have – even when the results are known to be sub-optimal.
As Mok explains,
"Anything new encounters resistance at first. You need to learn to trust that what the system predicts is right. But once people see that AI improves decision-making, adoption grows quickly."
But, once decision-makers could see that they could make more accurate stock position decisions by using the predictive capabilities of Thunderstock, they were quickly convinced.
Indeed, the results speak for themselves.
Results
The impact of Thunderstock’s demand forecasting on MS Mode’s operations was clear and measurable.
1. Less inventory, same revenue
MS Mode now achieves the same sales revenue from significantly less stock. That generates positive business benefits:
- higher margins
- lower markdown pressure
- more available cash flow
2. Better product availability
With a more accurate match between local demand and store inventory, customers are far more likely to find the items they want.
3. Faster learning loops
Better data leads to better decisions, creating a reinforcing cycle of continuous improvement across all key metrics.
4. A fundamentally different way of working
The company shifted from instinct-based planning to evidence-based decision-making. Instead of only looking back at historical data as a guide, the predictive algorithms accurately anticipate future demand using real-time data.
Rolling Out New Modules
After the successful results from the inventory module, MS Mode has started to implement Thunderstock’s other AI modules, including:
- Buying & Collection Planning: starting with Never-Out-of-Stock (NOS) items, expanding to the full range
- Markdown Optimization: recommending the right discount at the right moment, to preserve optimal margins
With each additional module, MS Mode is following a path towards a fully integrated, AI-enhanced merchandise process. This empowers human decision-makers with superior insights and a forward-looking perspective on customer demand.
"Ultimately we want to close the loop and improve the entire primary process - buying, inventory and markdown - with AI."
- Dennis Mok, CEO MS Mode
Looking Ahead
For MS Mode, the potential of AI extends beyond operational gains. Mok sees opportunities to reshape the wider fashion industry:
“If we use AI more intelligently, we can break the cycle of overstock, heavy markdowns and margin erosion. It makes the entire industry healthier, more efficient and more appealing to customers.”
For fashion retailers, the use of proven AI capabilities for inventory management is a clear strategic advantage. Retailers know that inventory is simultaneously the biggest investment and greatest risk for their businesses, so top-level inventory management is a vital capability.
With the growth of multichannel and omnichannel strategies, the challenge of inventory management will only become more complex. However, with an AI-driven solution like Thunderstock these strategies can become the opportunities they are meant to be.
Quote: "Inventory is one of the biggest investments for a fashion company. If you can manage it smarter, you can unlock tremendous gains."
