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Case Study

Inventory Allocation and Replenishment with AI

Adler Modemärkte

About ADLER

Founded in 1948, Adler Modemärkte AG is one of the leading clothing retailers in Germany for the target group 55+, a growing and affluent consumer segment. In 1974, ADLER became one of the first retailers to offer a customer loyalty card, and now boasts over 3 million loyalty card clients. In 2010, ADLER launched an online shop and later expanded its omni-channel services to include Click & Collect. Today, the company operates 172 stores in Germany, Austria, Switzerland and Luxembourg, generating approximately €500 million in annual revenue – of which 85% comes from its own brands.

The Challenge

The retail environment that ADLER competes in has changed dramatically. Digitalization is changing how consumers communicate, what they value and how they shop. While the online giants experience exponential growth and new e-commerce players continue to enter the market, traffic in brick-and-mortar is falling.

To remain competitive in the dynamic retail market, ADLER launched its “Strategy 2020”. At the core of this strategy: customer-centricity powered by a data-driven business model.

“We want to find answers to the data-driven business models of the online players.”
Marcel Turhan, Adler Modemärkte
Marcel Turhan
Head of PME & PMO

One crucial element of this new customer-centric approach is to continuously offer the right merchandise in the right quantity in the right place, at the right time – to make sure that customers are never left standing in front of empty shelves. Although ADLER has very precise inventory data thanks to the store-wide implementation of RFID, it lacked the instruments to fully take advantage of its data. Like most traditional retailers, ADLER was still managing its merchandise through its internally developed systems, combined with “Excel analytics” and intuition. Attempting to predict sales at the SKU level across all stores, taking into consideration all possible influencing factors, was near to impossible. In short, the manual and error-prone process was preventing ADLER from achieving its full profit potential.

ADLER & aifora

In February 2019, ADLER conducted an in-depth evaluation of five providers of merchandise management solutions to ensure that the transformation to a data-driven business would be completed with the right partner. Specifically, ADLER was looking for the optimal allocation & replenishment solution from a provider with expertise in omni-channel fashion retail. The evaluation included a technical and functional assessment by the users.

Ultimately, the fashion retailer joined the aifora Retail Automation Platform because aifora offered the highest level of flexibility as well as the most overlap with ADLER’s key requirements, including:

  • Predictive functionalities
  • Automation & exception handling
  • Management at the SKU level
After being integrated onto the aifora platform, users were onboarded through a series of workshops and 1:1 trainings, to ensure that everyone was confident working with the new AI-powered tool. For the purpose of intensive plausibility, the solutions were initially implemented for 3 select product groups. Next, the solutions were rolled-out step-by-step across the entire assortment and all countries. A Customer Success Manager continues to support the ADLER team to guarantee that the company achieves its goals. Moreover, continuous product improvements are implemented based on ADLER’s feedback and evolving requirements.

The Solution

Using data from ADLER’s back-end systems, as well as supplementary external data, aifora’s allocation and replenishment software forecasts consumer demand and calculates the ideal time for ordering goods. The algorithm takes available sales and store space, loyalty card data, promotions, weather data, and event data into account. Each store is considered individually and lead times for punctual delivery are accounted for. All of this occurs in real-time. 

ADLER now benefits from the following features:

  • Management of SKUs, options, articles or LOT units and programs for seasonal and promotional products
  • Forecasting of new articles on the basis of existing articles
  • Calculation of holdbacks on the basis of demand analyses and costs
  • Consideration of loyalty card data
  • Integration of available salesfloor and backroom storage space
  • Basic stocking, re-procurement with long and short lead times, as well as automatic ordering
  • Early identification of imminent shortages & overstocks even with long lead times
  • Determination of safety stocks using defined service levels and ABC analyses
  • Monitoring of supplier delivery reliability
  • Order generation also of article bundles (mixed volumes) taking into account past delivery qualities and logistics costs

Impact

Within just a few months ADLER was already able to see a positive impact from the implementation of aifora’s solutions. Most notably, out-of-stock situations were minimized, which results in increased revenues and more satisfied customers. Moreover, ADLER is able to react swiftly to changes in consumer demand. Through the automation of manual tasks, ADLER users are able to work more efficiently. As aifora’s algorithms continue to learn, ADLER will profit from even great improvements in the future. 

Increased availability of merchandise

Early detection of incipient shortages & surpluses

More balanced turnover/ stock ratio 

ADLER in the News

Fashion Network | Adler relies on data sharing

The German fashion retail industry needs change. In order to remain competitive, more and more companies are relying on artificial intelligence. Adler is also investing in its future strength and is using data sharing. Read more (in German).

Handelsblatt | Fashion chain Adler shares its data to fight against Amazon and Zalando

Adler shares data with its suppliers via a cloud. This is how retailers want to catch up with Amazon & Co. But many still lack courage and technical know-how. Read More (in German).

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