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International fashion retailer bonprix was struggling with outdated pricing and promotion systems, using rigid price-conversion tables. The company was facing high prices for many products in the highly competitive Russian market, leading to rising costs and falling profits. To modernize internal processes and meet the complex and changing market demands, the online German shop needed an automated solution to achieve consistent and granular price optimization with varying parameters for different countries. With five house brands in 30 countries, it was imperative the solution be seamless and effective.

UK-based supermarket chain Morrisons wanted to increase on-shelf availability through improved demand planning and replenishment based on analysis of customer behavior at every store. The goal is to put the customer at the heart of every decision. Store replenishment based on manual ordering by in-store teams proved time consuming, created inconsistencies between stores and was not always accurate. Morrisons wanted any new planning solution to easily integrate with, and streamline, its complex IT infrastructure, as well as be capital light.

SELGROS, a wholesale company, was facing a challenge with its advertising strategy. Every two weeks, the company would mail up to one million brochures to its customers. The decision on which customer should receive a catalog was a manual process using segmentation and decision trees. This process was not only time-consuming but also inefficient as it did not consider all the elements that influence customer spending. As a result, the company acknowledged that its marketing budget was not being used efficiently. SELGROS sought a solution to automate the process, reduce advertising costs, and improve customer targeting.

Globus CR, a part of the Globus Group, operates in three countries with a total of 47 hypermarkets, 91 DIY stores, and six electronics stores in Germany, 15 full-range stores in the Czech Republic, 15 in Russia, and two DIY stores in Luxembourg. The company was facing challenges with its supply chain management strategy, particularly in the areas of promotion and inventory replenishment. The market landscape they operate in is extremely promotion and price-driven, and their promotion planning processes were manual and cumbersome. This resulted in high leftover stocks after promotions and high planning and handling costs. The increasing labor costs were driving the need for automation. The company was also struggling with maintaining both promotion leftovers and out-of-stocks at a reasonable level due to data insights and planning activities being housed across different parts of the business.

OTTO, a German multichannel retailer, faced challenges in its competitive environment characterized by low margins, high competitive pressure, and rapidly changing market conditions and customer demands. The company needed to balance product availability and pricing for every single article in its extensive product portfolio. One of the greatest challenges was predicting the sales of an article at an early stage, as the profitable purchase of goods determines overall success. OTTO also faced challenges in reducing delivery times for partner products, which were longer than for OTTO’s own brands due to more complicated logistics processes. The retailer needed to know which articles would sell, how frequently, and in what sizes and amounts to order the right articles in advance based on the forecasts and expedite delivery to the customer.

Ariztía, the second largest chicken and poultry producer in Chile, was facing challenges in managing its short shelf life products. The company's products, which are shipped either fresh or frozen to customers, required tight inventory control to assure freshness. This was of paramount importance to Ariztía as it directly impacted their mission to provide quality products and excellent service to their customers. The company also strongly believed in the value of training and education to improve employee productivity. However, assuring freshness mandated strict adherence to first expired/first out inventory turnover practices, which was proving to be a challenge.

Campbell’s Snacks team advises on a robust bakery product line, with 750 distinct items sold under 100 brands. The advisor team must routinely produce and update more than 4,500 planograms to cover this complex product line, especially as marketing strategies and demand patterns shift. Historically, it took up to 10 weeks to create these planograms manually, and there was frequent employee overtime. The challenge was to find a solution that could automate and accelerate the process of producing thousands of customized space plans.

Harris Teeter, a North Carolina-based subsidiary of The Kroger Co., operates over 265 retail locations, 52 fuel centers, three distribution centers, and a dairy manufacturing operation. The company needed an enterprise-wide workforce management platform to drive associate engagement, efficiency, and customer satisfaction. The solution had to reflect and support the culture of diversity and inclusion that is a foundation of their business model. Harris Teeter wanted a workforce management solution that not only supported their continued push for innovation and inclusion but also brought innovative capabilities to the table. The company continuously strives to innovate in the way they serve their customers, which includes having Starbucks locations in stores, offering “Hot Bars” serving pizza by the slice and other chef-prepared foods, omelet stations, sushi stations, burger bars, and beer and wine bars. Their stores also support buy online/pickup in-store (BOPUS) convenience for shoppers.

Mahindra & Mahindra Farm Equipment, part of the $20 billion Mahindra Group, is the world’s number-one tractor company by volume. Its automotive business competes in almost every segment of the industry. The Spares Business Unit (SBU) provides genuine vehicle and tractor spare parts via advanced capabilities in sourcing, assembling, warehousing and distribution. To maximize supply chain efficiencies and service, Mahindra & Mahindra constantly evaluates scientific methods to tweak demand forecasting, inventory management and replenishment planning strategies to ensure that the right parts are available at the right place and time. However, their traditional, manually driven segmentation processes and tools often resulted in inefficient allocation, high safety inventory levels and less-than-optimal service levels.

Tesco, the world’s third-largest retailer, operates over 6000 stores across Europe and Asia, offering a wide product range, from groceries to clothing and electronics. The company produces one million planograms and 125,000 store floorplan changes annually. For over 20 years, Tesco has relied on Blue Yonder solutions to ensure the fast, accurate generation of these planograms. More than 100 colleagues at Tesco use Blue Yonder solutions. However, the company faced a challenge in maintaining software knowledge and best practices as the workforce evolved. The traditional on-the-job learning and peer training methods were not efficient enough to capture best practices that lead to higher-quality plans.

Wegmans, a family-owned supermarket chain with over 100 stores across the northeast and midAtlantic states, operates a private fleet to transport fresh, frozen, and dry foods and ingredients to their network of stores. However, with a network of this size and complexity, Wegmans wondered if they were getting the most utility possible from their fleet investments. The challenges they faced included tight store delivery windows, which limited opportunities for order consolidation or routing options, routing restrictions by type of commodity being shipped, and virtually no visibility to cost savings available from the use of backhauls.

Western Digital Corporation, a global leader in flash memory storage solutions, was facing challenges with its resource-intensive spreadsheet-based planning process. The process involved four-week planning cycles with only basic planning assumptions. The company wanted a daily integrated supply chain plan that includes demand, material supply and capacity constraints and utilization, allocation and execution objectives. They also wanted visibility into demand and supply across the entire organization, including the inventory in each segment and channel, promotion plans and supply and production plans. Furthermore, they wanted to use customer segmentation and a multilayered postponement strategy to reduce overall inventory levels while better positioning products and materials to support improved customer service.

Petco, the largest U.S. retailer of pet products and services, headquartered in San Diego, California, faced a challenge in response to emerging customer commerce needs. The company decided to create and deploy a buy online pick up in-store (BOPOS) capability in an accelerated timeframe. The requirements of the project included providing accurate and reliable inventory availability levels to both online and in-store consumers. Petco's technical architecture was composed of multiple disparate platforms, prohibiting the ability to achieve a single view of inventory and enable the new BOPIS capability at the scale and performance level required for the emerging needs of Petco.com.

Constellation Brands, a leading producer, marketer, and manufacturer of beer, wine, and spirits, faced a challenge in maximizing its category item impact on shelf due to the expansion of brands and SKUs offered in stores. The company was relying on historical data in a fast-paced market, which was not sufficient to keep up with the rapidly changing demand. The company needed a solution that could incorporate forward-looking data and predictive analytics into its space plans to support growth and maximize the value of assortment over the longer term.

Rexall, a Canadian retail pharmaceutical company, was facing challenges due to its reliance on older technology and processes. The store replenishment process was initiated at the store level based on the results of daily physical inventory counts that leveraged handheld RF technology. Store managers had limited visibility to future store-level demand pattern changes, item cannibalization, safety stock requirements or days coverage prior to placing these manual orders. This resulted in frequent demand-supply imbalances. Additionally, purchase orders to vendors were conducted via non-EDI channels with patterns and volatility that resembled the patterns within the stores, causing similar imbalances with the DCs. As such, the organization sought to establish an advanced planning model that would eliminate the extremely labor intensive and manual replenishment process.

Bayer, formerly Monsanto, identified the need to standardize its end-to-end transportation processes globally, which previously followed different practices across operating regions. The company's logistics processes required responsiveness to meet time-sensitive customer demands, a pressure that was intensified by the company’s continuing growth in its global markets. The critical need for standardization paired with seasonality challenges, road transportation challenges and lacking adequate tools and processes to provide visibility into logistics raised awareness around the need for a complete digital logistics overhaul. Bayer’s goal was to improve the customer experience that could consistently provide better information to their customers, while staying efficient.

BIC, a world leader in stationary, lighters, and shaver products, was facing challenges with its manual sequencing process at its Charlotte packaging facility. The process could only look out three days, limiting their ability to take advantage of improved production planning. The three-day rolling schedule resulted in frequent, expensive, and time-consuming changeovers. Moreover, the Charlotte facility was nearing capacity and would require capital investment in a new facility if production throughput could not be increased.

Mahindra & Mahindra Farm Equipment, part of the $20 billion Mahindra Group, is the world’s number-one tractor company by volume. Its Spares Business Unit (SBU) provides genuine vehicle and tractor spare parts via advanced capabilities in sourcing, assembling, warehousing and distribution. However, the SBU was losing sales revenues due to stockouts and tight working capital as a result of its high inventory investments. The business was relying on manual analysis and Excel spreadsheets to create demand and supply plans, but they were not adequate for the complexity and scale of the challenge. To gain greater responsiveness and ensure the availability of spares for different demand patterns, Mahindra sought Blue Yonder’s expertise and advanced technologies to optimize its parts inventories, spanning 100,000 SKUs and 21 distribution centers.

McKesson Canada, a company with annual revenues in the billions, serves millions of customers every day, delivering more than one-third of all prescription drugs in Canada. The company’s global supply chain manages over 250,000 distinct product SKUs. McKesson Canada was challenged to optimize its inbound products, and the inventory in its 13 distribution centers (DCs), via an outdated legacy system. New technology was needed to meet growing customer requirements, support revenue gains, manage supply-side disruptions, and increase accuracy and efficiency. McKesson Canada partnered with Blue Yonder to manage product flow into its DCs, as well as inventory levels. The stakes are high: billions of dollars in product acquisitions and over $1 billion of inventory are managed through Blue Yonder.

Marks & Spencer, a leading multinational retailer based in London, has been relying on Blue Yonder’s demand and fulfillment solutions, as well as workforce management, to optimize processes, manage complexity, and support responsiveness. However, the company needed to migrate all its Blue Yonder solutions to the cloud to achieve higher levels of agility and increased supply chain speed to provide the best service for customers. The challenge was to minimize business disruptions during the cloud migration as Blue Yonder demand and fulfillment is one of their mission-critical applications, which generates orders for their downstream systems. The company could not afford for their stores not to be replenished each day.

Anheuser-Busch, a company with over 160 years of history, owns and operates more than 120 facilities, including breweries, wholesaler distribution centers, agricultural facilities and packaging plants, employing more than 19,000 people. The company was facing a challenge in strategically orchestrating transportation needs across its production plants, warehouses and verticals such as metal container manufacturing facilities. The company was struggling to manage transportation demand and delivery across this complex network using an outdated technology solution. The need for a unified platform for always-on transportation optimization was evident. The company required a digital chain, from order creation to delivery, to gain greater control over transportation spending and to have real-time visibility and orchestration across the network.

Alnatura, an organic supermarket chain operating 139 supermarkets across Germany, faced a challenge in managing its tight space constraints while maximizing product availability and minimizing stock-outs. This was particularly difficult due to the diverse local preferences across its markets and the high costs associated with waste in fresh foods. The company needed to drive more automation, greater accuracy and localization, and increased efficiency for its category management and space planning activities.

Traxion, Mexico's largest logistics provider, has experienced a 28-fold growth since its inception in 2011. With a fleet of 8,000 vehicles and over 1,000 customers, Traxion is three times the size of its nearest competitor. As Traxion's customer base grows, so do customer requirements. The company needs to maximize its speed and responsiveness, while also controlling costs and ensuring profitability. The Mexican third-party logistics market was growing up to 25% per year before 2020. The pandemic dramatically accelerated that growth, with e-commerce in Mexico doubling in 2020, compressing three years of logistics demand into just one year.

Supermercados Peruanos, the largest supermarket chain in Peru, was struggling to accurately forecast demand for fresh and ultra-fresh foods such as produce and meat. The retailer was using a manual and decentralized process, relying on Excel spreadsheets and manual processes to forecast ultra-fresh products, based on history. This approach was revealed to be problematic during the pandemic, as it was unable to manage uncertainty and go beyond human cognition. The company needed an advanced, automated tool that could manage uncertainty and go beyond human cognition. They have millions of dollars invested at their distribution centers and needed to protect those investments with precision, not with averages.

Angelini Beauty, a leading global manufacturer and distributor of fragrances and cosmetics, faced challenges in accurately predicting demand and defining profitable stock levels due to the seasonal and trendy nature of its products and the geographically scattered markets it serves. The company operates in 85 markets worldwide, which means it has a lot of demand variability based on seasonality and shopper preference, not to mention trendy and short-lifecycle products. Prior to partnering with Blue Yonder, Angelini Beauty relied on manual analysis and had no real visibility to actual demand. Their processes were slow and inaccurate.

As the world’s largest express and logistics provider, DHL strives daily to meet its customer requirements by optimizing schedules, loads and processes within its current business constraints. This entails finding the most cost-efficient solutions for determining servicing locations, maximizing transportation costs and identifying consolidation opportunities. The company needed to gain a better understanding of how to quickly provide solutions customer projects and needed more flexibility and agility in controlling their vast network of operations. DHL’s goals were to enable transportation cost savings, improve optimization exercises and communication of results, replicate and evaluate business scenarios and understand the impact of various variables on proposed transportation solutions.

Morrisons, one of the largest grocers in the UK, operates nearly 500 stores serving 11 million customers weekly. The company prides itself on its in-store point of difference - Market Street - which includes fresh food counters offering fresh butchery, seafood, delicatessen and bakery products. However, as fresh products have a relatively short shelf life, Morrisons was conducting three manual markdown events daily. Often, the price was too low and eroded margins or, conversely, it was too high and products failed to sell. The company estimated that it could save millions of pounds in labor by having an automated, optimized pricing solution.

Clipper Logistics, a leading independent logistics company in the UK, is faced with the challenge of delivering an extreme level of speed, efficiency, accuracy, and responsiveness in providing warehouse and fulfillment services to its retail clients. As demand volatility increases and customer expectations grow, Clipper needs the most advanced technology available. The company is tasked with managing massive product volumes and large numbers of returns for its retail customers. The goal is to release inventory on 24 hours’ notice so retailers can move fast and maximize their full-margin sales. Furthermore, the company needs to manage the uncertainty in retail by being agile, flexible, and innovative.

Prinsel, a leading importer and distributor of toys and children's products in Mexico and Central America, was facing challenges in managing its two busy distribution centers. The centers handle over 1,000 SKUs, 7,000 shipments, and 2.5 million individual boxes each year. The warehouses were managed by manual processes, making it difficult to locate and ship products. This lack of visibility negatively impacted both customer service levels and financial results. The company was struggling to meet order deadlines due to the time-consuming manual processes and lack of understanding of warehouse capacity.

Founded in 1930, wilko is a leading UK homes and gardens retailer, with over 400 stores. Despite its growth, the company faced challenges in collecting and applying local shopper data, which led to poorly performing product assortments and visual displays. The lack of a data-driven strategy resulted in inefficiencies in the planning team and a lack of agility in responding to market changes. The company needed a solution that would make the planning team more efficient, more agile, and more driven by facts.