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Home > 4 Warehouse Management System Case Studies

4 Warehouse Management System Case Studies

• July 23, 2020

Successful WMS Implementation Case Studies

Warehouse Management Systems (WMS) represent a major investment in your supply chain and operational efficiency. While it can be difficult to gauge your estimated time to value, these four cases featuring enVista clients provide a warehouse management system business case and showcase outcomes after successful WMS implementations.

In this post, we’ll cover four examples of WMS implementations and how they helped companies to optimize warehouse operations :

• Nature’s Best
• Performance Bike
• Bradshaw International
• Men’s Wearhouse

Four  WMS Implementation Examples

1. nature’s best.

*Note: Since project completion, Nature’s Best has been acquired by KeHE.*

Leading the market of health and natural foods distribution, Nature’s Best serves Certified Organic products in over twelve states. Nature’s Best was experiencing high labor costs based on time and manpower to transport temperature-controlled food products between four buildings on its DC campus. The company’s zones were organized to suit either small or large clients – a key competitive differentiator. Because of the facility layout, the overall distribution process was inefficient; each product was touched 18 times on its way to the customer. Nature’s Best technology, distribution processes and buildings also needed updating to keep pace with growth projections.

enVista was called upon to address and resolve the challenges Nature’s Best was facing and did so using its consult, implement and operate (CIO) methodology to create a customized solution.

Phase One: Consult

A supply chain strategy that met Nature’s Best’s business goals was developed. enVista conducted a material flow analysis and redesigned the internal flow processes to increase efficiencies. As a result, a global WMS was selected that addressed all of Nature’s Best’s concerns and determined construction needs for the distribution center (DC). Operations would be consolidated to one DC, and enVista designed the new facility with various temperature-controlled zones.

Phase Two: Implement

As Nature’s Best began construction, enVista supervised the integration and implemented a Manhattan Associates WMS including interface design, configuration, training, facility preparation and labor standards among other features. Nature’s Best shifted from a mechanized to non-mechanized system and from paper to radio-frequency (RF) devices with voice-based technology. enVista managed the move of $25 million of inventory and trained the company team on new system processes.

Phase Three: Operate

During go-live, enVista ensured a seamless transition into Nature’s Best new facility, systems and processes. Throughout the Consult, Implement, and Operate phases, sales were steady – even growing – and upon completion, the project was delivered on time and within budget. The chosen system required few modifications for Nature’s Best’s business model, which would lower costs and allow for easier upgrades in the future.

The new system reduced labor costs by over 30 percent and more than doubled productivity. Ninety-seven percent of full-time employees were retained, and temporary and non-value-added positions were eliminated. Nature’s Best went consultant-free only four weeks after go-live.

Download Nature’s Best Case Study

Example 2: Performance Bike

Performance Bike is a privately-held, specialty retailer focused on bicycles and accessories. The company had expanded to over 110 retail locations since its founding in 1982. Performance Bike had a DC in Chapel Hill, NC, with over 60 associates and partners with a 3PL in Long Beach, CA.

Due to compliance issues with the U.S. Postal Service barcodes, Performance Bike had to make system changes to its Manhattan PkMS WMS. The company’s experience with Manhattan Associates gave it a flexible approach when considering an upgrade. enVista’s enABLE methodology was used for the upgrade, and many of the roles typically filled by software or consulting companies were completed by Performance Bike.

Because of the prior experience and flexibility of Performance Bike and enVista, the WMS implementation was under budget and on time. Team members from both enVista and Performance Bike worked together to complete and implement the WMS. The vice president of warehouse operations for Performance Bike noted enVista’s customer-centric approach and flexibility.

The WMS upgrade was implemented in less than 6 months. There were very minor changes to the user experience, so trainings were seamless and increased productivity. Performance Bike experienced a pick per hour increase of 50 to 100 units per hour, exceeding the company’s executives’ expectations.

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Example 3: Bradshaw International

Bradshaw International’s Good Cook™ brand is sold in over 30,000 U.S. retail stores. Bradshaw is a leading marketer of kitchenware products and launched Good Cook to incorporate quality, value and service into every product. This philosophy has allowed Good Cook to achieve the best position for kitchen tools and gadgets with 43 percent of the market.

Bradshaw was asked to participate in Wal-Mart’s direct store delivery consolidation (DSDC) program as Good Cook is distributed in the stores. The program was designed to allow shippers to directly replenish Wal-Mart stores in less-than-case-pack quantities. To do so, Bradshaw had to make changes to several parts of its current distribution systems.

Changes to electric data interchange (EDI), order management, and a pick/pack operation integrated with a new WMS would be required to handle the new variable volumes. enVista was asked to help design and integrate the DSDC program. To meet Walmart’s DSDC objectives, the team had to design and build a new pick/pack module, select the technology to be used by the picking team, and integrate it with the WMS. The order management software , EDI software and billing system had to be modified to accommodate the structures required by Walmart’s DSDC program.

The team profiled SKU movements, identified pick and storage mediums to model replenishment rates, and formulated labor plans and proper work flows. Bradshaw IT and enVista worked together to make configuration changes to the RedPrairie WMS and integrate it with the Pick from Light System and EDI software. The joint team also specified data maps from order capture to order management to WMS through EDI transmissions to move the infrastructure to industry standards.

With enVista’s help, Bradshaw successfully integrated the DSDC program into operations. Shipping volumes increased beyond expectations, but the new WMS has allowed Bradshaw to keep up with demand. The program was implemented with almost no customer disruption.

Example 4: Men’s Wearhouse

Founded in 1973, Men’s Wearhouse is one of the country’s largest specialty retailers of men’s apparel with over 700 stores. The stores carry a full selection of high-end men’s clothing and accessories.

Men’s Warehouse’s main DC was a 1.1-million square foot facility in Houston, Texas. It is the core retail distribution center for Men’s Warehouse retail stores, as well as 60 percent of merchandise from K&G Retail stores, acquired in 1999. A significant percentage of its garment-on-hanger merchandise is shipped by dedicated fleet to regional hubs across the country. enVista’s main objective was to consolidate retail and e-commerce systems to run all operations on a single platform and a central material handling equipment (MHE) integration point.

enVista acted as the program management role for supply chain execution and MHE software functions for all facilities. The implementation of the new systems platform occurred in two distinct phases.

The first phase focused on using the new systems platform to more efficiently meet Men’s Wearhouse’s growing e-commerce business needs. A new WMS and distributed order management system were implemented and integrated to an e-commerce web platform. These systems allowed strategic decision making regarding e-commerce order fulfillment and room for growth, along with the accuracy and flexibility necessary for seamless execution and delivery.

Phase two focused on implementing the new WMS and a consolidated warehouse control system (WCS) in Men’s Wearhouse’s Retail Distribution Operation. The WMS replaced the retailer’s legacy system, and the WCS consolidated the management of several operations into one system. Men’s Wearhouse now has the ability to dynamically change product flow, unit allocation, and achieve more effective utilization of Case Level ASN receiving with the new WMS. The system’s ability to recognize and execute on cross-docking opportunities created improved throughput and lower overall processing costs.

With the implementation of a common WMS and standardized processes, Men’s Wearhouse was able to share recourses across operations and respond to seasonal increases in workload more effectively. The implementation of WMS and WCS gives the company the ability to consolidate its distinct Men’s Wearhouse and K&G distribution operations to reduce costs and increase overall processing efficiency.

Download Men’s Wearhouse Case Study

Conclusion: enVista’s WMS Expertise

Getting your WMS right and making sure it’s integrated properly across your supply chain technology stack is critical to realizing quick ROI and improved operational efficiencies. 

enVista has completed hundreds of WMS implementation projects in its nearly two decades of experience, and our vendor agnostic approach to consulting and implementation ensures you get objective help for your most critical projects. We’re passionate about supply chains and delivering solutions that are the right fit for our clients and would love to help you optimize your supply chain.

If you have a WMS project on the horizon or want to learn more about how we can help you, let’s have a conversation .

About the Author

enVista Thought Leadership

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5 Case Studies on Warehouse Management System (WMS) Implementations

Commonly, we study the success stories of others to get inspiration and find new ideas for improving our business or personal efficiency. As a custom WMS development partner, we at HQSofware, also follow best practices and trends to deliver top-notch solutions to our clients. However, based on our WMS development experience, we can already share our own examples of winning warehouse management systems.

In this article, we’ll take a look at 5 successful examples of WMS software to understand how to implement such a system to enhance warehouse productivity.

What is a Custom WMS?

Developing an e-3pl system for warehouse automation, implementing predictive analytics for smart inventory management, providing warehouse navigation to speed up order picking, improving supply management with a wms, developing a wms module to boost marketplace operations, how to maximize wms efficiency.

A warehouse management system (WMS) is a powerful tool that optimizes and streamlines warehouse operations, including inventory management, picking and packing processes, shipping management, etc. A custom WMS, designed according to your unique workflow, eliminates unnecessary features and offers a user-friendly interface. With custom WMS development , you can prioritize factors that are crucial for your organization, ensuring that the system aligns perfectly with your unique business needs.

Let’s take a look at some custom WMS examples and how they’ve helped to overcome warehouse challenges for their respective owners.

It’s no longer enough for a modern warehouse management system to merely provide inventory visibility and assist in order picking and packing. Companies are now striving to maximize operational efficiency by choosing smart systems with advanced features that can simultaneously address a wide range of issues.

In line with this trend, a US-based startup embarked on the development of comprehensive WMS software that adheres to modern requirements. A large international team of developers, including HQSoftware specialists, was involved in the project.

The main goal was to create an advanced system that can automate and optimize many logistics processes and perform some of them autonomously. For example: automatically generate replenishment orders based on customer demand forecasts, or update goods availability and price for buyers in real-time.

In addition, the system facilitates warehouse audits, provides enhanced navigation, integrates with numerous third-party systems, and enables express picking and receiving. With all its innovative features, the E-3PL platform boasts an impressive 99.9% order accuracy and 99.4% same-day order delivery.

This WMS implementation case study highlights the potential for comprehensive software to enhance virtually any warehouse operation. Achieving this requires a thorough analysis of every process within your warehouse and careful consideration of how advanced technology can drive improvements. This is especially beneficial if you decide to turn to custom WMS software development , as this allows you to build a system that meets your business needs in the best possible way.

Not wasting financial resources and being able to meet changing customer demand are deeply desired by every business and a must-have feature of modern WMS software.

Our client approached us with just such a request. They needed to upgrade a legacy WMS and implement predictive analytics capabilities to optimize warehouse inventory.

To accomplish this, our development team carefully selected the most suitable Machine Learning models capable of analyzing both historical and real-time operational data. The system provides data-driven replenishment recommendations tailored to specific parameters such as supplier delivery terms and minimum stock quantities. As a result, the client was able to reduce inventory costs by 15%.

The power of predictive analytics lies in its ability to learn and adapt to your unique business characteristics, offering personalized recommendations on how to improve it. So, you can benefit from optimal stock levels, excess-cost elimination, efficient space utilization, and a proactive response to customer needs, gaining a strong competitive edge in the market.

Since goods in a warehouse are not arranged as in a supermarket but are stored in boxes with numerical location identifiers, finding the right item can be a daunting task for pickers.

To address this WMS challenge and streamline order picking, our client — a retail company from Germany — decided to implement enhanced warehouse navigation . The feature creates optimized picking routes according to the picker and other items’ location and warehouse configuration.

The solution is delivered as a cross-platform mobile app that provides a map with a picking route and offers voice and visual guidance. With the app, pickers now spend 25% less time on order picking .

Even if you have many large warehouses with different layouts, this is no reason to overlook such a feature. Our developers can create an intuitive graphical interface that allows you to create any warehouse layout, as was implemented in this WMS case study.

Want to create a WMS solution to improve your warehouse operations? We’re ready to help! HQSoftware has a team of skilled professionals ready to tackle the project. Let’s talk! Anna Halias Business Development Manager Get a Free Quote

In an ideal world, all suppliers would have compatible systems that seamlessly integrate with your WMS. However, in reality, you may encounter scenarios where a vendor relies on Google Spreadsheets for inventory tracking or where having a large number of suppliers makes collaboration within a single WMS challenging.

Well, we know several examples of WMSs that include a separate platform for onboarding and communicating with suppliers. We’ve developed such a platform as well . It enables a US retailer to connect with all suppliers in a single interface. Here, suppliers can upload product catalogs, manage item availability, and set prices, while the customer can place purchase orders and establish collaborative agreements.

An important feature of this platform is its ability to handle various data formats, enabling suppliers to post catalogs in their preferred format, which was quite a challenge for our development team. We also ensured system scalability, enabling the customer to expand their network of suppliers.

With this platform, the customer now enjoys seamless order placement, improved supply management, and a 37% reduction in product delivery delays.

The process of publishing and updating items on a single marketplace is relatively straightforward. You fill out the product details, add images, and configure display settings. This is true for several products or catalogs hosted on a single platform. But when you’re a 3PL provider responsible for hosting hundreds of clients with thousands of items on multiple marketplaces, it’s more like a nightmare.

Therefore, for one of the 3PL providers, the HQSoftware team has developed a module for the company’s custom supply chain software system that can automatically publish and update catalogs on several marketplaces and allows for manual item updates within one interface. By synchronizing with the customer’s system, the module ensures consistent and accurate data across platforms.

Within the module, the customer can also customize the display of different products according to specific parameters, such as particular display times, different prices for different times of the day, etc. With robust data exchange mechanisms implemented by our team, the module seamlessly uploads files with all data, speeding up product management tasks by 30%.

Even if you’re not a 3PL provider, such a feature can greatly simplify marketplace management. You no longer have to manually navigate through each product listing on every platform to make changes. All this can be done with a few clicks through a user-friendly interface.

Based on the expertise we’ve gained from our WMS implementation case studies, we understand that leveraging the advantages of WMS software takes more than simply finding or developing a suitable system. It’s also important to focus on proper WMS implementation . Consider the following actions.

• Define system requirements . Conduct a thorough analysis of your warehouse operations to understand how a new system can automate and improve established processes. This analysis will help you define the specific requirements for your WMS.
• Create an implementation plan. The step-by-step plan will help you overview the whole cycle of WMS implementation and control the progress. A common WMS implementation project plan example includes several key phases, starting with planning, then analysis, then implementation, testing, training, and finally, deployment.
• Clean up data. It’s a good idea to get rid of outdated or duplicate information that can lead to errors and slow down the process of migrating data to the new WMS.
• Integrate a WMS with other systems. This greatly enriches WMS functionality and allows you to get valuable insights from both internal and external platforms.
• Test a WMS. Verify that the system can process all your data smoothly without any interruptions or delays. It is important to test the system’s interaction with third-party systems and ensure it meets the needs of end-users.
• Train employees. Comprehensive training ensures that your employees know how to use the system effectively and helps overcome potential resistance to change. Create visual and interactive manuals and step-by-step tutorials that employees can refer to when they encounter difficulties.

But one of the most important factors in successfully implementing a WMS is choosing a reliable and trusted WMS provider, especially if you opt for a custom WMS. The capabilities of your system and its successful implementation will depend directly on the expertise of your development partner.

At HQSoftware, we have extensive experience not only in creating comprehensive WMS systems but also in working with cutting-edge technologies that can enhance WMS functionality, such as Artificial Intelligence , Machine Learning , IoT , etc. Contact us to learn more about our WMS development services.

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To ensure the outstanding quality of HQSoftware’s solutions and services, I took the position of Head of Production and manager of the Quality Assurance department. Turn to me with any questions regarding our tech expertise.

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Amazon: a case study in how strategic warehouse placement can drastically reduce shipping times.

Updated: Apr 27, 2022

Few businesses can compete with Amazon—not just as a retailer, but also in shipping, data management, and even warehousing. To become the juggernaut it is today, Amazon has evolved to provide many of its necessary service needs. 

For its warehousing needs alone, for example, Amazon reportedly owns nearly 319 million square feet of fulfillment center floor space in the United States. Though that is a massive number, consider that Amazon’s warehouse placement is designed to keep shipping times as low as possible. In other words, Amazon warehouses have been strategically placed all over the country. 

Strategic warehousing allows Amazon to ensure that goods are already nearby when a customer places an order. It also enables the company to focus on efficiency and cost-effectiveness for shipping. This is how Amazon can offer free next-day or two-day shipping.  

With these facts in mind, let’s look at how strategic warehouse placement can help other companies reduce their shipping times. 

Less Time on the Road

Transportation occupations are some of the most dangerous jobs . In 2018 alone, workers’ injuries and illnesses in transportation and material moving accounted for 20% of all injuries. These statistics also include related transportation roles, such as mechanics and transport-related warehouse jobs.

Strategic warehouse placement reduces the time that trucks and other transport options need to be used. Shorter travel periods can also decrease the time that vehicles are on the road and, thus, can help with driver fatigue. Furthermore, using strategic warehouse placement in high-volume areas will:

• Ensure the fastest shipping times by decreasing the hindrance of supply bottlenecks.
• Keep high-volume items well-stocked, eliminating unplanned shipments.
• Benefit from courier usage to deliver goods where larger delivery options may struggle (such as residential or historic areas).  

Additionally, warehouses built in strategic locations can reduce the load of other warehouses. Not only does this decrease shipping times in the area, but it also increases the efficiency of the once-beleaguered warehouse.

Optimization In, Optimization Out

A strategically placed warehouse is optimized inside and out. Shipping costs and speeds are affected by more than the distance. Without optimized functions and employees, warehouses and shipping will suffer.

No matter the industry, however, warehouse safety is essential. Injured workers won’t be working, and could be costing money. Perhaps more importantly, a poorly managed warehouse will drag down morale, handling speeds, and efficiency. Mistakes will pile up, just like the hazards that surround the workers.

To achieve an optimized and safe warehouse, the following guidelines must be followed:

• Rigid daily protocols, especially around safety, awareness, and internal assistance.
• Incentivize safe efficiency, not bottom-line numbers. Breakneck speed is only temporarily sustainable.
• Storage and organization pipelines must always be adhered to.
• Use optimized scheduling to keep shipping and receiving on different shifts.

Each of the above-mentioned tips not only ensures smooth operations, but also keeps the employees and their safety in mind. Unless the warehouse is entirely automated, optimization must consider the humans within.  

Technology and automation should still be used, but focus on systems that work with the human element in mind. Use machine learning and logic-oriented technologies to study your warehouse statistics. Optimize how the team at hand works, instead of forcing them into a “pre-optimized mold.” 

In short, if the warehouse and its employees are optimized, then shipping times too will be optimized.

Strategic Location Keeps the Goods Close By

Today’s supply chain management goals are meant to ensure customer satisfaction . Two-day or next-day shipping is no longer a leg up over other services. Rapid shipping is now the expected offering. Larger fleets or faster processing lines alone won’t speed up shipping times if the warehouse is located across the country.

Therefore, strategically placing warehouses ensures that goods are always within your customers’ desired shipping times. Amazon’s vast number of warehouses allow for same-day shipping in some areas. Often, within hours of an online order, the purchased item is at the customer’s door. It doesn’t get much faster than that. This is achieved by the vast amount of strategic square footage Amazon devotes to customer satisfaction.

Of course, not every business can afford millions of feet of storage space. Still, a company can decide where best to locate the storage it can afford. For example, warehouses next to major shipping hubs can take better advantage of increased shipping options. Major metropolitan areas benefit from having warehouses nearby, especially in high-volume areas.

Large metropolitan areas also provide other strategic benefits, including:

• Better access to existing infrastructure.
• A more significant potential labor pool.
• A greater area of serviceable customers, plus the ability to offer reduced shipping times to a major section of customers.

Keeping warehouses close to the manufacturing locations can reduce shipping times on the back end. However, strategically located warehouses next to major shipping hubs can benefit from nearly the same back-end fulfillment, and provide customers with even quicker delivery times.

Final Thoughts

Warehouses use massive amounts of capital, both in start-up mode and during normal operations. They can be dangerous, especially with a high-velocity mix of employees and machinery. Warehouse use and placement must therefore be strategic to maximize efficiency at all levels. From employee safety to customer satisfaction, where you place a warehouse has long-existing ramifications. 

Companies have found success working backward with the customer as the end goal. Strategically located warehouses allow logistics to focus on the fastest route to the customer. Be it extra stock for a high-volume item, or simply shorter shipping times from the warehouse to the customer’s door, warehouse placement is critical.

Rachel Perez is an Outreach Associate with North Star Inbound and wrote this piece working in tandem with BigRentz . An honors graduate of New York University, she is passionate about writing about business, e-commerce, construction, and travel. When not writing, she enjoys spending time in the Florida sunshine.

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Warehouse Management Software: A Case Study 

• Post author: Maryliya M J
• Post published: January 11, 2024
• Reading time: 12 mins read

Warehouse Management Software (WMS): A Case Study 

Table of contents.

Warehouse management software (WMS) has become an integral tool for modern businesses seeking to optimize their supply chain operations. With the ever-increasing complexity of managing inventory, orders, and logistics, implementing an effective WMS solution can provide significant advantages.

Introduction to Warehouse Management Software (WMS)

Understanding warehouse management systems (wms).

Warehouse Management Software ( WMS ) is like your personal assistant for managing the chaos of a warehouse. It’s a fancy computer program that helps keep track of inventory, streamline processes, and make your life a whole lot easier. Think of it as the Hermione Granger of your warehouse – organized, efficient, and always on top of things.

Evolution and Advancements in WMS

Gone are the days of scribbling inventory numbers on a piece of paper and playing detective to find that missing box of widgets. WMS has come a long way since then. It has evolved from simple spreadsheets to sophisticated systems that can handle complex tasks like inventory tracking, order processing, and even automated picking and packing. It’s like upgrading from a flip phone to the latest iPhone – everything just works better.

Benefits of Implementing WMS

Implementing a WMS might sound like a hassle, but trust me, the benefits are totally worth it. With a WMS by your side, you can say goodbye to inventory nightmares, reduce errors, and improve overall efficiency. It’s like having a superpower that makes your warehouse run smoother than a freshly oiled machine. From enhanced inventory visibility to streamlined order fulfillment, WMS has your back.

About the Client

Our client, a prominent e-commerce company, faced challenges in efficiently managing its warehouse operations. With a growing inventory and increasing order volume, they recognized the need for a robust Warehouse Management Software (WMS) to streamline inventory tracking, order fulfillment, and overall warehouse efficiency. 

Project Overview

The project involved developing a .NET-based Warehouse Management Software that seamlessly integrated with the client’s existing systems. The primary objectives were to provide real-time visibility into stock levels, automate order processing, and optimize the warehouse layout for improved picking and packing processes. 

The Challenges

• Inefficient Inventory Tracking: The existing systems lacked real-time visibility, leading to inaccuracies in inventory tracking. 
• Manual Order Processing: Order fulfillment processes were time-consuming and prone to errors due to manual interventions. 
• Suboptimal Warehouse Layout: The warehouse layout needed optimization to enhance picking and packing efficiency. 

The Solution

Our team, comprising skilled developers and project managers, collaborated to design and implement a comprehensive Warehouse Management Software. Technologies such as .NET, SQL Server, and REST APIs were employed to ensure a robust and scalable solution. 

Key Features of the WMS

• Real-time Stock Visibility: The WMS provided instant visibility into stock levels, reducing the risk of stockouts and overstock situations. 
• Automated Order Processing: Orders were processed seamlessly, minimizing errors and accelerating the fulfillment process. 
• Optimized Warehouse Layout: The software employed intelligent algorithms to optimize the warehouse layout, resulting in improved picking and packing efficiency. 

The Outcome

The Warehouse Management Software was successfully deployed, leading to significant improvements in warehouse operations. The client reported enhanced efficiency in inventory management, reduced order processing times, and improved overall warehouse productivity. 

By leveraging the benefits of WMS, such as enhanced inventory visibility, streamlined order fulfillment processes, and improved accuracy and efficiency, the company was able to overcome their warehouse management challenges and achieve remarkable results. The lessons learned from this case study provide valuable insights for businesses considering the adoption of WMS, emphasizing the importance of careful selection, thorough implementation planning, and seamless integration with existing systems. Ultimately, the successful implementation of WMS opens doors to increased productivity, cost savings, and improved customer satisfaction, making it a strategic investment for any organization looking to optimize their warehouse operations.

Our team’s expertise in developing a tailored Warehouse Management Software using cutting-edge technologies resulted in a solution that addressed the client’s challenges effectively. The implementation of real-time visibility, automated order processing, and warehouse layout optimization contributed to a more streamlined and efficient warehouse operation. 

Are you facing similar challenges in warehouse management? Contact us today to explore how our expertise in WMS development can transform your warehouse operations and drive efficiency. 

What is Warehouse Management Software (WMS) and why is it important?

Warehouse Management Software (WMS) is a software solution designed to efficiently manage and control various aspects of warehouse operations, including inventory management, order fulfillment, and logistics. It is important because it helps businesses optimize their warehouse processes, improve inventory accuracy, streamline operations, enhance productivity, and ultimately deliver better customer service.

How does a WMS solution benefit businesses?

A WMS solution offers numerous benefits to businesses. It provides real-time visibility into inventory levels and locations, enabling effective inventory management and reducing stockouts. It automates and streamlines order fulfillment processes, improving speed and accuracy while reducing errors. WMS also optimizes warehouse layout, resource allocation, and workflow, leading to increased operational efficiency, productivity, and cost savings.

What considerations should businesses keep in mind when selecting a WMS solution?

When selecting a WMS solution, businesses should consider factors such as scalability, ease of integration with existing systems, customization options, vendor support, and cost. It is crucial to assess specific business requirements, evaluate the software’s functionality, and determine whether it aligns with the organization’s long-term goals. Conducting thorough research, seeking recommendations, and requesting demos or trials can help make an informed decision.

Is it challenging to integrate WMS with existing systems and processes?

Integrating WMS with existing systems and processes can present challenges, mainly due to differences in data structures, formats, and compatibility. It requires careful planning, data migration, and coordination between the WMS provider and internal IT teams. However, with proper communication, collaboration, and expert guidance, businesses can overcome integration challenges and achieve seamless connectivity between WMS and other enterprise systems.

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Case Studies

The automotive maker Renault has installed the Easy WMS warehouse management system by Mecalux in its production warehouse in Seville (Spain). The manufacturing centre in this city focuses on the assembly of transmissions and the warehouse supplies manufacturing ...

Danone’s distribution centre in Valdemoro (Spain) must cope with a very high-paced daily work rhythm: managing between 500 and 600 SKUs and preparing up to 700 orders. It is an all-in-one omnichannel warehouse, i.e. orders are sent to retailers, wholesalers and c...

Decathlon has chosen Mecalux’s shelving for picking once again to manage its omnichannel logistics. After equipping its warehouses in France, Germany, Italy and Poland, it is Northampton’s (UK) turn. With 35,000 SKUs, the warehouse preps and ships out 3,000 order...

Interlake Mecalux and partner Andersen Material Handling have equipped a 13,935 m 2 warehouse in Miami, Florida, for Dufry, a travel retailer. The project includes adjustable pallet racks and the high-density push-back racking system. Overall, the syste...

Hayat Kimya

Hayat Kimya is a leading manufacturer in the Eurasian fast-moving consumer goods market, specifically in the sector for hygiene and cleaning products. Founded in 1937, with its headquarters in Turkey, the company currently has 5,200 employees and exports to 101 c...

Here you can see some real solutions that Mecalux has developed. Contact us so we can assess the ideal solution for your company.

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Automated clad-rack warehouse of Michelin integrated with manufacturing

Porcelanosa

Mecalux completes the process of automating the porcelanosa group’s warehouses in castellón, spain.

Next-generation automated clad-rack warehouse: a sure bet to streamline of logistics processes at Cepsa

Espace des Marques

Omnichannel warehouses with 70,000 skus.

Schneider Electric

How to achieve the ideal balance between speedy picking and storage capacity.

Efficient conveyors improve storage at Nestlé in Girona

IKEA Components

Ikea components automates its warehouse in malacky without disrupting operations.

A 100% automated, turnkey warehouse for Würth in La Rioja

Easy WMS of Mecalux runs the warehouse of the car maker Renault

Novartis automates its supply chain in Poland

Coca-Cola Refrescos Bandeirantes

Warehouse with coca-cola soft drinks of refrescos bandeirantes in brazil.

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Earthquake-proof racking: warehouse with mecalux conventional racking on the pacific rim.

Decathlon has opened a new omnichannel warehouse in Northampton (United Kingdom)

The Adidas sportswear and footwear store in Pennsylvania, USA

Mecalux installs a new logistics centre for DHL on the outskirts of Madrid

Mecalux has equipped the new Unilever distribution centre with pallet racking

BASF: digitisation for just-in-time production

Danone’s warehouse for the infant and medical nutrition product line in Madrid

Digitisation transforms the supply chain

Royal Canin

Multiple solutions to manage pet food products, {{reference.name}}, {{reference.pcase.name}}.

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Distribution Network Cost- A Mini Case Study

Logistics Bureau

SEPTEMBER 7, 2022

Related articles on this topic have appeared throughout our website, check them out: The 7 Principles of Warehouse and Distribution Centre Design. Spotlight on Triadic Distribution Centres Making Triadic, Dyadic and Monadic Sense of your Warehouse . The Long and Short of Designing a Distribution Network.

Companies Using ERP: Case Studies

SEPTEMBER 22, 2021

Case Study #1: Noble Biomaterials. Read the full Noble Biomaterials case study to learn more. . Case Study #2: Veoneer. The company operates multiple sites in different locations, as well as four warehouses in different districts. Read the full Veoneer case study to learn more.

AutoStore and the Rise of Flexible Automation: The Parts Town Case Study

MAY 7, 2018

Historically, we talked about warehouses as being manual or highly automated. Manual warehouses are more flexible. Highly automated warehouses have much higher throughput, but their lack of flexibility adds risk.

Case Study: DSV Implements a Single-Instance Control Tower with a Global Footprint

After having opened a new warehouse in Johannesburg - the largest integrated logistics center on the continent - a multi-national FMCG Healthcare company approached DSV South Africa (SA) for services across the end-to-end supply chain.

Watch: Alpine Supply Chain Solutions & Ecentria: A Case Study

APRIL 27, 2023

Huge growth in sales led to the need to optimize inventory, fulfillment and warehouse operations at Ecentria, say Michael Wohlwend, managing principal of Alpine Supply Chain Solutions, and Andrew Mironov, head of operations at Ecentria.

AutoSchedler.AI is Named Sponsor of the Supply Chain Matters Blog

Supply Chain Matters

AUGUST 29, 2024

As Founder and Managing Editor I am pleased to announce to our global-wide Supply Chain Matters readership that Cloud based warehouse management orchestration provider AutoScheduler.AI This deployment has since expanded to this customer’s other warehousing facilities. AutoScheduler Overview AutoScheduler.AI

Warehouse Robots Enable a Digital Transformation

AUGUST 13, 2018

Because about half of this company’s 2017 revenues are related to warehousing services, several of their digital projects have been related to improving efficiency in their warehouses . This case study describes their approach to testing out mobile logistics robots.

Primer for Control Layer Technology Platforms Applied to Warehousing and Customer Fulfillment Processes

MARCH 14, 2023

Supply Chain Matters provides a first installment in a four-part technology market education series where we address the evolving use of Cloud based control layer technology platforms applied to warehousing and customer fulfillment processes. This initial posting provides readers with an overview and primer for this type of technology.

Why Packaging Matters with Phillip Akhzar

FEBRUARY 27, 2023

Arka’s API uses AI to auto-replenish packaging inventory for warehouses and 3PLs. Arka works with both shippers and warehousing companies. For warehousing companies: Arka automates the packaging ordering process by connecting Arka’s API to the warehouse management system (WMS).

Machine Learning in Supply Chain: Definition, Uses, Case Studies

APRIL 4, 2023

We also break down several case studies of companies currently using machine learning in their supply chain processes. Machine learning can improve the supply chain in numerous ways, from tracking and predicting warehousing needs to delivery optimisation, and customer demand forecasting. What is machine learning?

Warehousing Case Study: JD.COM 3PL Warehouse

JULY 14, 2024

As the largest retailer in China, JD.COM serves 99% of the country, providing unparalleled same-day and next-day delivery. With approximately 600 million active customers, JD.COM faces costly, inefficient, and labor-intensive operations, compounded by high turnover rates. To address these pain points, JD.COM partnered with ForwardX Robotics.

Top Mobile Barcoding Case Studies for Oracle’s JD Edwards

OCTOBER 14, 2020

In this article, we’ll explore top case studies illustrating how companies added mobile barcoding technology to get more out of their JD Edwards ERP investment. It relies on 32 warehouses situated strategically around the country, each with extensive inventory volume, to accomplish this.

Case Study: Reducing Excess Inventory

Demand Driven Technologies

JANUARY 11, 2022

But when the inventory piles up in your warehouse because you don’t have the other materials you need to manufacture your products? It’s hard to pass up a good deal from one of your preferred suppliers. That good deal starts to seem less attractive. Frustrated by inventory inefficiencies, supply chain leaders at Ukrainian pet food.

TMS for SMB: A Case Study with Carhartt

OCTOBER 19, 2016

Rapid growth, coupled with new market segments and channels (including ecommerce), prompted Carhartt to embark on a multi-million dollar upgrade of its distribution center, which included investments in warehouse management and transportation management solutions.

How Food Manufacturing Software Drives Profit [w Case Studies]

AUGUST 11, 2020

The right software will also improve operational processes, boost warehouse efficiency and reduce waste. For example Stock Age by Stock Keeping Unit (SKU) can be cross-referenced with warehouse location to see which ingredients are sitting on the shelf and need to be moved (perhaps with a local promotion or price change).

Flexible Warehousing with Flexe CEO Karl Siebrecht

MARCH 24, 2023

Karl Siebrecht and Joe Lynch discuss flexible warehousing , which is exactly what Karl and the Flexe team provides to their customers. Key Takeaways: Flexible Warehousing Karl Siebrecht is the Co-Founder and CEO of Flexe, a company that solves the hardest omnichannel logistics problems for the world’s largest retailers and brands.

Understanding the Profitability of Omnichannel Retail is a Problem

NOVEMBER 20, 2023

But one thing you notice as you go to omnichannel software vendor’s web sites and examine customer case studies , the case studies may talk about retailers growing their revenues by 100% or more, but none talk about how much profitability grew. These new order fulfillment paths allowed retailers to rapidly grow sales.

Watch: Romark Logistics and Gather AI: A Case Study

APRIL 9, 2024

A case study about the application of drones employing artificial intelligence to the warehouse operations of Romark Logistics.

Find Your Warehouse Maturity Phase

Find Your Warehouse Maturity Phase Every day, we hear, read, and talk about warehouse automation. Our partner Zebra Technologies designed a five-phase warehouse maturity model to help businesses identify where they fall in the automation race and how to reach the next phase. Download the Warehouse Maturity Model Checklist.

7 Traits of Great Supply Chain Leader: A Case Study of Tim Cook

OCTOBER 3, 2013

Cook reduced number of warehouses , from 19 to 9 and slashed inventory level from 2 months to 1 month. So he reduced number of key suppliers, from 100 down to 24. Cook also asked them to consider the price discount and relocate closer to Apple''s factory. By September of 1998, inventory level was down to 6 days.

Physician Office Case Study: Hybrent provides supply chain efficiency at multi-site locations

FEBRUARY 6, 2019

And, because Village Podiatry locations are scattered around the region and it does not have a warehouse that supplies can be delivered to, it is important for the accounts payable department to know immediately when a product is delivered. The old system didn’t provide this option. Ross is satisfied with the changeover to Hybrent.

Implementing RFID for Manufacturing Visibility: A Case Study

DECEMBER 8, 2014

Likewise, maintenance personnel will be equipped with a mobile RFID reader to read and log maintenance work done on a stillage and maintain historical data.

A Case Study in Reverse Logistics Optimization!

Supply Chain Game Changer

NOVEMBER 23, 2018

Inadequate planning and execution resulted in excess and obsolete inventory and poor utilization of warehouse space. The post A Case Study in Reverse Logistics Optimization! Difficulties forecasting demand in a high-volume repair environment caused inventory costs to skyrocket. The Solution. Learn more at [link].

Delivering Green: Three Case Studies in Low-Carbon Logistics

MIT Supply Chain

APRIL 29, 2013

Caterpillar is the subject of one of three case studies that show how supply chain management can support both environmental and financial goals. Here are three case studies that offer clear, irrefutable evidence that sustainability and profitability can be compatible in the supply chain domain.

Adexa is Recipient of 2024 Top Supply Chain Projects Award

JUNE 17, 2024

About Supply & Demand Chain Executive Supply & Demand Chain Executive is the only supply chain publication covering the entire global supply chain, focusing on trucking, warehousing , packaging, procurement, risk management, professional development and more. Food Logistics also operates SCN Summit and Women in Supply Chain Forum.

What is picking in a warehouse?

6 River Systems

DECEMBER 13, 2019

Warehouse picking refers to the process where individual items are picked from a fulfillment facility to satisfy customers’ orders. It’s an essential aspect of order fulfillment and is considered one of the most expensive and labor-intensive activities for warehouses .

Case Study: People and Processes Drive Supply Chain Improvements at Honeywell

MAY 8, 2019

Create a load plan for the warehouse and daily share files. To solve the issue of missed pickups, warehouse dock clutter, and rolled bookings, we shifted more volume toward an incumbent carrier that had a drop yard near our warehouse . Send rebooking advice to our Freight Forwarder. Wednesday, May 15 in Grand Sonoran E.

Optimization and Execution: How Manufacturing can lead the Industry Renaissance

DELMIA Quintiq

JUNE 9, 2020

They also must be working together in harmony to achieve maximum benefit from their capabilities: MOM Specifics: Visibility, synchronization and control over ALL operations: production, quality, warehousing , maintenance and field operations. Each solution has inherent value but are less effective when implemented in isolation.

NOVEMBER 8, 2022

Find Your Warehouse Maturity Phase. Every day, we hear, read, and talk about warehouse automation. Our partner Zebra Technologies designed a five-phase warehouse maturity model to help businesses identify where they fall in the automation race and how to reach the next phase. Download the Warehouse Maturity Model Checklist.

Efficiently Picking Your Way to Success: Best Practices for Improving Order Picking Speed and Accuracy in Warehouse Management

MARCH 10, 2023

Order picking is a critical process in warehouse management that involves selecting items from inventory and assembling them into customer orders. The accuracy and speed of this process have a significant impact on warehouse efficiency, customer satisfaction, and ultimately, business profitability. My Warehouse is a Mess!

Free Trade Zone – Is Your 3PL Giving You All the Warehouse and Distribution Cost Savings You Deserve?

ModusLink Corporation

FEBRUARY 8, 2023

Fulfillment Free trade zones, or FTZs, are controlled places in a country that offer warehouse and distribution services for goods from foreign markets, excluding them from paying taxes on those goods. These include: People and staffing requirements include skilled workers and managers that will do the daily warehouse operations.

Lull Case Study: Order Fulfillment that Doesn’t Keep You Up at Night

OCTOBER 11, 2018

Get the PDF of Lull’s case study >> Challenges to Order Fulfillment. The FLEXE Supply team sourced additional warehouse providers in the FLEXE network—all of which were already running on the FLEXE software platform. Blog and video: 2018 D3: Future-Proof Your Warehouse Strategy. 30% reduction in FedEx costs.

Unlocking the Value of Global Supply Chain: the Case Studies

JULY 7, 2014

In order to control its supply chain, they use a central warehouse to Germany to receive and ship products to local distribution centers in different countries. They don''t invest in production facility at all because they utilize a network of nearly 700 suppliers located in Asia and Europe.

Fulfillment That Makes You Smile: Smile America Partners Case Study

3PL Insights

FEBRUARY 2, 2023

The portal was integrated with Evans’ warehouse management system (WMS). Evans associates designed a unique pick and pack process in the warehouse using barcodes to trace inventory in the WMS. Download the case study here. This integration allows for faster order processing and inventory visibility.

Flexible Warehousing Solutions: A Public Goods Case Study

Amware Logistics and Fulfillment

SEPTEMBER 22, 2020

In this article, we’ll showcase Amware's flexible warehousing solutions in helping Public Goods respond to a 500% spike in orders. This is certainly true within the world of logistics, where order volumes – especially those for essential household products – have increased dramatically since March.

Case Study: How Generac Power Systems Cut Millions from Its Global Transportation Spend

CH Robinson Transportfolio

MARCH 28, 2018

Alan’s team can see the 40’ containers arriving at the port and they can track the freight as it is moved to a warehouse and is consolidated onto 53’ intermodal containers. The post Case Study : How Generac Power Systems Cut Millions from Its Global Transportation Spend appeared first on Transportfolio.

Warehouse Wins: Leveraging Software to Transform Inventory Challenges into Inventory Triumphs

JUNE 2, 2023

A common “slow zone” in the warehouse . Even though new warehouse software may require an initial investment, the efficiencies gained quickly pay off, providing a return on investment, better known as ROI. When it comes to warehouse optimization, relying on smart, innovative software solutions is hard to beat.

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Logistics and Supply Chain Case Studies

Review our case studies to see how we’ve helped major corporations turn logistical ideas into a reality., leading beverage distributor, penske logistics helps beverage distributor rapidly establish new warehousing operations.

When this distributor had to expand its operation quickly to counter a competitor, they turned to Penske to deploy a customized solution.

Baby2Baby Donation Transportation

Coordination and planning lead to successful transport of $3 million clothing donation.

Penske Logistics worked with Baby2Baby, a nonprofit that provides basic essentials to impoverished children, and Old Navy to transport $3M of clothing donations.

Luxury Product Manufacturer

Penske logistics reduces inventory shrinkage, improves overall inventory management.

A leading producer of fine luxury products required a partner who could improve their warehouse and distribution operations and reduce the theft.

Poultry Supplier

Transporting food items requires extra care and expertise.

Poultry producers, navigate a complex array of supply and delivery challenges to ensure their food arrives fresh, wholesome, and on-time.

Building Products Manufacturer

Customized fleet technology solution.

A leading building products manufacturer sought to streamline its supply chain operations and expand its fleet while improving visibility through the implementation of fleet management technology.

National Wholesale Distributor

A national wholesale distributor case study.

A national wholesale distributor of heating and air conditioning supplies was struggling to manage its complex supply chain and maintain high levels of customer service, which is a top priority.

Looping Process Ensures Continuous Production

Penske collaborated with Novelis to create a closed-loop recycling network that moves finished aluminum coils and transports scrap for new production.

A Global Manufacturer

Optimizing activities in the distribution center.

Penske worked with this global manufacturer to optimize its inventory routing and mode selection and to improve visibility to its supply chain.

Quick Service Restaurant

Food and beverage in-store delivery and warehousing.

Penske helped this restaurant chain get its supply chain fundamentals in place with the right logistics tools, truck driver training and warehousing solutions.

Tier 1 Automotive Component Supplier

Managing the inbound supply chain.

Penske helped this supplier minimize supply chain disruptions by designing a network that optimized mode selection, routing and analysis.

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Improving warehouse operations—digitally

Warehouse operations are increasing in complexity with time. The growth of e-commerce has led to a proliferation of SKUs, and there’s an ever-growing need to delight customers by offering super-fast fulfillment. Technology is a factor as well: as new automation systems come onto the market, operations leaders must face the challenge of keeping pace and understanding which technologies apply and what kind of impact they can generate.

Worldwide, companies spend an estimated $350 billion a year on warehousing, and that number grows each year as pick sizes shrink and costs balloon, raising pressure not just on margins but also on service levels.

The need to improve both sides of the equation may be obvious, but the question is how. Trial-and-error is not an option: companies cannot simply shut down a warehouse so they can tinker with new layouts and workflows to see what works best.

But the better news is that they don’t have to. A few companies are already able to design and visualize their warehouse operations virtually via “digital twin” simulations. The simulations allow companies to create virtual models of their existing facilities, and then test different scenarios—no shutdowns required.

This digital warehouse-design approach lets companies experiment with different floor plans, workflows, and other variables to assess the overall impact virtually. Operations leaders can see the impact of changes in a wide range of factors, including the SKU mix, order and shipment profiles, seasonal demand spikes, productivity initiatives, automation options, and a host of other issues that impact warehouse performance. This level of detail allows warehouse designs to be optimized in advance, before anyone starts moving physical assets.

The process typically takes six to ten weeks. The revamped warehouse designs that result can help companies improve efficiency by 20 to 25 percent, before spending the money to test or pilot the changes (exhibit).

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The power of digital simulations.

Digital warehouse design has a wide range of applications, from productivity initiatives at existing facilities to mergers, warehouse consolidations, and new warehouse construction. Across all applications, however, the benefits are reasonably consistent: sizable savings in operating expenses from productivity improvement, as well as in capital expenses from optimizing the deployment of material-handling equipment, storage assets, and targeted, right-sized automation systems.

The approach removes bottlenecks to improve efficiency and effectiveness, and enables optimal slotting and product flows to meet service requirements at the lowest possible cost. Most important, digital warehouse design identifies the full potential of a given facility, rather than forcing companies to settle for incremental improvements to the as-is layout.

Critically, the process also enables companies to gauge the potential impact of mechanization and automation options across the entire spectrum of vendors and products on the market. These technologies can be powerful tools to reduce space and increase efficiency. But in some cases, incorrect or inappropriate automation can actually create more problems than it solves. Digital modeling lets companies see what is possible from a range of technologies and applications, before they make any investment decisions.

Transcending traditional improvements

Of course, most companies know they need to improve their warehouse operations. But they struggle to identify and make the needed upgrades, due to limited data and internal expertise. Quite simply, many companies lack the full set of capabilities needed to assess various warehouse improvement options and create a business case that incorporates capex investments and running costs.

Some rely on third-party logistics providers, but even those vendors often lack the breadth of expertise to see what is truly possible with alternative warehouse designs and operations. A related problem is that most traditional methods to design or revamp warehouses use computer-aided design software (CAD)—which is resource-heavy and time-consuming, and doesn’t allow companies to calculate the impact of new changes or anticipate second-order effects. Digital warehouse design, by contrast, offers a low-risk way to visualize and optimize layouts, allowing companies to rapidly identify real, feasible solutions that deliver quick impact.

For example, a North American manufacturer decided to consolidate several regional manufacturing and warehouse locations into a single campus, with separate buildings dedicated to manufacturing and warehousing. However, it faced several challenges, including capital constraints, insufficient warehouse space, and a need to move fast.

Instead of relying on traditional tools, the company used a digital warehouse-design approach to simulate various options across warehousing, kitting (assembly of related items into a single “kit” for shipment), and value-added operations. The digital tools allowed the company to develop detailed OPEX and CAPEX estimates for both manual and automated solutions, making it far easier to evaluate various business cases. In all, the company reduced planned capex by approximately 10 percent and operating expenses by more than 30 percent.

Digital warehouse design can also help companies rethink existing facilities. For example, another company deployed digital warehouse-design and simulation tools to optimize and revamp its operations in a warehouse currently in operation. It built models to test various layouts, material-handling-flow scenarios, picking methods, and targeted automation solutions.

Starting from an optimized slotting design, the digital twin analyzed historical orders to estimate the exact labor and equipment requirements by day of the week and by hour of the day. With accurate labor-staffing models, the company was able to choose the most optimal, modular design to implement during the transition. In addition, the company could define precise, engineered standards for each operation of the warehouse, and it could monitor daily labor and equipment performance once the new system was in place. This enabled the company to reduce annual operating expenses by 18 percent.

Similarly, one business had a central regional warehouse in Eastern Europe, with annual costs of several million dollars. By constructing a digital twin, the company analyzed the potential improvements from a proposed layout change (specifically, a picking zone that enabled one-step picking). Looking at both high-season and low-season volume, the company determined that it could reduce input costs by more than 25 percent.

Supply chain risk management is back

Foundational capabilities.

As with most technology, digital warehouse design is not a turnkey solution. To capture its full potential, companies must understand their strategy not only for today and tomorrow, but also well into the future—in terms of product portfolio, customer-order profiles, and other factors. Leadership teams must assess the implications of design changes on the supply-chain network as well. And success requires new capabilities in warehouse design—typically engineers who understand the range of variations and permutations for a space. Most organizations do not yet have internal people ready for these roles, and thus need to source that expertise externally.

As a practical matter, the simulation process must involve operations and warehouse managers—those with the deep day-to-day knowledge and real-world insights that can only come from direct experience. Because these experts will be tasked with implementing any changes to the warehouse after the simulation ends, their buy-in will be essential. The more they contribute during the early stages of the process, the more willing they are likely to be to forego old habits and work in new ways.

Last, companies need to plan for repeated changes over time. Optimizing warehouse performance is a process without a finish line—it must happen again and again, as market forces, technology, and consumer preferences continue to evolve. In fact, digital warehouse-simulation tools could become a new way of setting performance expectations, with the tools embedded as part of the day-to-day management of each distribution center. Estimating daily performance targets based on daily volume, mix, and staffing can help warehouse managers manage the shift’s performance more precisely than any other traditional, static approach to setting goals.

Companies face a growing need to improve their warehouse operations. Digital warehouse design is one clear means to help them do so. The process may be virtual, but the results generate a real impact on performance, providing an edge in an ever-more-complex warehousing landscape.

Stay current on your favorite topics

Felipe Bustamante is a consultant in McKinsey’s Miami office, Ashutosh Dekhne is a partner in the Dallas office, Jörn Herrmann is a senior expert in the Zürich office, and Vedang Singh is a consultant in the New Jersey office.

The authors wish to thank Aditi Brodie for her contribution to this article.

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Merchandise Warehouses takes its operations to the next level with high-density, deep lane racking and a pallet shuttle system

Merchandise Warehouse, a logistics provider of multi-temperature warehouse services, hasn’t stopped growing since its beginning as a 50,000-square-foot dry warehouse. An industry-wide shortage of cold storage facilities led the company to invest in cooler and freezer rooms in 1959, and now today the third-generation, family-owned warehouse has increased its facility size by eight times, with more than 400,000-square-feet of cooler and freezer space.

Consumer Demand Fuels Continued Cold Storage Growth

Yet while the company continued to excel, for years they relied on common warehouse operations. Traditional pallet racking was working, and as the old saying goes, “if it isn’t broke, don’t fix it.” However, continued growth was already pushing Merchandise Warehouse to its limit. The facility was busting at its seams with product, and the company’s customers were demanding even more room.

That growth, along with Merchandise Warehouse’s more aggressive pursuit of the latest technologies, presented the perfect opportunity to act on the company’s motto: “Take it to the next level.”

The Warehouse As A Competitive Advantage

“We’re always trying to be bigger, faster and stronger, and are looking for the latest and greatest tools that will help us achieve that,” says Seth Hamman, warehouse manager at Merchandise Warehouse. “When we were facing even more rapid growth, we saw it as an opportunity to find and implement those latest solutions that were revolutionary in the industry.” 

Next Level, Efficient Solutions

Merchandise Warehouse knew what it needed: practical and affordable solutions that would help them be more efficient for their customers. The company started their search with who they knew and trusted: Raymond and Associated, an authorized Raymond Sales and Service Center. 

“Associated and Raymond have always been leaders in the industry, so we knew we could trust them with this project,” explains Scott Whiting, vice president and general manager at Merchandising Warehouse. “ Plus, we have a lot of loyal Raymond fans in our warehouse, so we already had a great foundation for getting our team on board with new technologies.” 

Merchandise Warehouse worked with Associated to assess the current operations and technologies and determine the best options for upgrading. They landed on high-density, deep lane racking and a pallet shuttle system from Raymond called Radioshuttle, which are both especially suited for cold storage. 

Radioshuttle allows additional capacity and pallet positions, while also helping store and pick product faster with its pallet shuttle system. It’s efficient, yet has fewer opportunities for product damage on account of fewer touches required to move product. While Radioshuttle moves pallets through racking, the operator—typically using a reach truck—is free to do other work.

The Rise of High-Tech Cold Storage

Most importantly, Radioshuttle allowed for maximum storage utilization. By using the full height of the warehouse and high-density, deep lane racking, Merchandise Warehouse could better fill the facility with product. 

The reduction in product touches was furthered with the integration of three conveyor systems: one moves product from the blast freezer through a de-spacing operation on to staging for lift truck put-away in the RadioShuttle system, and two others take product from the RadioShuttle storage freezer and stage it for truck loading.

Efficient Solutions with Immediate Results

The collaboration between Merchandise Warehouse, Associated and Raymond didn’t just work—it thrived.

“The companies worked together through the entire process, and in doing so, we were able to optimize our entire warehouse,” says Whiting. “We started seeing results faster than we even expected. We were seeing results in the first two months after implementing Radioshuttle and the racking.” 

Merchandise Warehouse added more than 14,000 more pallet positions with the new solutions, and in doing so, was able to keep staffing levels the same. “Overall, the warehouse was more efficient—44 percent more efficient,” says Whiting. “What used to take seven man-hours to move product through the warehouse now takes about four. And what used to take 12 touches from receiving to shipping now only takes six. Fewer required touches means less opportunity for product damage.” 

The Warehouse Manager’s Handbook

Outside of the storage, Merchandise Warehouse was also able to update its spacer removal process, cutting the time in half. Removing spacers from pallets used to take four hours, but now only takes two. 

“Four or five years ago, I was dreaming of this kind of process improvement and upgrade. I was scribbling this stuff on napkins,” says Hamman. “It’s remarkable to see it come to life with the help of Radioshuttle and the new racking. We couldn’t have asked for a better experience or results.” 

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Real-Time Data Warehouse Examples (Real World Applications)

Discover how businesses are leveraging real-time data warehouses to gain actionable insights, make informed decisions, and drive growth..

Gone are the days when organizations had to rely on stale, outdated data for their strategic planning and operational processes. Now,  real-time data warehouses process and analyze data as it is generated, helping overcome the limitations of their traditional counterparts. The impact of real-time data warehousing is far-reaching. From eCommerce businesses to healthcare providers, real-time data warehouse examples and applications span various sectors.

The significance of real-time data warehousing becomes even more evident when we consider the sheer volume of data being generated today. The global data sphere is projected to reach a staggering  180 zettabytes by 2025 . 

With these numbers, it’s no wonder every company is looking for solutions like real-time data warehousing for managing their data efficiently. However, getting the concept of a real-time data warehouse, particularly when compared with a traditional data warehouse, can be quite intimidating, even for the best of us. 

In this guide, with the help of a range of examples and real-life applications, we will explore how real-time data warehousing can help organizations across different sectors overcome the data overload challenge.

What Is A Real-Time Data Warehouse?

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A  Real-Time Data Warehouse (RTDW) is a  modern tool for data processing that provides immediate access to the most recent data. RTDWs use real-time  data pipelines to transport and collate data from multiple data sources to one central hub, eliminating the need for batch processing or outdated information.

Despite similarities with traditional data warehouses, RTDWs are capable of  faster data ingestion and processing speeds . They can detect and rectify errors instantly before storing the data, providing consistent data for an effective decision-making process.

• Real-Time Data Warehouse Vs Traditional Data Warehouse

Traditional data warehouses act as storage centers for  accumulating an organization’s historical data from diverse sources. They combine this varied data into a unified view and provide comprehensive insights into the past activities of the organization. However, these  insights are often outdated by the time they are put to use , as the data could be days, weeks, or even months old.

On the other hand, real-time data warehousing brings a significant enhancement to this model by  continuously updating the data they house. This dynamic process provides a current snapshot of the organization’s activities at any given time, enabling immediate analysis and action. 

Let’s look at some of the major differences between the two.

Complexity & Cost

RTDWs are  more complex and costly to implement and maintain than traditional data warehouses. This is because they require more advanced technology and infrastructure to handle real-time data processing.

Decision-Making Relevance

Traditional data warehouses predominantly assist in long-term strategic planning. However, the real-time data updates in RTDWs make them  suitable for both immediate, tactical decisions and long-term strategic planning.

Correlation To Business Results

Because of fresher data availability, RTDWs make it easier to  connect data-driven insights with real business results and provide immediate feedback.

Operational Requirements

RTDWs demand constant data updates, a process that can be carried out without causing downtime in the data warehouse operations . Typically, traditional warehouses don't need this feature but it becomes crucial when dealing with data updates happening every week.

Data Update Frequency

While the lines between traditional data warehouses and real-time data warehouses are now blurred due to some data warehouses adopting streaming methods to load data, traditionally, the former updated their data in batches on a daily, weekly, or monthly schedule. As a result, the data some of these data warehouses hold may not reflect the most recent state of the business. In contrast, real-time data warehouses  update their data almost immediately as new data arrives.

• 3 Major Types Of Data Warehouses

Let's take a closer look at different types of data warehouses and explore how they integrate real-time capabilities.

Enterprise Data Warehouse (EDW)

An Enterprise Data Warehouse (EDW) is a  centralized repository that stores and manages large volumes of structured and sometimes unstructured data  from various sources within an organization. It serves as a comprehensive and unified data source for business intelligence, analytics, and reporting purposes. The EDW consolidates data from multiple operational systems and transforms it into a consistent and standardized format.

The EDW is designed to  handle and scale with large volumes of data . As the organization's data grows over time, the EDW can accommodate the increasing storage requirements and processing capabilities. It also acts as a  hub for integrating data from diverse sources across the organization . It gathers information from operational systems, data warehouses, external sources, cloud-based platforms, and more.

Operational Data Store (ODS)

An Operational Data Store (ODS) is designed to  support operational processes and provide real-time or near-real-time access to current and frequently changing data. The primary purpose of an ODS is to facilitate operational reporting, data integration, and data consistency across different systems. 

ODS collects data from various sources, like transactional databases and external feeds, and  consolidates it in a more user-friendly and business-oriented format.  It typically stores detailed and granular data that reflects the most current state of the operational environment. 

A  Data Mart is a specialized version of a data warehouse that is  designed to meet the specific analytical and reporting needs of a particular business unit , like sales, marketing, finance, or human resources.

Data Marts provide a more targeted and simplified view of data. It contains a  subset of data that is relevant to the specific business area , organized in a way that facilitates easy access and analysis.

Data Marts are  created by extracting, transforming, and loading (ETL) data from the data warehouse or other data sources and structuring it to support analytical needs. They can include pre-calculated metrics, aggregated data, and specific dimensions or attributes that are relevant to the subject area.

11 Applications Of Real-Time Data Warehouses Across Different Sectors 

The use of RTDWs is now common across many sectors. The rapid access to information they provide significantly improves the operations of many businesses, from online retail to healthcare.

Let’s take a look at some major sectors that benefit from these warehouses for getting up-to-the-minute data.

In the dynamic eCommerce industry, RTDWs facilitate immediate data processing that is used to get insights into customer behavior, purchase patterns, and website interactions. This enables marketers to  deliver personalized content, targeted product recommendations, and swift customer service . Additionally, real-time inventory updates help maintain optimal stock levels, minimizing overstock or stock-out scenarios.

RTDWs empower AI/ML algorithms with new, up-to-date data. This ensures models make predictions and decisions based on the most current state of affairs. For instance, in automated trading systems, real-time data is critical for  making split-second buying and selling decisions.

Manufacturing & Supply Chain

RTDWs support advanced manufacturing processes such as  real-time inventory management, quality control, and predictive maintenance . It provides crucial support for business intelligence operations. You can make swift adjustments in production schedules based on instantaneous demand and supply data to  optimize resource allocation and reduce downtime.

RTDWs in healthcare help improve care coordination. It provides  instant access to patient records, laboratory results, and treatment plans, improving care coordination . They also support real-time monitoring of patient vitals and provide immediate responses to critical changes in patient conditions.

Banking & Finance 

In banking and finance, RTDWs give you the  latest updates on customer transactions, market fluctuations, and risk factors . This real-time financial data analysis helps with immediate fraud detection, instantaneous credit decisions, and real-time risk management.

• Financial Auditing

RTDWs enable continuous auditing and monitoring to give auditors  real-time visibility into financial transactions . It helps identify discrepancies and anomalies immediately to enhance the accuracy of audits and financial reports.

• Emergency Services

RTDWs can keep track of critical data like the  location of incidents, available resources, and emergency personnel status . This ensures an efficient deployment of resources and faster response times, potentially saving lives in critical situations.

• Telecommunications

RTDWs play a vital role in enabling efficient network management and enhancing overall customer satisfaction. They provide  immediate analysis of network performance, customer usage patterns, and potential system issues . This improves service quality, optimizes resource utilization, and proactive problem resolution.

• Online Gaming

RTDWs provide  analytics on player behaviors, game performance, and in-game purchases  to support online gaming platforms. This enables game developers to promptly adjust game dynamics, improve player engagement, and optimize revenue generation.

• Energy Management

In the energy sector, RTDWs provide  instantaneous data on energy consumption, grid performance, and outage situations. This enables efficient energy distribution, quick response to power outages, and optimized load balancing.

• Cybersecurity

RTDWs are crucial for cybersecurity as they provide  real-time monitoring of network activities and immediate detection of security threats. This supports swift countermeasures, minimizes damage, and enhances the overall security posture.

Real-Time Data Warehouse: 3 Real-Life Examples For Enhanced Business Analytics

To truly highlight the importance of real-time data warehouses, let’s discuss some real-life case studies.

• Case Study 1: Beyerdynamic 

Beyerdynamic , an audio product manufacturer from Germany, was facing difficulties with its previous method of analyzing sales data . In this process, they extracted data from their legacy systems into a spreadsheet and then compiled reports, all manually. It was time-consuming and often caused inaccurate reports.  

To overcome these challenges, Beyerdynamic developed a  data warehouse that automatically extracted transactions from its existing ERP and financial accounting systems. This data warehouse was carefully designed to store standard information for each transaction, like product codes, country codes, customers, and regions. 

They also implemented a web-based reporting solution that helped managers create their standard and ad-hoc reports based on the data held in the warehouse.

Supported by an optimized data model, the new system allowed the company to perform detailed sales data analyses and identify trends in different products or markets.

• Production plans could be adjusted quickly based on changing demand , ensuring the company neither produced excessive inventory nor missed out on opportunities to capitalize on increased demand.
• With the new system, the company could use  real-time data for performance measurement and appraisal . Managers compared actual sales with targets by region, assessed the success of promotions, and quickly responded to any adverse variances.
• Sales and distribution strategies could be quickly adapted according to changing demands in the market. For instance, when gaming headphone sales started increasing in Japan, the company promptly responded with tailored promotions and advertising campaigns.
• Case Study 2: Continental Airlines 

Continental Airlines is a major player in the aviation world. It  faced significant issues because of old, manual systems. Their outdated approach slowed down decision-making and blocked easy access to useful data from departments like customer service, flight operations, and financials. Also, the lack of real-time data meant that decisions were often based on outdated information.

They devised a robust plan that hinged on 2 key changes: the  ‘Go Forward’ strategy and a  ‘real-time data warehouse’

• Go Forward Strategy:  This initiative focused on tailoring the airline’s services according to the customer’s preferences. The concept was simple but powerful –  understand what the customer wants and adapt services to fit that mold . In an industry where customer loyalty can swing on a single flight experience, this strategy aims to ensure satisfaction and foster brand loyalty.
• Real-Time Data Warehouse:  In tandem with the new strategy, Continental also implemented an RTDW. This technological upgrade gave the airline quick access to current and historical data. The ability to extract insights from this data served as a vital reference point for strategic decision-making, optimizing operations, and enhancing customer experiences.

The new strategy and technology led to critical improvements:

• The airline could offer a personalized touch by understanding and acting on customer preferences. This  raised customer satisfaction and made the airline a preferred choice for many.
• The introduction of the RTDW brought simplicity and efficiency to the company’s operations. It facilitated quicker access to valuable data which was instrumental in  reducing the time spent on managing various systems. This, in turn, resulted in significant cost savings and increased profitability.
• Case Study 3: D Steel 

D Steel, a prominent steel production company, was facing a unique set of challenges when they aimed to  set up a real-time data warehouse to analyze their operations. While they tried to use their existing streams package for synchronization operations, several obstacles emerged.

The system was near real-time but it  couldn't achieve complete real-time functionality.  The load on the source server was significantly high and synchronization tasks required manual intervention.

More so, it lacked automation for  Data Definition Language (DDL) , compatibility with newer technologies, and had  difficulties with data consistency verification, recovery, and maintenance . These challenges pushed the steel company to seek a new solution.

The Solution

D Steel decided to implement real-time data warehouse solutions that enabled instant data access and analysis. 

The new RTDWs system proved to be extremely successful as it resolved all previous problems. It provided:

• Real-time synchronization
• Implementing DDL automation
• Automated synchronization tasks
• Reduced the load on the source server

The system also introduced a unique function that  compared current year data with that of the previous year  and helped the company in annual comparison analysis.

• Enhancing Real-Time Data Warehousing: The Role of Estuary Flow

Estuary’s Flow is our  data operations platform   that binds various systems by a central  data pipeline . With Flow, you get diverse systems for storage and analysis, like databases and data warehouses. Flow is pivotal in  maintaining synchronization amongst these systems, ensuring that new data feeds into them continuously.

Flow utilizes  real-time data lakes as an integral part of its data pipeline. This serves dual roles. 

First, it works as a transit route for data and facilitates an easy flow and swift redirection to distinct storage endpoints. This feature also helps in backfilling data from these storage points.

The  secondary role of the data lake in Flow is to serve as a reliable storage backbone . You can lean on this backbone without the fear of turning into a chaotic ‘data swamp.’ 

Flow assures automatic organization and management of the  data lake . As data collections move through the pipeline, Flow applies different schemas to them as per the need.

Remember that the data lake in Flow doesn’t replace your ultimate storage solution. Instead, it aims to  synchronize and enhance other storage systems crucial for powering key workflows , whether they're analytical or transactional.

As we have seen with real-time data warehouse examples, this solution transcends industry boundaries. Only those organizations that embrace real-time data warehousing to its fullest can unlock the true potential of their data assets. 

While it can be a little tough to implement, the benefits of real-time data warehousing far outweigh the initial complexities, and the long-term advantages it offers are indispensable in today's data-driven world.

If you’re considering setting up a real-time data warehouse, investing in a top-notch real-time data ingestion pipeline like  Estuary Flow should be your first step. Designed specifically for building real-time data management, Flow provides a no-code solution to synchronize your many data sources and integrate fresh data seamlessly.  Signup for Estuary Flow for free and seize the opportunity today.

Start streaming your data for free

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• Banking & Finance 

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Practical Data Warehousing: Successful Cases

Table of contents:

No matter how smooth the plan may be in theory, practice will certainly make adjustments. Because each real case has its own characteristics, which in the general case cannot be taken into account. Let's see how the world's leading brands have adapted to their needs a well-known way of storing information — data warehousing. If you think this is your case, then arrange a call .

The Reason for Making Decisions

The need to make business decisions based on data analysis has long been beyond doubt. But to get this data, it needs to be collected, sorted and prepared for analytics .

Operating Supplement

supplier integrations

cost reduction

David Schwarz

DATAFOREST has the best data engineering expertise we have seen on the market in recent years.

This is what data warehousing specialists do. To focus on the best performance, it makes sense to consider how high-quality custom assemblies came out of this constructor.

Data warehousing interacts with a huge amount of data

A data warehousing is a digital storage system that integrates and reconciles large amounts of data from different sources. It helps companies turn data into valuable information and make informed decisions based on it. Data warehousing combines current and historical data and acts as a single source of reliable information for business.

After raw data mining (extract, transform, load) info enters the warehouse from operating systems, such as an enterprise data resource planning system or a customer relationship management system. Sources also include databases, partner operational systems, IoT devices, weather apps, and social media. Infrastructure can be on-premises or cloud-based, with the latter option predominating in recent times.

Data warehousing is necessary not only for storing information, but also for processing structured and unstructured data: video, photos, sensor indicators. Some data warehousing options use built-in analytics and in-memory database data technology (info is stored in RAM rather than on a hard drive). This is necessary to access reliable data in real time.

After data is sorted, it is sent to data marts for further analysis by BI or data science .

Why consider data warehousing cases

Consideration of known options for data warehousing is necessary, first of all, in order not to keep making the same mistakes. Based on a working solution, you can improve your own performance. If you want to always be on the cutting edge of technology, book a call .

• When using data warehouses, executives access data from different sources, they do not have to decide blindly.
• Data warehousing is needed for quick retrieval and analysis. When using warehouses, you can quickly request large amounts of data without involving personnel for this.
• Before uploading to the warehouse, the system creates data cleansing tasks and puts them for further processing, ensuring converting the data into a consistent format for subsequent analyst reports.
• The warehouse contains large amounts of historical data and allows you to study past trends and issues to predict events and improve the business structure.

Blindly repeating other people's decisions is also impossible. Your case is unique and probably requires a custom approach. At best, well-known storage solutions can be taken as a basis. You can do it yourself, or you can contact DATAFOREST specialists for professional services. We have a positive experience and positive customer stories of data warehousing creating and operating.

Case 1: How the Amazon Service Does Data Warehousing

Amazon is one of the world's largest and most successful companies with a diversified business: cloud computing, digital content, and more. As a company that generates vast amounts of data (including data warehousing services), Amazon needs to manage and analyze its data effectively.

Two main businesses

Amazon's data warehousing needs are driven by the company's vast and diverse data sources, which require sophisticated tools and technologies to manage and analyze effectively.

1. One of the main drivers of Amazon's business is its e-commerce platform , which allows customers to purchase a wide range of products through its website and mobile apps. Amazon's data warehousing needs in this area are focused on collecting, storing, and analyzing data related to customer behavior, purchase history, and other metrics. This data is used to optimize Amazon's product recommendations engine, personalize the shopping experience for individual customers, and identify growth strategies.

2. Amazon's other primary business unit is Amazon Web Services (AWS), which offers cloud computing managed services to businesses and individuals. AWS generates significant amounts of data from its cloud data infrastructure, including customer usage and performance data. To manage and analyze this modern data effectively, Amazon relies on data warehousing technologies like Amazon Redshift, which enables AWS to provide real-time analytics and insights to its customers.

3. Beyond these core businesses, Amazon also has significant data warehousing needs in digital content (e.g., video, music, and books). Amazon's advertising business relies on data analysis to identify key demographics and target ads more effectively to specific audiences.

By investing in data warehousing and analytics capabilities, Amazon through digital transformation can maintain its competitive edge and continue to grow and innovate in the years to come.

Do you want to streamline your data integration?

Obstacles on the way to the goal.

Amazon faced several specific implementation details and challenges in its data warehousing efforts.

• The brand needed to integrate data from various sources into a centralized data warehouse. It required the development of custom data pipelines to collect and transform data into a standard format.

• Amazon's data warehousing needs are vast and constantly growing, requiring a scalable solution. The company distributed data warehouse architecture center using technologies like Amazon Redshift, allowing petabyte-scale data storage and analysis.

• As a company that generates big data, Amazon would like to ensure that its data warehousing solution could provide real-time data analytics and insights. Achieving high performance requires optimizing data storage, indexing, and querying processes.

• Amazon stores sensitive customer data in its warehouse, prioritizing data security. To protect against security threats, the brand implements various security measures, including encryption, access controls, and threat detection.

• Building and maintaining a data warehousing solution can be expensive. Amazon leverages cloud-based data warehousing solutions (Redshift) to minimize costs, which provide a cost-effective, pay-as-you-go pricing model.

Amazon's data warehousing implementation required careful planning, significant investment in technology and infrastructure, and ongoing optimization and maintenance to ensure high performance and reliability.

Change for the better

When Amazon considered all the needs, found the right tools, and implemented a successful data warehouse, the company got the following main business outcomes:

• Improved data driven decision

• Better customer enablement

• Cost effective decision

• Improved performance

• Competitive advantage

• Scalability

Amazon's data warehousing implementation has driven the company's growth and success. Not surprisingly, a data storage service provider must understand data storage. The cobbler's children don't need to have no shoes.

Case 2: Data Warehousing Adventure with UPS

United Parcel Services (UPS) is an American parcel delivery and supply chain management company founded in 1907 with an annual revenue of 71 billion dollars and logistics services in more than 175 countries. In addition, the brand distributes goods, customs brokerage, postal and consulting services. UPS processes approximately 300 million tracking requests daily. This effect was achieved, among others, thanks to intelligent data warehousing.

One mile for $50 million

In 2013, UPS stated that it hosted the world's largest DB2 relational database in two United States data centers for global operations. Over time, global operations began to increase, as did the amount of semi structured data. The goal was to use different forms of storage data to make better users business decisions.

One of the fundamental problems was route optimization. According to an interview with the UPS CTO, saving 1 mile a day per driver could save 1.5 million gallons of fuel per year or $50 million in total savings.

However, the data was distributed in DB2; some included repositories, some local, and some spreadsheets. UPS needed to solve the data infrastructure problem first and then optimize the route.

Four letters "V."

The big data ecosystem efficiently handles the four "Vs": volume, validity, velocity, and variety. UPS has experimented with Hadoop clusters and integrated its storage details and computing system into this ecosystem. They upgraded data warehousing and computing power to handle petabytes of data, one of UPS's most significant technological achievements.

The following Hadoop components were used:

• HDFS for storage

• Map Reduce for fast processing

• Kafka streaming

• Sqoop (SQL-to-Hadoop) for ingestion

• Hive & Pig for structured queries on unstructured data

• monitoring system for data nodes and names

But that's just speculation because, due to confidentiality, UPS didn't declassify the tools and technologies they used in their big data ecosystem.

Constellation of Orion

The result was a four-year ORION (On-Road Integrated Optimization and Navigation) route optimization project. Costs — about one billion dollars a year. ORION used the results to data stores and calculate big data and got analytics from more than 300 million data points to optimize thousands of routes per minute based on real-time information. In addition to the economic benefits, the Orion project shortened approximately 100 million shipping miles and a 100,000-ton reduction in carbon emissions.

Case 3: 42 ERP Into One Data Warehouse

In general, the topic of specific cases of data warehousing implementation is sufficiently secret. There may be cases of consent and legitimate interests in the contracts. There are open-source examples of work, but the vast majority are on paid libraries. The subject is so relevant that you can earn money from it. Therefore, sometimes there are "open" cases, but the brand name is not disclosed.

Brand X needs help

World leader in industrial pumps, valves, actuators, controls, etc., needed help extracting data from disparate ERP systems. They wanted it from 42 ERP instances, standardized flat files, and collected all the information in one data warehouse. The ERP systems were from different vendors (Oracle, SAP, BAAN, Microsoft, PRMS) to complicate future matters.

The client also wanted a core set of metrics and a central dashboard to combine all the information from different locations worldwide. The project resulted from a surge in demand for corporate data from database management. The company knew its data warehousing needed a central repository for all data from its locations worldwide. Requests often came from top to bottom, and when an administrator required access to the correct data, there were logistical extracting problems. And the project gets started.

Are you interested in enhanced insights through data aggregation?

The foundation stone.

The hired third-party developer center has made a roadmap, according to which ERP data was taken from 8 major databases and placed in a corporate data warehouse. It entailed integrating 5 Oracle ERP instances with 3 SAP ERP. Rapid Marts have also been integrated into Oracle ERP systems to improve the project's progress.

One of the main challenges was the need for more standardization of fields or operational data definitions in ERP systems. To solve this problem, the contractor has developed a data service tool that allows access to the back end of the database and displays info suitably. Since then, the customer has known which fields to use and how to set them each time a new ERP instance is encountered. These data definition patterns were the project's foundation stone and completely changed how customer data is handled. It was a point to launch consent.

All roads lead to data warehousing

The company has one common and consistent way to obtain critical indicators. The long-term effect of the project is the ease of obtaining information. What was once a long and inconsistent process of getting relevant information at an aggregate level is now streamlined to store data in one central repository with one team controlling it.

Data Warehousing: Different Cases — General Conclusions

Each data warehouse organization has unique methods and tools because business needs differ. In this case, data warehousing can be compared with a mosaic and a children's constructor. You can make different figures from the same parts, arranging the elements especially. And if one part is lost or broken, you need to make a new one or find another one and "process it with a rasp."

Generalities between different cases of data warehousing

There are several common themes and practices among successful data warehousing implementations, including:

• Successful data warehousing implementations start with clearly understanding the business objectives and how the warehouse (or data lake) can support those objectives.

• The data modeling process is critical to the success of data warehousing.

• The data warehouse is only as good as the data it contains.

• Successful data warehousing requires efficient data integration processes that can operate large volumes of data and ensure consistency and accuracy.

• Data warehousing needs ongoing performance tuning to optimize query performance.

• A critical factor in data warehousing is a user-friendly interface that makes it easy for end users to access the data and perform complex queries and analyses.

• Continuous improvement is essential to ensure the data warehouse remains relevant and valuable to the business.

Competent data warehousing implementations combine technical expertise and a deep understanding of business details and user needs.

Your case is not mentioned anywhere

When solving the problem of organizing data warehousing , one would like to find a description of the same case and do everything according to plan. But the probability of this event is negligible — you will have to adapt to the specifics of the customer's business and consider your knowledge and capabilities, as well as the technical and financial conditions of the project. Then it would help if you took a piece of the puzzle or parts of the constructor and built your data warehouse. Minus — you have to work. Plus — it will be your decision on data storage and only your implementation.

Data Warehousing Is Like a Trampoline

Changes in data warehousing , like any technological and methodological changes, are carried out to improve the data collection, storage, and analysis level. It takes the customer to a new level in his activity and the contractor — to his own. Like a jumper and a trampoline: separately, it is just a gymnast and just equipment, and in combination, they give a certain third quality — the possibility of a sharp rise.

If you are faced with the problem of organizing a new data warehousing system, or you are simply interested in what you read, let's exchange views with DATAFOREST.

What is the benefit of data warehousing for business?

A data warehouse is a centralized repository that contains integrated data from various sources and systems. Data warehousing provides several benefits for businesses: improved decision-making, increased efficiency, better customer insights, operational efficiency, and competitive advantage.

What is the definition of a successful data warehousing implementation?

The specific definition of a successful data warehouse implementation will vary depending on the goals of the organization and the particular use case for data warehousing. Some common characteristics are: meeting business requirements, high data quality, scalability, user adoption, and positive ROI.

What are the general considerations for implementing data warehousing?

Implementing data warehousing involves some general considerations: business objectives, data sources, quality and modeling, technology selection, performance tuning, user adoption, ongoing maintenance, and support.

What are the most famous examples of the implementation of data warehousing?

There are many famous examples of the implementation of data warehousing across industries:

• Walmart has one of the largest data warehousing implementations in the world

• Amazon's data warehousing solution is known as Amazon Redshift

• Netflix uses a data warehouse to store and analyze data from its streaming platform

• Coca-Cola has a warehouse to consolidate data from business units and analyze it

• Bank of America analyzes customer data by data warehousing to improve customer experience

What are the challenges while implementing data warehousing, and how to overcome them?

Based on the experiences of organizations that have implemented data warehousing, some common challenges and solutions are:

• Ensuring the quality of the data that is being stored and analyzed. You must establish data quality standards and implement data validation and cleansing by data types.

• Integrating from disparate data sources. Establishing a clear data integration strategy that considers the different data sources, formats, and protocols involved is vital.

• As the amount of data stored in a data warehouse grows, performance issues may arise. A brand should regularly monitor query performance and optimize the data warehouse to ensure that it remains efficient and effective.

• To ensure that sensitive data stored in the data warehouse is secure. It involves implementing appropriate measures such as access controls, encryption, and regular security audits. They are details of privacy security.

• Significant changes to existing processes and workflows. Solved by establishing a transparent change management process that involves decision-makers and users at all levels.

What is an example of how successful data warehousing has affected a business?

An example of how successful data warehousing has affected Amazon is its recommendation engine. It suggests products to customers based on their browsing and purchasing history. By using artificial intelligence and machine learning algorithms to analyze customer data, Amazon has improved the fully managed accuracy of its recommendations, resulting in increased sales and customer satisfaction.

What role does data integration play in data warehousing?

Data integration is critical to data warehousing, enabling businesses to consolidate and standardize data from multiple sources, ensure data quality, and establish effective data governance practices.

How are data quality and governance tracked in data warehousing?

Data quality and governance are tracked in data warehousing through a combination of data profiling, monitoring, and management processes and establishing data governance frameworks that define policies and procedures for managing data quality and governance. So, businesses can ensure that their data is accurate, consistent, and compliant with regulations, enabling effective decision-making and driving business applications' success.

Are there any measures to the benefits of data warehousing?

The benefits of business data warehousing can be measured through improvements in data quality, efficiency, decision-making, revenue and profitability, and customer satisfaction. By tracking these metrics, businesses can assess the effectiveness of their data warehousing initiatives and make informed decisions about future investments in data management and analytics with cloud services.

How to avoid blunders when warehousing data?

By following the best practices, businesses can avoid common mistakes, minimize the risk of blunders when warehousing data, and ensure their data warehousing initiatives are successful and practical to be analyzed with business intelligence.

Aleksandr Sheremeta

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Factory logistics improvement: a case study analysis of companies in northern thailand, 2022–2024.

1. Introduction

2. background, 2.1. industries in thailand, 2.2. logistics in thailand, 2.3. industries in northern thailand, 3. methodology, 4. results and case study, 4.1. transportation management, 4.1.1. vehicle routing solution, 4.1.2. transportation management system (tms), 4.2. warehouse and inventory management, 4.2.1. inventory model application.

• Analysis of order history.
• Implementation of Pareto/ABC classification to categorize materials based on their value, volume, and frequency of use [ 37 ].
• Application of inventory models, specifically the Economic Order Quantity (EOQ) model, incorporating Reorder Point (ROP) and Safety Stock (SS) calculations [ 38 ].

4.2.2. Warehouse Layout Design

• Redesign of warehouse layout based on product category and significance using Pareto/ABC classification.
• Determination of stock levels for A-level raw materials using Safety Stock (SS) calculations.
• Introduction of visual control concepts to enhance warehouse operations (as illustrated in Figure 4 ).

4.2.3. Warehouse Management System (WMS)

4.2.4. automation in material handing, 4.3. logistics administrative management, 4.3.1. forecasting and demand planning, 4.3.2. logistics communication, 4.3.3. outsourcing, 5. discussion and conclusions.

• Developing more adaptive and scalable logistics improvement methodologies that can accommodate businesses of varying sizes and technological readiness levels.
• Investigating the long-term sustainability of logistics improvements, particularly in the face of changing market conditions and technological advancements.
• Exploring the potential of emerging technologies, such as artificial intelligence and blockchain, in facilitating more seamless integration across logistics functions.
• Examining the role of organizational culture and change management in the successful implementation of logistics improvements.
• For policymakers, the results underscore the importance of continued support for logistics improvement initiatives, particularly in developing economies. The triple-helix model demonstrated here could serve as a blueprint for similar programs in other regions or countries.
• Industry practitioners can benefit from the practical insights and methodologies presented, adapting them to their specific contexts to achieve logistics optimization.
• Academic researchers can build upon this work to further explore the interconnections between various logistics functions and develop more integrated theoretical models of logistics performance.
• Technology providers may find opportunities to develop more tailored solutions that address the specific challenges faced by businesses in implementing logistics improvements.

Author Contributions

Data availability statement, acknowledgments, conflicts of interest.

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Share and Cite

Ramingwong, S.; Sopadang, A.; Tippayawong, K.Y.; Jintana, J. Factory Logistics Improvement: A Case Study Analysis of Companies in Northern Thailand, 2022–2024. Logistics 2024 , 8 , 88. https://doi.org/10.3390/logistics8030088

Ramingwong S, Sopadang A, Tippayawong KY, Jintana J. Factory Logistics Improvement: A Case Study Analysis of Companies in Northern Thailand, 2022–2024. Logistics . 2024; 8(3):88. https://doi.org/10.3390/logistics8030088

Ramingwong, Sakgasem, Apichat Sopadang, Korrakot Yaibuathet Tippayawong, and Jutamat Jintana. 2024. "Factory Logistics Improvement: A Case Study Analysis of Companies in Northern Thailand, 2022–2024" Logistics 8, no. 3: 88. https://doi.org/10.3390/logistics8030088

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