Commentary: Challenging the warehouse management system implementation paradigm
Warehouse management systems have come a long way from the 1980s and 1990s. So why are so many companies still asking for customizations? Here's the case for no modifications in WMS implementations.
The warehouse management system (WMS) market in the United States is fairly mature, with many companies on their second, third, or fourth system. The software has come a long way from the custom-written systems developed in the 1980s and '90s that often took well over a year to get up and running, were prone to bugs, and caused integration nightmares. Much sleep was lost by information technology (IT) and operations staff when a go-live was imminent, worried that the cutover might cause bottlenecks in their shipments or, even worse, shut down their distribution center entirely.
It only makes sense that these complex, robust systems would evolve over time. Many of the "best of breed" providers now offer WMS software that, while still able to handle complex operations, are easier to use and often are web-based and mobile-friendly. Features that were once custom-developed to meet the need of a specific client or industry are now part of the standard software and accessible to all users as part of the base system. Even so, many companies have not recognized these changes and instead are still trying to implement WMS in the same way that they have for years.
Implementations—the old-fashioned way
Historically, the complex nature of WMS software meant that a lot of technical expertise was needed just to implement the software successfully—let alone make any customizations that might be necessary to fit a company's functional requirements. Implementations were often long, expensive, and painful. They would be measured in years rather than in months. Furthermore, the systems were not user-friendly, consisting of green screens and basic commands that were not intuitive. As a result, the software required extensive training that was often tedious and time-consuming. Finally, to meet the individual needs of a distribution operation, the software was usually heavily modified and custom-coded.
Even at that time, it was recognized that customization wasn't always a good idea. The software was typically customized to meet the existing processes, but the processes it was automating were not always the most efficient way to do things. Companies expected software to be a magic wand that would instantly make them more productive, efficient, and profitable. But in hindsight, managers often realized they should have fine-tuned their processes to align with best practices first before they customized the software. Furthermore, highly modified WMS software required even more training and led to even longer implementation timeframes.
Still, having a WMS was a far cry from handling operations with paper. Once a system was configured and working properly, it provided a great deal of information to aid in decision making, helped end users increase efficiency and productivity, and reduced costs.
New approach to implementation: no modification
WMS software and implementation processes have come a long way in the past couple of decades. Warehouse management systems now include best practice processes for most industries and functional requirements. In fact, they've gotten so good that if your process requires a modification, you really need to spend the time to dig deep and ask yourself if your way is truly better and necessary, or if you would benefit from changing your process. Software is also written differently and is more configurable, which means features can be turned on or off within the system based on a company's industry and requirements.
Still, many companies today continue to choose to write modifications to the software rather than change their processes to match the software's built-in best practices approach. Perhaps this is because of a "this is the way we've always done it" mentality or because the company hasn't taken the time to research the benefits of changing processes to match best practices. And sometimes consulting companies even encourage modifications because it means more billable work for them. However, many problems arise when you modify the code of software, including higher total cost of ownership, longer implementation timeframes, integration integrity issues, increased fees for support and maintenance, and limited ability to upgrade and adopt new features as new versions of the software are released.
While implementing a WMS with no modifications would have been out of the question 10 years ago, it is a very real option for most companies today. In fact, it should be the expectation and starting point, rather than assuming from the beginning that there must be system modifications. For example, most of our clients who are upgrading to a new WMS are now choosing to reduce their modifications by 80 to 100 percent and have seen many benefits to this no-modification approach. The upgrades on average cost only25 percent of their original implementation, and they are saving an average of 30 percent on maintenance costs.
Additionally, a no-modification WMS implementation can be up and running in three to nine months, versus one-year and longer for more modified systems. To understand why, let's look at a simple modification that might take five to 10 days of development and unit testing, plus another week or two of acceptance testing and rework. This modification would also require time and resources to update documentation, training materials, and standard operating procedures. And if that piece of functionality needs to share information with other systems, such as an enterprise resource planning (ERP), transportation management system (TMS), or labor management solution, then you need to modify the integration with those systems, potentially impacting the integrity of those systems. Additionally, any modifications can have an impact on the existing adjacent code within the WMS. All this adds up quickly to significant cost, time, and integrity issues, and this example is based on only one straight-forward modification. And the increased costs continue—most WMS vendors charge an extra 15 percent of the cost of the modification annually for maintenance costs.
Getting started
If you are interested in implementing a WMS with the goal of no modifications, start by an analyzing your current operations and processes with a partner who has distribution expertise and deep knowledge of the WMS features, functions, and capabilities. Together you will explore each functional need you have alongside the WMS standard functionality and discuss how the software and processes meet and how processes might be tweaked to match the WMS best practices. For some companies, modifying WMS software may make sense but only if the costs associated with modification are less than the long-term cost savings for such modification.
Based on our experience, we believe that for the vast majority of companies, the no-modification approach advocated here is most beneficial. It is easier to install, can be up and running faster, costs less, and provides a smoother upgrade path so you can more easily take advantage of new features as they are released. No modifications also mean that you are raising the standard of your operational processes to be in line with best practices; the ones that the software is based on at the start. This alone will provide efficiencies for your operations that may not have been previously realized.
The launch is based on “Amazon Nova,” the company’s new generation of foundation models, the company said in a blog post. Data scientists use foundation models (FMs) to develop machine learning (ML) platforms more quickly than starting from scratch, allowing them to create artificial intelligence applications capable of performing a wide variety of general tasks, since they were trained on a broad spectrum of generalized data, Amazon says.
The new models are integrated with Amazon Bedrock, a managed service that makes FMs from AI companies and Amazon available for use through a single API. Using Amazon Bedrock, customers can experiment with and evaluate Amazon Nova models, as well as other FMs, to determine the best model for an application.
Calling the launch “the next step in our AI journey,” the company says Amazon Nova has the ability to process text, image, and video as prompts, so customers can use Amazon Nova-powered generative AI applications to understand videos, charts, and documents, or to generate videos and other multimedia content.
“Inside Amazon, we have about 1,000 Gen AI applications in motion, and we’ve had a bird’s-eye view of what application builders are still grappling with,” Rohit Prasad, SVP of Amazon Artificial General Intelligence, said in a release. “Our new Amazon Nova models are intended to help with these challenges for internal and external builders, and provide compelling intelligence and content generation while also delivering meaningful progress on latency, cost-effectiveness, customization, information grounding, and agentic capabilities.”
The new Amazon Nova models available in Amazon Bedrock include:
Amazon Nova Micro, a text-only model that delivers the lowest latency responses at very low cost.
Amazon Nova Lite, a very low-cost multimodal model that is lightning fast for processing image, video, and text inputs.
Amazon Nova Pro, a highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks.
Amazon Nova Premier, the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models
Amazon Nova Canvas, a state-of-the-art image generation model.
Amazon Nova Reel, a state-of-the-art video generation model that can transform a single image input into a brief video with the prompt: dolly forward.
Economic activity in the logistics industry expanded in November, continuing a steady growth pattern that began earlier this year and signaling a return to seasonality after several years of fluctuating conditions, according to the latest Logistics Managers’ Index report (LMI), released today.
The November LMI registered 58.4, down slightly from October’s reading of 58.9, which was the highest level in two years. The LMI is a monthly gauge of business conditions across warehousing and logistics markets; a reading above 50 indicates growth and a reading below 50 indicates contraction.
“The overall index has been very consistent in the past three months, with readings of 58.6, 58.9, and 58.4,” LMI analyst Zac Rogers, associate professor of supply chain management at Colorado State University, wrote in the November LMI report. “This plateau is slightly higher than a similar plateau of consistency earlier in the year when May to August saw four readings between 55.3 and 56.4. Seasonally speaking, it is consistent that this later year run of readings would be the highest all year.”
Separately, Rogers said the end-of-year growth reflects the return to a healthy holiday peak, which started when inventory levels expanded in late summer and early fall as retailers began stocking up to meet consumer demand. Pandemic-driven shifts in consumer buying behavior, inflation, and economic uncertainty contributed to volatile peak season conditions over the past four years, with the LMI swinging from record-high growth in late 2020 and 2021 to slower growth in 2022 and contraction in 2023.
“The LMI contracted at this time a year ago, so basically [there was] no peak season,” Rogers said, citing inflation as a drag on demand. “To have a normal November … [really] for the first time in five years, justifies what we’ve seen all these companies doing—building up inventory in a sustainable, seasonal way.
“Based on what we’re seeing, a lot of supply chains called it right and were ready for healthy holiday season, so far.”
The LMI has remained in the mid to high 50s range since January—with the exception of April, when the index dipped to 52.9—signaling strong and consistent demand for warehousing and transportation services.
The LMI is a monthly survey of logistics managers from across the country. It tracks industry growth overall and across eight areas: inventory levels and costs; warehousing capacity, utilization, and prices; and transportation capacity, utilization, and prices. The report is released monthly by researchers from Arizona State University, Colorado State University, Rochester Institute of Technology, Rutgers University, and the University of Nevada, Reno, in conjunction with the Council of Supply Chain Management Professionals (CSCMP).
Specifically, 48% of respondents identified rising tariffs and trade barriers as their top concern, followed by supply chain disruptions at 45% and geopolitical instability at 41%. Moreover, tariffs and trade barriers ranked as the priority issue regardless of company size, as respondents at companies with less than 250 employees, 251-500, 501-1,000, 1,001-50,000 and 50,000+ employees all cited it as the most significant issue they are currently facing.
“Evolving tariffs and trade policies are one of a number of complex issues requiring organizations to build more resilience into their supply chains through compliance, technology and strategic planning,” Jackson Wood, Director, Industry Strategy at Descartes, said in a release. “With the potential for the incoming U.S. administration to impose new and additional tariffs on a wide variety of goods and countries of origin, U.S. importers may need to significantly re-engineer their sourcing strategies to mitigate potentially higher costs.”
Grocers and retailers are struggling to get their systems back online just before the winter holiday peak, following a software hack that hit the supply chain software provider Blue Yonder this week.
The ransomware attack is snarling inventory distribution patterns because of its impact on systems such as the employee scheduling system for coffee stalwart Starbucks, according to a published report. Scottsdale, Arizona-based Blue Yonder provides a wide range of supply chain software, including warehouse management system (WMS), transportation management system (TMS), order management and commerce, network and control tower, returns management, and others.
Blue Yonder today acknowledged the disruptions, saying they were the result of a ransomware incident affecting its managed services hosted environment. The company has established a dedicated cybersecurity incident update webpage to communicate its recovery progress, but it had not been updated for nearly two days as of Tuesday afternoon. “Since learning of the incident, the Blue Yonder team has been working diligently together with external cybersecurity firms to make progress in their recovery process. We have implemented several defensive and forensic protocols,” a Blue Yonder spokesperson said in an email.
The timing of the attack suggests that hackers may have targeted Blue Yonder in a calculated attack based on the upcoming Thanksgiving break, since many U.S. organizations downsize their security staffing on holidays and weekends, according to a statement from Dan Lattimer, VP of Semperis, a New Jersey-based computer and network security firm.
“While details on the specifics of the Blue Yonder attack are scant, it is yet another reminder how damaging supply chain disruptions become when suppliers are taken offline. Kudos to Blue Yonder for dealing with this cyberattack head on but we still don’t know how far reaching the business disruptions will be in the UK, U.S. and other countries,” Lattimer said. “Now is time for organizations to fight back against threat actors. Deciding whether or not to pay a ransom is a personal decision that each company has to make, but paying emboldens threat actors and throws more fuel onto an already burning inferno. Simply, it doesn’t pay-to-pay,” he said.
The incident closely followed an unrelated cybersecurity issue at the grocery giant Ahold Delhaize, which has been recovering from impacts to the Stop & Shop chain that it across the U.S. Northeast region. In a statement apologizing to customers for the inconvenience of the cybersecurity issue, Netherlands-based Ahold Delhaize said its top priority is the security of its customers, associates and partners, and that the company’s internal IT security staff was working with external cybersecurity experts and law enforcement to speed recovery. “Our teams are taking steps to assess and mitigate the issue. This includes taking some systems offline to help protect them. This issue and subsequent mitigating actions have affected certain Ahold Delhaize USA brands and services including a number of pharmacies and certain e-commerce operations,” the company said.
Editor's note:This article was revised on November 27 to indicate that the cybersecurity issue at Ahold Delhaize was unrelated to the Blue Yonder hack.
The new funding brings Amazon's total investment in Anthropic to $8 billion, while maintaining the e-commerce giant’s position as a minority investor, according to Anthropic. The partnership was launched in 2023, when Amazon invested its first $4 billion round in the firm.
Anthropic’s “Claude” family of AI assistant models is available on AWS’s Amazon Bedrock, which is a cloud-based managed service that lets companies build specialized generative AI applications by choosing from an array of foundation models (FMs) developed by AI providers like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself.
According to Amazon, tens of thousands of customers, from startups to enterprises and government institutions, are currently running their generative AI workloads using Anthropic’s models in the AWS cloud. Those GenAI tools are powering tasks such as customer service chatbots, coding assistants, translation applications, drug discovery, engineering design, and complex business processes.
"The response from AWS customers who are developing generative AI applications powered by Anthropic in Amazon Bedrock has been remarkable," Matt Garman, AWS CEO, said in a release. "By continuing to deploy Anthropic models in Amazon Bedrock and collaborating with Anthropic on the development of our custom Trainium chips, we’ll keep pushing the boundaries of what customers can achieve with generative AI technologies. We’ve been impressed by Anthropic’s pace of innovation and commitment to responsible development of generative AI, and look forward to deepening our collaboration."