Kimberly-Clark connects its supply chain to the store shelf
In its quest to achieve a demand-driven supply chain, Kimberly-Clark turned to software that generates shipment forecasts based on point-of-sale data. Now the consumer products giant can better serve some of its customers with a lot less inventory.
For the past six years, Kimberly-Clark Corp. has been on a mission to connect its supply chain to the store shelf. The manufacturer of personal-care products wanted to create a demand-driven supply chain that would make and warehouse only the precise amount of inventory needed to replace what consumers actually purchased.
The company had good reason to make this one of its top priorities. "If we align our activities to what's happening on the shelf, we can take a lot of cost, waste, and inventory out of the system," explains Rick Sather, Kimberly-Clark's vice president of customer supply chain for North America consumer products.
That's easier said than done, of course. The roadblock for Kimberly-Clark was that its store shipments were based on historical sales forecasts, which were not very accurate predictors of future sales. To match shipments with actual demand, the company would need to use point-of-sale (POS) data from consumer purchases as the basis for replenishments to grocers and retailers.
Toward that end, the manufacturer began using software that utilizes sales data to generate forecasts that trigger shipments to stores. To date, only three of Kimberly-Clark's largest customers are participating in the program, but the results have been notable. These demand-driven forecasts, which are more accurate than the historical sales forecasts, let the manufacturer better serve those customers but with much less inventory.
Shifting focus
Based in Irving, Texas, a suburb of Dallas, Kimberly-Clark makes such well-known personal-care products as Kleenex facial tissues, Huggies diapers, and Scott's paper towels. Its worldwide sales exceeded $20 billion in 2011.
Back in 2006, company executives decided to refocus Kimberly-Clark's supply chain strategy from supporting manufacturing to serving the specific needs of its retail and grocery customers. As a first step, the company reconfigured its North American distribution network to place its warehouses closer to those customers. Before the reconfiguration, Kimberly-Clark used 120 facilities of various types, and it shipped from 60 to 70 locations to satisfy all customer orders. The shipping location depended on the product mix of the order. As a result, different product mixes resulted in different shipping locations for the same customer, and forecasting and maintaining the proper mix of products at any given DC was difficult.
By 2008, Kimberly-Clark had reduced the number of warehouses it used to 30 multiproduct facilities strategically located near its customers. The reconfiguration involved a combination of opening new, larger facilities—some of which handle Kimberly-Clark's full product line—and repurposing some existing sites. For example, a few of the distribution centers began supporting a smaller group of customers, or they switched to shipping only promotional items. Today, 20 of the 30 warehouses and distribution centers now ship directly to customers.
Because the reconfiguration placed more warehouses and DCs closer to Kimberly-Clark's customers, the company was able to increase order frequency and reduce transit times for many of them. That paid off not just for the customers but for the manufacturer, too. "We realigned our DC network and streamlined it to bring inventory and costs out of the system and make ourselves more responsive to customer needs," says Manager of Supply Chain Analysis Michael Kalinowski. "We used to view our supply chain as ending once we delivered to the customer's door, but now we've extended that to the customer's retail location, and in some cases, right to the shelf."
Becoming one with demand
The ultimate objective of any change in supply chain strategy is to increase company profits. Kimberly-Clark viewed a demand-driven supply chain as being critical to achieving that objective. The Great Recession of 2008-2009 brought additional "energy" to that focus as Kimberly-Clark sought to reduce its inventory holdings to free up working capital, says Director of Supply Chain Strategy Scott DeGroot.
To become a truly demand-driven supply chain, managers knew, Kimberly-Clark would have to incorporate demand-signal data—information about actual consumer purchases—into its plans for resupplying retailers with products. In 2009, the company made some limited use of downstream retail data in its demand-planning software, but it continued to rely for the most part on historical shipment data as the basis for its replenishment forecasts. But forecasts based on historical sales are prone to errors, because they cannot predict spikes in consumer demand. Such errors left Kimberly-Clark with excess safety stock and unsold inventory.
To address that problem and improve forecasting, Kimberly-Clark conducted a pilot program with the software vendor Terra Technology that aimed to incorporate demand signals into its North American operation. The pilot proved successful, and in 2010 the consumer products giant purchased and implemented Terra Technology's multienterprise demand-sensing solution. Initially, Kimberly-Clark only ran the software's forecast engine, using its own internal data. Since 2011, however, it has been using actual retail-sales data to drive both replenishment and manufacturing.
Three retailers, which account for one-third of Kimberly-Clark's consumer products business in North America, currently provide point-of-sale data. That information is fed daily into the solution's engine, which then recalibrates the shipment forecast for each of those retailers. Each day, the software evaluates any new data inputs from the retailers along with open orders and the legacy demand-planning forecast to generate a new shipment forecast. That forecast, in daily buckets, covers the current week plus the next four weeks. Kimberly-Clark then uses that forecast to guide internal deployment decisions and tactical planning.
The software contains algorithms that process data provided by the retailers, such as point-of-sale information, inventory in the distribution channel, shipments from warehouses, and the retailer's own forecast. It reconciles all of that data to create a daily operational forecast. The software also identifies patterns in the historical data to determine which inputs are the most predictive in forecasting shipments from Kimberly-Clark's facilities. The inputs are re-evaluated weekly, and how much influence each input has on the forecast can change. For example, POS might be the best predictor of a shipment forecast on a three-week horizon, but actual orders could be the best predictor for the current week.
By using actual demand—that is, the point-of-sale data—to recalculate its operational forecasts, Kimberly-Clark can better ensure that it has the products consumers want to buy in stores at the right time. Although only three companies at the moment are providing POS data, Kimberly-Clark is also using the Terra solution to create forecasts for its other retail customers. For that customer group, the manufacturer relies on historical shipment data to develop its forecast.
Lower forecast error rates
The incorporation of demand signals into Kimberly-Clark's shipment forecasting has resulted in substantial improvements in several respects. For one thing, the company has been able to develop a more granular metric for forecast errors. In the past, it measured forecasts by product categories; the metric it uses now tracks stock-keeping units (SKUs) and stocking locations. This metric is defined as the absolute difference between shipments and forecast, and it's reported as a percentage of shipments.
Using that particular metric to evaluate its daily forecast, Kimberly-Clark has seen a reduction in forecast errors of as much as 35 percent for a one-week planning horizon and 20 percent for a two-week horizon. "What we've noticed is that as you go farther out in the [planning] horizon, the inputs are less predictive and the amount of forecast-error reduction tends to erode," says Jared Hanson, a demand planning specialist.
Thanks to that reduction in forecast errors, there is less need for safety stock. In fact, Hanson says, more accurate forecasts have allowed Kimberly-Clark to take out one to three days of safety stock, depending on the SKU. "From a dollars or return on investment perspective, that's the most tangible benefit," he says.
More accurate forecasts and the commensurate reductions in safety stock have helped Kimberly-Clark reduce its overall inventory. The company says it has cut finished-goods inventory by 19 percent in the last 18 months.
Equally important, say Kimberly-Clark's supply chain executives, is that this stellar inventory performance has not compromised the quality of service it provides to its customers. "As we sit today," says Rick Sather, "our ability to serve customers with this level of inventory is the best it's been in many years."
Benefits for Amazon's customers--who include marketplace retailers and logistics services customers, as well as companies who use its Amazon Web Services (AWS) platform and the e-commerce shoppers who buy goods on the website--will include generative AI (Gen AI) solutions that offer real-world value, the company said.
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.”
Freight transportation providers and maritime port operators are bracing for rough business impacts if the incoming Trump Administration follows through on its pledge to impose a 25% tariff on Mexico and Canada and an additional 10% tariff on China, analysts say.
Industry contacts say they fear that such heavy fees could prompt importers to “pull forward” a massive surge of goods before the new administration is seated on January 20, and then quickly cut back again once the hefty new fees are instituted, according to a report from TD Cowen.
As a measure of the potential economic impact of that uncertain scenario, transport company stocks were mostly trading down yesterday following Donald Trump’s social media post on Monday night announcing the proposed new policy, TD Cowen said in a note to investors.
But an alternative impact of the tariff jump could be that it doesn’t happen at all, but is merely a threat intended to force other nations to the table to strike new deals on trade, immigration, or drug smuggling. “Trump is perfectly comfortable being a policy paradox and pushing competing policies (and people); this ‘chaos premium’ only increases his leverage in negotiations,” the firm said.
However, if that truly is the new administration’s strategy, it could backfire by sparking a tit-for-tat trade war that includes retaliatory tariffs by other countries on U.S. exports, other analysts said. “The additional tariffs on China that the incoming US administration plans to impose will add to restrictions on China-made products, driving up their prices and fueling an already-under-way surge in efforts to beat the tariffs by importing products before the inauguration,” Andrei Quinn-Barabanov, Senior Director – Supplier Risk Management solutions at Moody’s, said in a statement. “The Mexico and Canada tariffs may be an invitation to negotiations with the U.S. on immigration and other issues. If implemented, they would also be challenging to maintain, because the two nations can threaten the U.S. with significant retaliation and because of a likely pressure from the American business community that would be greatly affected by the costs and supply chain obstacles resulting from the tariffs.”
New tariffs could also damage sensitive supply chains by triggering unintended consequences, according to a report by Matt Lekstutis, Director at Efficio, a global procurement and supply chain procurement consultancy. “While ultimate tariff policy will likely be implemented to achieve specific US re-industrialization and other political objectives, the responses of various nations, companies and trading partners is not easily predicted and companies that even have little or no exposure to Mexico, China or Canada could be impacted. New tariffs may disrupt supply chains dependent on just in time deliveries as they adjust to new trade flows. This could affect all industries dependent on distribution and logistics providers and result in supply shortages,” Lekstutis said.
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.