Right From the Start: Demand Planning’s Role in Supply Chain Success
The hallmark of a successful retail supply chain starts with demand planning: Just like in the classic Goldilocks fairy tale, a retailer wants neither too much nor too little when predicting the amount of necessary inventory. Of course, getting that “just right” recipe is easier said than done on a good day — throw a pandemic or a logged cargo ship in the Suez Canal, and even the most prepared retailers are stress tested.
By tapping into advanced analytics, machine learning and artificial intelligence, retailers can better set themselves up for success by becoming more targeted in their forecasting.
Many retailers are already using artificial intelligence as part of their demand forecasting solutions, Neil Saunders, managing director and retail analyst at GlobalData Retail, tells RIS, citing Costco, Walmart and Amazon as a trio of examples. Costco uses AI to help predict demand for some perishable items, while Walmart has built it into many of its forecasting operations, including developing an automated re-ordering system with Procter & Gamble.
“Retailers are eager to use AI as they see it as a way to help improve forecast accuracy. It also helps them plan during periods of rapid change when it can be challenging to understand demand.”
NEIL SAUNDERS
Managing Director and Retail Analyst
GlobalData Retail
This isn’t to say that AI is a cure-all for all supply chain disruption. Saunders notes that the product shortages experienced in 2020 occurred as a result of a lack of capacity to produce or deliver certain products. “AI would not have fixed that.”
Leveraging AI within demand planning also carries sustainability benefits, as having the right amount of product on hand ultimately translates into less waste. For apparel retailers, this means fewer markdowns to get rid of inventory at the end of the season, while grocers have to contend with less food spoilage.
Convenience chain Kum & Go is unifying its supply chain and merchandising optimization with a little help from machine learning. The retailer recently gave its forecasting and mobility capabilities a boost by leveraging ML-driven forecasts that factor in more data sources to increase order accuracy. It’s also integrating technology that enables store-level exception-based order review and mobile planogram review, both of which are expected to improve interaction between its operations and merchandising teams.
Retailers expect to spend more on business intelligence/data analytics, and 35% will increase spending on artificial intelligence
Source: Gartner via Retail Dive
63%
The Future of Inventory Management
The pandemic exposed gaps in the retail supply chain to consumers as out-of-stocks left shelves bare and e-commerce orders placed were disconnected from stock realities. These major hiccups will not soon be forgotten by the public, which is perhaps why 33% of grocers have kicked off a major upgrade to their real-time inventory capabilities, and another 20% will do so over the next two years. When asked what solutions they are most interested in to help improve their inventory capabilities, grocers, who suffered highly publicized inventory woes, pointed to real-time reporting, artificial intelligence and machine learning.
Bringing inventory management into the cloud further fosters synchronization. Bed Bath & Beyond recently tapped a cloud-based technology platform to deliver automated forecasting, replenishment and allocation planning to improve the company's in-stock position and inventory turnover, enhancing the customer experience while driving sales and gross margin improvements.
"We are leading with a digital-first, omni-always approach to build authority in our core markets and make it easy to feel at home,” says CTO Scott Lindblom. “Investing in modern inventory management technologies is a critically important component of this approach.”
AI-enabled supply chains are
more effective with reduced risk and lower overall costs
Source: ResearchandMarkets
Success in leveraging AI throughout the supply chain hinges upon data accuracy. “Very often the initial data input is inaccurate, which can impact the quality of the AI predictions,” Saunders notes. “For complete visibility, AI also needs to link to the constant monitoring of stock” given the risk products face in being lost, stolen, damaged or accounted for incorrectly. As a result, AI can receive an inaccurate view of availability, which is why most retailers today are using AI alongside human forecasting.
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53%
35%
30%
Grocers’ Have a High Level of Interest in Investing in the Following Tech to Improve Inventory Management
Real-Time Reporting
Computer Vision
Artificial Intelligence
28%
25%
18%
Machine Learning
In-Aisle Robots
RFID
Source: RIS, “Grocery Tech Trends Study 2020: Adjusting to the New Normal”
“Inventory management powered by machine learning gives brands real-time consumer data, enabling the synchronization of inventory across all sales channels and optimizing delivery for speed and cost,” notes Coresight Research.
Grocers’ with up-to-date inventory management technology in place today
Source: RIS, “Grocery Tech Trends Study 2020: Adjusting to the New Normal”
26%
Autonomous Robots Enhance Inventory Management
Schnuck Markets brought autonomous robot Tally, the inventory-management solution it first piloted in July 2017, to half of its stores in September 2020.
Dave Steck, Schnucks VP of IT infrastructure and development, says Tally’s use has resulted in 14 times more out-of-stock detection than manual auditing and at least a 20% reduction in out-of-stock items. It’s also increased accuracy of real-time inventory that feeds into Schnucks’ automated replenishment system, allowing for more efficient inventory management.
Access to real-time product location data through the Schnucks Rewards app enables more efficient restocking for associates, and streamlined ordering and replenishment ensures store shelves are restocked faster. Tally robots scan more than 4.2 million products per day — giving Schnucks accurate, frequent and comprehensive insights into product flow and operations.
“The amount of critical data and valuable insights that Tally continues to bring us from a select number of stores is immeasurable. By introducing Tally to more than half our stores, we will improve our in-stock position for our customers and free up our teams from tedious inventory-related tasks, allowing more focus on service.”
DAVE STECK
VP of IT Infrastructure and Development, Schnuck Markets
A tire’s DOT code is essentially its barcode, which can make managing tire inventory throughout the supply chain a nightmare. Previously, Discount Tire technicians used a pen and paper to record each DOT code and manually measured as many as 12 different spots for tread depth. With the new mobile handheld solution, technicians can complete an assessment typically in under five seconds per tire. Technicians simply swipe each tire to scan the DOT code and check tread depth with the tool’s camera in real-time. They can instantly capture the DOT tire identification number on the sidewall of any tire to determine age and manufacture location. The mobile solution even integrates with Discount Tire’s technology system to help eliminate other paper-based processes, such as automating the creation of customer profiles.
Discount Tire Harnesses Mobile Solutions for Inventory Management
Distributed Order Management Puts E-Commerce Pieces Together
Thanks to all of these sky-high consumer expectations, distributed order management is becoming a must-have investment in today’s retail climate. In RIS’ 2021 Retail Technology Study, published in April, distributed order management was the only one of the 80-plus benchmarked technologies to finish in the top five for the all-systems-go trifecta of currently investing, will invest in 12 months, and will invest in 24 months.
And for good reason: Given the pandemic-prompted dramatic spike in e-commerce — and the subsequent increase in new fulfillment methods — knowing how to get the right product to the right place in the most efficient and cost-effective manner is a crucial component of the consumer experience. With a modern order management system, retailers are better situated to not only accommodate inevitable supply chain shifts, but also improve their collaboration with suppliers prior to ordering. All of these benefits combine to ensure products are where they’re supposed to be — increasing a retailer’s chance to develop customer loyalty and repeat purchases.
“Being able to manage our inventory, no matter where it is, is really an advantage for us.”
JANEY WHITESIDE
Executive Vice President and Chief Customer Officer
Walmart
Walmart pulled inventory from stores and redirected orders to get them fulfilled when its distribution center faced out-of-stocks during the pandemic.
Retailers who cited an inability to make rapid adjustments with supply chain partners as a top 5 supply chain obstacle
Source: RIS, “Supply Chain Technology Study 2020:
Balancing Supply Chain Resilience and Efficiency”
56%
Distributed Order Management
Retail Leader View: AI’s
Greatest Impact in Next 2 Years
Sustainable fashion retailer Frank And Oak, part of the United Commerce Group (UCG) brand portfolio, improved its omnichannel experiences by not only upgrading its POS system, but also its order management system so that it integrated both
e-commerce and store inventory. By doing so, the retailer doubles down on ensuring its offering all inventory to customers regardless of location or purchase channel.
What’s more, the technology can be managed by store associates using iPhone apps, and the company can have a single system for all inventory, orders and customer data. This means that setting up new Frank And Oak stores will be as simple as shipping out a box of iPhones, UCG co-founder and CEO Dustin Jones says, noting it intends to extend the model to its other brands.
Up-to-Date Technology in Place
Started But Not Finished Major Upgrade
Will Start Upgrade Within 12 Months
Will Start Upgrade Within 12-24 Months
No Plans
Source: RIS, “31st Annual Retail Technology Study:
Building the Future-Proof Enterprise”
14.3%
28.6%
17.9%
7.1%
32.1%
Customer Intelligence
Inventory Management
Chatbots for Customer Service
53%
50%
49%
Fast, Faster, Fastest Fulfillment
To simply say the pandemic boosted e-commerce is not telling the whole story. What it did was skyrocket consumers’ expectations to place orders digitally and receive them anyway they want, whether that’s a 30-minute curbside pickup, such as Walgreens rolled out last November, or to their doorsteps in two hours with no minimum order requirement, a change Walmart made this March.
"Retail has evolved to be as much about how you sell, as what you sell, which has
brought the supply chain closer to the consumer and raised its level of importance to the organization. If you do not offer fulfillment options that consumers seek, they will go elsewhere,” says Jordan K. Speer, research manager, global supply chain, in “IDC PlanScape: Omni-Channel/Curbside Fulfillment Technology.”
Bringing inventory closer to the consumer is key in meeting these demands, and to
do this, clean real-time data is obligatory.
“AI and analytics can determine the products or types of products most likely to be purchased online for pickup, and perhaps situate those closer to the staging area, for faster picking and packing,” says Speer. “AI can also be applied to task management and picking workflow to tie orders to the planogram, to present the order to the picker to align with the shelf.”
While necessary to appease customers, omnichannel order fulfillment is driving up costs. AI offers a solution, and these technologies must become a part of planning and operations in order to make the anytime/anyway experience profitable.
To increase the efficiency of capturing a tire’s Department of Transportation (DOT) information and tread depth, Discount Tire recently deployed a mobile computing solution nationwide.
Up-to-Date Technology in Place
Started But Not Finished Major Upgrade
Will Start Upgrade Within 12 Months
14.3%
28.6%
17.9%
Will Start Upgrade Within 12-24 Months
7.1%
No Plans
32.1%
Retailers will have up-to-date fulfillment technology in place or will have started an upgrade within the next 12 months.
Source: RIS, “31st Annual Retail Technology Study: Building the Future-Proof Enterprise”
72.4%
Levi Strauss & Co.’s new ship-from-store capability fulfilled 20% of all its e-commerce volume in Q3 2020, as well as its buy-online-pickup-in-store (BOPIS) capability, now in the majority of its U.S. fleet. Levi’s is using AI in its U.S. stores to ensure it’s optimizing margins in fulfilling orders in the most efficient ways, which has been critical with the rollout of ship-from-store, president and CEO Chip Bergh said in an earnings call.
“We actually used AI to steer the orders to where we have the biggest opportunity to clear that specific inventory,” he says. “And that’s a capability that we’ve built and we are going to continue to leverage that on a go forward basis.”
Bergh also notes Levi’s is making “good progress” on leveraging data analytics and machine learning in more aspects of its business.
“At our stores, AI is enabling local stores in China and the U.S. to better curate their assortments by predicting demand based on the specific profile and preferences of consumers in the vicinity of each store, which will thereby optimize the profitability of these smaller mainline doors.”
Source: KPMG, “Thriving in an AI World”
AI-Efficient Fulfillment
Kroger Delivery’s First Customer Fulfillment Center (CFC) Opens
In Kroger’s highly automated CFCs, powered by Ocado Group, over 1,000 bots whizz around giant 3D grids, orchestrated by proprietary air-traffic control systems in the unlicensed spectrum. The grid, known as The Hive, contains totes with products and ready customer orders. As customers’ orders near their delivery times, the bots retrieve products from The Hive and are presented at pick stations for items to be sorted for delivery, a process governed by algorithms that ensures items are intelligently packed. For example, fragile items are placed on top, bags are evenly weighted, and each order is optimized to fit into the lowest number of bags, reducing plastic use. After being packed, powerful machine learning algorithms dynamically optimize delivery routes, considering factors like road conditions and optimal fuel efficiency.
Top Challenge an AI-Enabled Supply Chain Might Help Your Business Address?
We need to offset the higher cost of omnichannel fulfillment with smarter supply chain strategies
Tackling the Rate of Returns
As e-commerce sales rise, the changing tide brings along another retail challenge: the rising rate of returns. “Last year, we saw an increase in returns of online purchases as the pandemic forced more consumers to shop online,” says Mark Mathews, NRF’s VP of research development and industry analysis. “Retailers view the return process as an opportunity to further engage with customers, as it provides additional points of contact for retailers to enhance the overall consumer experience.”
While the total rate of returns is in line with recent years, according to NRF, online returns more than doubled in 2020 from 2019 and are a major driver of the overall growth of returns. Approximately $102 billion of merchandise purchased online was returned. In addition to impacting the bottom line, retail returns have an adverse impact on the environment across three key areas: landfill, carbon emissions, and packaging and plastic waste, Coresight Research warns. “Employing artificial intelligence and machine learning can help retailers and brands rapidly deploy returns solutions and reverse the returns trend,” the firm adds. “New innovative retail tech companies are developing solutions to address multiple returns challenges.”
Amazon, Walmart and other companies are using artificial
intelligence to decide whether it makes economic sense to process a return, The Wall Street Journal reported earlier this year, opting to refund the purchase price and let customers keep the products when it’s cheaper than incurring hefty shipping fees for large or inexpensive items.
Meanwhile, apparel e-tailers are turning to AI and ML to help customers not only discover new products that may pique their interest, but also identify SKUs and specific sizes they’ll happily keep in their wardrobe, says Rolling Stone. New experiences such as virtual fitting rooms have emerged, allowing home shoppers to “try on” products and then decide whether or not to purchase them online, resulting in a lower frequency of returns.
“Returns reduction efforts of the past have been hindered by lack of comprehensive data that may be siloed throughout the organization. Getting the complete picture of the causes of returns requires the consolidation and analysis of massive amounts of structured and unstructured data. Advancements in AI, analytics and automation have allowed for new solutions to the age-old problem.”
Coresight Research
IKEA implemented technology in 10 distribution centers, 50 retail stores and the U.S. customer support center to streamline the returns flow and improve the customer experience. The platform aims to remove waste from IKEA’s reverse supply chain as part of the retailer’s mission to build a circular business by 2030. It leverages data analytics and machine learning to help retailers efficiently manage and resell returned inventory.
IKEA’s AI Solution
“[The] solution enables us to eliminate much of the waste created in the reverse supply chain, from minimizing the carbon emissions released in return shipping to finding the best next homes for returned items,” says Javier Quiñones, president and chief sustainability officer of IKEA Retail U.S.
Conclusion
As consumers increasingly insist upon fulfillment any way and anywhere they want, planning for demand, order and inventory management, and near-instantaneous order fulfillment becomes a monumental task — one that cannot be achieved without AI and ML powering the modern retail supply chain.
The need for real-time inventory visibility and the ability to connect that visibility throughout the enterprise is key. Once next-gen inventory management is achieved, the instant an order is placed retailers must be able to pinpoint the quickest and most economical way to fulfill it.
AI solutions can instantaneously examine inventory levels, delivery distance, fulfillment options and local demand to arrive at the most cost-effective fulfillment solutions. In addition, these technologies can achieve a deep understanding of consumer purchasing habits, allowing retailers to position the right inventory, closer to the end customer. If and when shoppers seek to return items purchased, having AI in their corner can help retailers ease the cut into the bottom line.
Source: RSR, "The Case For An AI-Enabled Retail Supply Chain”
Retail Winners
Others
44%
35%
Returns Management
Source: RIS, “31st Annual Retail Technology Study:
Building the Future-Proof Enterprise”
Up-to-Date Technology in Place
Started But Not Finished Major Upgrade
Will Start Upgrade Within 12 Months
32.1%
17.9%
17.9%
Will Start Upgrade Within 12-24 Months
3.6%
No Plans
28.6%
Estimated amount consumers returned in merchandise to retailers in 2020, approximately 10.6% of total U.S. retail sales.
Source: NRF
$428
billion
Look to advanced analytics, machine learning and artificial intelligence to not only improve forecasting accuracy but to also advance sustainability goals.
Utilizing AI and ML to power inventory management will allow for synchronizing inventory across all sales channels through real-time consumer data.
Upgrading your order management systems can help with inevitable supply chain shifts, as well as supplier collaboration.
To meet consumers’ need for speed, while remaining profitable, use AI to both predict local demand and determine how to fulfill orders in the most efficient ways.
Use AI and ML to help mitigate the cost of returns by better identifying exact needs to reduce returns in the first place, and determining whether it makes economic sense to process a return when they do occur.
28.6%
27.6%
27.6%
Currently Upgrading
Distributed Order Management
Logistics
Fulfillment
24.1%
17.9%
Warehouse Management
Returns Management
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Source: RIS, “31st Annual Retail Technology Study: Building the Future-Proof Enterprise”
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over 65%