Here are some highlights from these trends in 2023 and implications on supply chain planning.
After the pandemic, retailers are faced with new challenges and disruptions due to global conflicts, trade restrictions, and now recessions. On a daily basis, supply chain teams are juggling new sustainability requirements, supply disruptions, sudden changes in consumer demand, and labor shortages.
Recessionary environments cause disruptions in the manufacturing industry around the globe, leading to long lead times, shortages, rising prices, and complications in transportation lines. With these at play, having agile planning systems which can consume large amounts of internal and external data and provide decision intelligence and decision automation are becoming essential capabilities retailers seek.
It is not easy for companies to cope with customers’ sudden changes in demand without agile planning capabilities leveraging advanced technologies such as AI/ML and Optimization. As we’ve seen over the past few years, businesses will keep automating and integrating supply chain planning capabilities, including demand-sensing, dynamic safety-stock management, inventory optimization, and external collaboration.
End-to-end visibility and ecosystem collaboration across suppliers, retailers, and 3PLs, provide the ability to manage the supply chain ecosystem more effectively in light of uncertainty and disruptions. Planners have been using control towers to spot issues and take action. Over the last year, with the rise of ChatGPT, planners’ exception management capabilities have been augmented by chat-based digital assistants.
Many industries, including the tech industry, are experiencing one of the largest layoffs in recent years; job insecurity in an inflation-ridden economy has left consumers with less disposable income, making them more conscious about what they spend their money on.
The retailers feel the impacts of the recession fast and deeply. Due to the workforce layoffs, consumers have less disposable income. This means they are more likely to focus on value and affordability and change their priorities and brand preferences when making purchases. They are more likely to shop for discounts and sales and may delay purchases of some items. At the same time, rising prices will change price elasticities and change the way demand shapes in response to promotional offers.
Retailers will also have an inventory surplus because people will buy less overall, meaning they may need to lower prices to clear their excess stock–hurting their profits. These changes influencing customer behavior require advanced demand-sensing capabilities and AI/ML to help retailers make smarter and more targeted promotion decisions through continuing test-and-learn cycles.
With the changing preferences and new ideas being tested, taking a test-read-and-react approach to assortment planning, leveraging advanced analytics and AI/ML technology for promotions planning and markdown optimization, and changing the way they order and interact with their suppliers to minimize risk will continue to be essential for fashion brands. As many retailers will look into sourcing products locally, re-evaluating their supply and logistics networks to optimize their supply chains will be more critical than ever.
Since the start of the pandemic, shoppers have been changing their shopping patterns and are now relying more on online shopping and mobile apps and asking for faster deliveries. In March 2022, online shopping was up 27% over the previous year. From the start of the pandemic until March 2022, online shopping went up by 33%. In 2022 overall, U.S. e-commerce online sales accounted for $1034 Billion.
Managing inventory across all interaction mediums—including online and offline channels—requires real-time inventory tracking, omnichannel order fulfillment, and transportation planning capabilities to optimize service levels while minimizing logistics costs. Increasing availability across all interaction channels with this new complexity to the order fulfillment dynamic is challenging.
In 2023, fast decision-making is crucial. And future supply chains will rely on effective data collection, advanced analytics, automation, and control towers augmented with AI/ML technology.
While brick-and-mortar stores can consider footfall, weather, holidays, and promotions, e-commerce companies factor in click rates, promotions, competitor offers, and customer journeys as they browse across different websites. ML algorithms help uncover insights within vast data landscapes.
Advanced machine learning (ML) technology is needed to reveal hidden patterns and correlations, facilitating accurate predictions and informed decisions.
Now the use of AI/ML is expanding beyond finding insights in data and providing predictions for the future. With the use of advanced technologies, planning decisions can also be automated. The evolution towards autonomous planning has gained speed over the last two years, and we already see businesses moving from human-in-the-loop decision-making to fully autonomous decisions on daily operational plans such as store replenishment, warehouse procurement, transportation planning, production planning, and order fulfillment.
Today, retailers are one of the most significant contributors to plastic packaging, representing 40% of global plastic usage. With the rise in online shopping, a factor contributing to plastic usage is e-commerce product returns, with an average of 20% of online purchases being returned.
AI can quickly analyze retailers’ data and identify the most returned items and the reason behind the returns. If a product is constantly found defective or otherwise disliked by consumers, the brand can pull that product out of circulation to limit the number of returns.
Another area where AI can help retailers increase profitability and reduce their environmental impact is reducing waste in the grocery industry. Food waste produces 7% of the world’s greenhouse gas emissions, mainly methane, an extremely potent gas. Not to mention that food waste costs retailers about $18.2 billion a year.
Minimizing waste in grocery retailers starts with accurate and robust demand forecasting. The better the forecast and replenishment decisions, the higher the financial benefit and the lower the waste.
All combined, the sustainability requirements will emphasize the need for end-to-end visibility systems that can track sustainability metrics, analyze data on the scale, and check vendor sustainability credentials all across the supply chain.
The number of cyber attack incidents and data breaches increased by 15.1% in 2021 compared to the year before. While supply chain compromises accounted for 1% of the intrusions in 2021, they rose to 17% in 2022.
In 2013, Target experienced a data breach that exposed the personal information of 40 million customers. The attack was traced to a third-party vendor responsible for heating and air conditioning services.
As supply chain networks and planning systems become more interconnected, attackers can disrupt operations without breaching a company’s servers. They can exploit vulnerabilities through vendors, partners, or clients.
The resulting delays and system outages can lead to empty shelves in retail stores, lost sales, and damage to reputation.
This trend highlights the need for increased cyber security measures, including experts, tools, employee training, and a proactive approach to securing company infrastructures. However, many companies need more resources to protect themselves adequately.
SaaS solutions offer a way for companies to keep their software up-to-date continuously without requiring a significant investment of the IT team’s time and resources. This approach saves time, money and preserves the company’s reputation.
Following her consulting tenure with Silicon-valley based software companies, she brought her Advanced Analytics and Business Process Engineering experience to Apparel Retail where she worked at Gap Inc. and Cache, where she led Merchandise Planning and Distribution teams to advance analytical capabilities in Forecasting, Assortment Planning and Price Optimization to improve sales and profitability.
Asena holds B.S. and Master of Engineering degrees in Operations Research and Industrial Engineering from Cornell University. She is one of the contributing authors in the Oxford Handbook of Price Management and has been a guest lecturer at San Francisco State and Columbia University business school on multiple occasions.
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