Retail revolution: Fast fashion disrupts priorities, AI reshapes supply chains


By Dan Mitchell, Global Director- Retail & Consumer Goods, SAS

Shoppers who frequent online “fast-fashion” marketplaces like TEMU and Shein are sending a signal to retailers: One- or two-day shipping may not be the highest priority anymore. So what is critical to shoppers? The rising popularity of these low-cost sites indicates deep discounts and 1-click shopping are more prized and offer less risk, especially for younger shoppers. These marketplaces represent a new platform, new sellers, and new products. If you don’t mind that it may take two weeks to receive your package of steeply discounted holiday twinkle lights, this e-commerce option works.

This e-commerce reality may encourage retailers like Amazon, Target, and Walmart to cut prices in response, and that could trickle down into staffing and service support gaps. This trend may also push established retailers to finally replace aging fulfillment systems and fully embrace initiatives like shorter
demand planning cycles, better forecasting techniques, and price optimisation. If these kinds of fast-fashion discounters have staying power, the pendulum may swing for more established retailers to rethink their assortments for a new balance of quality and low-price merchandise offerings. Boosting fulfillment systems technologies into the cloud not only makes them more agile, the cloud also makes using them easier, more cost-effective, and more secure.

The MGM Resorts cybersecurity breach in September 2023 raised the question: For better security, should click-and-connect systems (like dining, room access, gaming) be separated from other technology systems in a retail environment? The breached organisation can’t just unplug and reset because critical customer data will be lost. Incorporating a data clean room into retail information systems could be the best middle ground as it offers the retailer an option to anonymise and protect customer data from cyber criminals even during a disruption.

AI and analytics applied to customer data help savvy retailers survive the ebb and flow of inflation and other consumer pressures. Deep customer insights allow a retailer to adapt the way they interact with shoppers to strengthen the brand. Even when consumer spending is tight, understanding the customer-specific category needs and wants allows the retailer to shift the strategies around promotions and shopper experience to inspire buying. Look beyond broad-brush shopper insights in favor of long-term planning that focuses on an individual customer’s lifetime value to your enterprise.

Powerful technologies like AI and analytics will observe what’s happening in real-time – shifting consumer trends, sudden market disruptions, insufficient inventory levels – and offer retail and CPG companies complete visibility from supplier to shipping container to a customer’s front porch. Known as a high-velocity supply chain, it will allow an organisation to “see the future” in ways that enable real-time decision-making, avoid serious and costly risks, and keep customers happy and loyal. A high-velocity supply chain offers the kind of transparency that reduces costs, retains and expands the customer base, and
optimises operations.

Capturing and analyzing real-time data is the first step in creating a high-velocity supply chain. Data can come from current sales, SKUs, cargo ships, rail, ground transportation and distribution centers. Collecting data when disruption happens is also critical whether it’s tracking a hurricane approaching a major port, track failure for trains feeding an essential distribution hub, or draughts that lead to crop failures and materials shortages. Data at the order, line, and SKU levels will be used to refresh forecasts in real time. When coupled with consistent correlation analytics on existing and new data sources, an organisation can produce more accurate results to protect customer loyalty.

This type of meaningful data analysis helps an organisation understand, predict, and remain agile. It allows an organisation to accurately predict whether an item is in or out of stock. And if an item is out of stock at a particular store, the organization can pinpoint where it is anywhere along the supply chain so
a customer’s needs can be met in ways that maintain satisfaction and loyalty.
With inflation and reconfigured global supply chains as perennial headline grabbers, consumer goods companies understanding consumer behavior changes will be more important than ever. It will help organisations get closer to their customers and find ways to personalise offers and drive loyalty. Rapidly evolving technologies like AI, machine learning, and digital twin simulations are important for consumer goods companies to gain these insights and confidently take action.

For example, by merging digital twin capabilities with analytics, a consumer goods company can visualize how its supply chain functions and how it may be affected by unplanned pressures. It helps the organisation anticipate problems and road test plans before they’re rolled out.


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