According to Bain & Co.’s 2024 Consumer Products Report, the industry is grappling with slowing growth and increasing pressures from both the global market and evolving consumer expectations. To remain competitive, companies are being urged to reset their growth strategies, emphasizing sustainable innovation, digital transformation, and operational agility. Businesses must adapt to disruptions in the supply chain and shifts in consumer behavior, positioning themselves to seize emerging opportunities while maintaining a focus on long-term objectives.
While it might be perceived as a Herculean feat, reducing markdowns by 30% can be a game-changer for retailers looking to optimize profitability, and smart allocation and planning are key to making it happen. By strategically aligning inventory with customer demand through the use of advanced data analytics, retailers can minimize excess stock and lost sales, reduce markdowns and increase full-price sales. But how can retailers effectively forecast and manage inventory across diverse product categories?
A Focus on Breaking Down Silos
The answer is by facilitating real-time Sales & Operations Planning (S&OP) and enabling better collaboration between sales planning and supply chain planning teams–breaking down silos and fostering more effective collaboration across the organization. This is best done with an industry specific platform that uses AI and machine learning to revolutionize merchandise planning and allocation, and drives profitability. Once retailers and wholesalers are able to move away from manual processes like Excel, holistic approaches that use AI and machine learning are able to provide granular consumer demand insights. Today, the capability exists to dig right down to the SKU (stock keeping unit) at a specific store for a given week. This level of detail allows retailers to make smarter, faster inventory decisions based on real-time, localized demand.
In addition, AI-driven systems can accurately forecast demand, ensuring optimal stock levels and minimizing the risk of overstocking or stockouts by analyzing real-time sales data, customer behavior, and market trends. This advanced technology enables dynamic, data-informed allocation, helping businesses meet customer demand while significantly reducing markdowns and improving profitability across various product categories.
Delivering Real Results Through Smart Allocation and Planning
Clients have experienced firsthand the significant benefits of using these solutions. For example, one large conglomerate reported that by utilizing a wholesale account planning system, they were able to place their production orders a week earlier, leading to a $1/garment cost reduction form their supplier–a notable savings in the retail industry.
7thonline clients have gained increased visibility across multiple continents, allowing them to track local demand in various countries and regions. This ensures that headquarters can stay ahead of demand signals across the entire organization. By breaking down data silos, companies are empowered to use their data to make meaningful improvements in both operations and profitability.
Streamlined Stock Management for Optimal Performance
By integrating demand-driven allocations, tailored strategies based on product attributes, and real-time replenishment tools, retailers can significantly enhance their inventory management processes. Balancing push and pull methods, alongside quick reorder algorithms, ensures that stock levels remain responsive to changing demand, reducing the risk of overstock or stockouts. This holistic approach not only improves customer satisfaction by keeping popular items in stock, but also enhances overall profitability through better resource management.
Demand-Driven Allocation for Maximum Sales Potential
Effective allocation and replenishment systems are critical for maximizing product sales and reducing inefficiencies. Demand-driven approaches focus on distributing inventory based on which products have the highest propensity to sell. By analyzing consumer behavior and sales trends, retailers can ensure that the right products are placed in the right location, optimizing the chances of meeting customer demand. This method not only improves stock availability but also minimizes the risk of overstocking less popular items.
Tailored Allocation Based on Fashion, Season, and Attributes
To enhance inventory accuracy, optimal allocation methods are tailored to consider fashion, seasonal trends, and basic product attributes. This ensures that products are aligned with local market preferences and timely demand changes. For instance, fast fashion items may require more dynamic allocation based on emerging trends, while basic or staple items can be managed with steadier forecasts. Retailers benefit from a balanced approach that meets both store-term trends and long-term needs.
Actionable Insights for Pre-and-Post-Allocation Adjustments
A comprehensive allocation system provides recommendations not just before, but also after allocation, allowing retailers to fine-tune their strategies. Pre-allocation recommendations help in distributing inventory proactively, whole post-allocation feedback allows businesses to adjust stock levels based on real-time sales data. This continuous cycle of adjustments ensures that inventory levels remain optimal across different locations.
Technology’s Promising Future for Enhanced Profitability and Quality of Life
AI is reshaping the role of buyers, allowing them to stay ahead of trends and introduce product assortments that align with customer demand, particularly for seasonal items. According to a study published by Forbes, 60% of apparel products bought by buyers aren’t profitable, while only 40% are. This is because many decisions are made pre-season, long before customers interact with the products. AI enables retailers to gauge consumer behavior at the start of the selling season and make smarter, secondary product assortment allocations based on real-time data. Ultimately, retailers and wholesalers that are able to embrace AI and machine learning will be better able to minimize markdowns, increase profitability and ultimately enhance the quality of life for the stakeholders of the entire retail supply chain.
Read the original article on Fashion Mannuscript here: https://issuu.com/mannpublicationsmagazines/docs/digital_issue#:~:text=For%20our%20October%202024%20edition,as%20we%20enjoyed%20crafting%20it.
To learn more about our AI-based smart allocation and demand planning tool for retailers and wholesalers, email us at info@7thonline.com or book a demo with our team.
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