Retailers face unprecedented challenges with supply chain volatility, inflation, oil price fluctuations, labor shortages and geopolitical activities, making it difficult to plan across the organization.
With retail evolving, coupled with persistent supply chain issues, this adds complexity to anticipating and planning for shifts in consumer demand.
The emergence of an unpredictable and sustainable shopping mindset is pushing retailers to rethink their strategies for entire product categories. Staffing shortages, empty shelves, and product recalls are driving customers to ditch their preferred brands for alternatives.
Additionally, traditional demand planning processes are often managed by several different teams across a retail organization, which has not always been effective. The truth is retailers are having a difficult time interpreting and meeting shifting consumer demand.
To address these challenges, intelligent planning solutions, driven by AI and machine learning, emerge as a crucial solution.
Here’s what we mean
Merging data-powered analytics into operations can enhance predictability and overcome challenges across the retail network. Leading retailers invest in AI and machine learning for improved planning, with solutions like SAS® Intelligent Planning facilitating effective management of diverse inventories. Retail planners can now manage a range of categories and brand inventory across a magnitude of stores.
Starting from fast-moving consumer products or seasonal items like apparel to slow-moving, higher-priced non-essential products. Everything can be allocated in the right place at the right time without the worry of over/under stocking or markdowns.
Yildiz Holding attests to the success of demand planning from SAS to improve forecasts for manufacturing, inventory and sales planning processes.
“The forecasting accuracy rate of demand sensing across the group increased by 15%, while overstocks and understocks were significantly decreased We eliminated several disjointed processes for demand sensing and replaced them with much faster, integrated ones.”
Gul Erol, CIO, Yildiz Holding CEO, Yildiz Tech
A heap of benefits for organizations
Successfully implementing an AI-driven demand planning strategy is a challenging yet crucial task for retailers. Operating in silos with traditional planning systems is no longer viable. Mastery of forecasting not only provides a competitive edge but also aligns retailers with shifting consumer behavior expectations.
The advantages of superior retail planning are significant, leading to better business decisions. Achieving this brings forth a range of benefits:
- Informed inventory decisions.
- Increasing inventory turns through reduced out-of-stocks and elimination of excess inventory.
- Cost reduction by minimizing product markdowns.
- Enhanced customer experience.
- Optimize logistics and transportation planning.
- Reduce waste and working capital.
In essence, a successful demand planning strategy not only meets current challenges by positions retailers for sustained success as the market changes.
Why chose SAS for retail planning?
SAS is recognized as a leader in retail planning, valued for its expertise in AI and machine learning on large datasets. Our retail planning platform automates key aspects like financial planning, assortment optimization and demand shaping at scale, seamlessly embedding adaptive AI into daily workflows.
Forrester recently recognized SAS as a leader for retailers or brands that "value expertise in running sophisticated AI and ML against large data sets."
Building on five decades of innovation and profitability, SAS incorporates AI and machine learning throughout the planning lifecycle, facilitating data management, model development and deployment on the flexible Viya Platform. Serving diverse retail and CPG clients, including Belk, Carrefour and Nestlé, SAS’ current offering excels in deployment options like AWS, Azure or Google Cloud Platform or as a managed service.