How to Leverage GenAI for CPG and Retail Optimization

By definition, we are all consumers and given the holiday season, will most likely be making retail purchases. Now consider the challenges that consumer packaged goods (CPG) companies and retailers face in understanding the nuances of your individual buying characteristics mapped to their specific supply chain realities and you have a PhD-level data analytics challenge.

GenAI for CGP and Retail Demystified

CPG and retail organizations looking to solve this challenge will require seamless integration with existing ERP, CRM, SCM, and HR systems (e.g., SAP, Oracle), then combine internal transactional data with external datasets, such as weather patterns and consumer price indices. This is the power of generative AI (GenAI) and simplifies these integrations to enable actionable insights that drive smarter, data-informed decisions for better business outcomes.

Whether it’s improving demand planning, optimizing inventory, forecasting commodity prices, or refining logistics, the platform empowers organizations to tackle challenges that were once beyond reach.

Know Your Customer and Forecast Their Patterns

Ultimately the winner will be the organization that best understands their customers and buying patterns through past, present and future state modeling.

The 9 GenAI use cases that potentially can deliver the best immediate value include:

• Demand Planning: Modernize traditional statistical forecasting methods with GenAI to avoid overfitting by minimizing or pruning out factors that have little-to-no demand impact and apply the machine learning algorithms not only on a product-store/channel level but also at different levels of aggregation (e.g., product-region or product-chain) and with flexible groupings to release 10-40% improvement in forecast accuracy and 10-20% improvement in inventory turns.
• Retail Fresh Product Order: Upgrade traditional “safety stock” based methods with GenAI to replacing static safety stocks for fresh products with probability-based order optimization to capture how demand volume and uncertainty fluctuate throughout the course of a week and enable fresh product retailers to optimize the trade-off between risk of waste and risk of lost sales.
• Supply Chain Network: Ensure good flow smoothly with GenAI to enable dynamic network optimization for “Click and Collect” or “Click and Deliver” fulfillment models by understanding the full range of products carried by each store as well as an array of store- and product-specific data to increase efficiency both in stores and in the distribution network.
• Store Clustering: Accommodate changing market forces with GenAI to understand demand patterns and local demographics across all categories within the store estate to quickly identify and rank categories which show the largest variation in demand across the estate and benefit most from the implementation of a more localized / store-level range & space customer offer to maximize ROI.
• Workforce Optimization: Apply GenAI/Machine Learning to satisfy both the short-term need to create well-balanced, effective work shifts and the long-term need to ensure the business meets contractual and regulatory requirements in mere seconds.
• Visual Merchandising: Understand store-specific optimization with GenAI to identify each product’s shelf placement and number of facings to be optimized based on local demand forecasts and inbound goods flow and leverage locally optimized planograms to drive tangible business value, reducing goods handling costs and increasing on-shelf availability and sales.
• Markdown Strategies: Optimize price elasticity with GenAI to autonomously identify the products and stores that will benefit from markdowns, then recommends the optimal markdown prices in accordance with the retailer’s pricing strategy and allow planners to quickly execute markdowns with little effort and accurately unlock new opportunities.
• Promotion Strategies: Improve ROI with GenAI to identify and define the relationships between promotion attributes and sales uplift while establishing a continuous relationship between variables (e.g. the price decrease and demand allows) and estimating the effects of individual variables as well as combinations and insights from the whole data sets and not depend on past promotions.
• Commodity Price Intelligence: GenAI can provide a thorough assessment of the supply market, regional supply chain cost structures, value drivers, and distribution costs and deliver predictive models to forecast the impact of various parameters – such as commodity prices, weather forecasts, prices of substitutes, raw material prices, to attain advantages in sourcing and procurement.

The best way to realize the value of GenAI for these use cases would be the use of a decision intelligent cloud where non-technical business leaders and data analysts/scientist alike can have immediate access to information without the need for proprietary resources or tools.

The Power of a Decision Intelligent Cloud for CPG and Retail

Vendors like UBIX deliver on the promise of a zero-code, highly scalable and flexible cloud architecture that leverages the best-in-class cloud technologies to support modern data workloads, including analytics, AI, and ML. A perfect fit for any AI transformation or intelligent cloud project. With an architecture that is designed to adapt to the varying demands of CPG and retail operations, you can scale up or down based on specific use case requirements.

By consuming all on-premise infrastructure, cloud-based infrastructure and cloud application datasets directly, UBIX makes the integration seamless and ensures that your existing data assets are fully utilized by LOB with a simple natural language query. This also frees data scientists and data analysts to address innovations instead of generating more superfluous reports.

Understanding the nuances of a decision intelligent cloud and how a no code solution can deliver on the promise of bridging the communication gap between LOB and IT for CPG and retail has never been easier. Download our free eBook titled “Solving the Problem of Data and Decision Making” to help better understand the details of emerging AI concepts and how to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AI Readiness Workshop, you can contact one of our AI experts today.