Smart Retail & Trade
Digital solutions open up diverse opportunities in the retail sector and set new standards for customer orientation, process efficiency, and cost reduction. The systematic integration of production, warehousing, logistics, and the sales floor creates transparency in workflows, reveals opportunities for optimization, and enables quality improvements.
Smart retail implies a customer-centric approach. Analyzing and evaluating consumer behavior and customer segments is essential for identifying and meeting customer needs. By leveraging modern AI and physical analytics methods, we are able to generate reliable demand forecasts and ensure better planning capabilities.
Holistic, data-driven, and automated monitoring of the supply chain fosters the decentralization of decision-making and drives faster, more efficient implementation. Decision-makers maintain a global overview while remaining close to the customer at all times.
OmegaLambdaTec supports retail operators, retail chains, and corporations in unlocking the potential of innovative retail business.
OUR SERVICES AT A GLANCE
- Automated analysis of product, demand, and customer flows, as well as supply chains and logistics.
- Data-driven forecasting of production, demand, consumption, logistics, or prices
- Retail-optimized solutions for complex real-time systems using simulations
- Digital twin concepts for live IoT-based optimization of logistics processes
- AI-based characterization and segmentation of specific product and customer attributes
- Data preparation for migration in real-time database systems
REAL-WORLD USE CASES WE’VE SUCCESSFULLY DELIVERED
Optimized data-driven sales and replenishment forecasts for the retail sector
Key Challenges and Goals
Sales patterns and demand planning for individual retail products are complex processes influenced by numerous unknown external factors (e.g., holidays, events, seasons). A critical challenge for product providers is to forecast expected sales across the entire product range as accurately as possible. In particular, the aim is to optimally forecast and meet demand for products ranging from those in high demand to those with low or negligible demand.
Figure: Schematic representation of optimized demand and stock-level forecasts for the retail sector.
OLT-Solution
- Automated statistical analyses and ML methods for demand forecasting of individual product categories, product groups, and individual products.
- ML methods for identifying hidden correlations between individual product attributes
- Precise planning chains based on the exact demand for a specific product at a specific time or location (e.g., branch office, aircraft, etc.)
- Optimization of inventory levels and capacity utilization based on the analysis of historical sales figures.
- Forecasting and impact of new product categories, product groups, and individual products on purchasing behavior and demand.
Benefit
- Optimization of returns and costs for the integrated system comprising production planning, consumption, and demand.
- Precise process and planning chains for the production and demand of specific individual products for a particular point in time or location.
- Cost reduction for the loading process of transport systems (e.g., trucks, aircraft) while simultaneously maximizing the utilization of available capacities.
Retail-optimized gate positioning for airports
Key Challenges and Goals
Airport operators and retail shop owners face numerous uncertainties, stemming in part from fixed locations and the time- and customer-specific constraints governing the shopping behavior of air travelers. Strategically positioning aircraft and shops at specific gates can significantly boost retail sales. How, then, can shops and aircraft be positioned at airport gates to maximize retail revenue?
Figure: Scenario simulator for revenue maximization through optimal gate positioning.
Passengers with the largest budgets should be able to spend enough time in the shops with the highest sales potential.
OLT-Solution
- Automated simulation framework for solving the complex airport positioning problem using efficient solver algorithms.
- Automated monitoring using an analysis tool that accesses the airport’s fluctuating shop, purchase, and customer data on an hourly basis.
- Establishment and integration of the current utilization of hubs, gate positions and variable flight schedules
- Evaluation and adjustment of all model properties to seasonal changes
- Evaluation of feasibility and business potential using a digital twin simulation framework
Benefit
- Optimal capacity utilization and potential to increase total revenue across all retail stores by more than 20% through the optimal matching of customer demand and store locations.
- Investitions-optimierte Planung und Koordination der Flughafenbetreiber, Airlines und Retail-Anbieter
