Customer activity repository

NHS Technologies helps customers implement SAP CAR to collect retail sales data from multiple channels for faster business decisions. Powered by lightning-fast SAP HANA in-memory technology, SAP CAR offers real-time inventory visibility, POS data transfer, sales analytics, and demand forecasting.

We can help you to

• Gather multichannel customer and POS data to discover and visualize real time insights.
• Forecast demand to optimize upstream business processes and decisions
• Personalize marketing through targeted promotions and product assortments
• Improve consumer experience with a real-time view of inventory and on-shelf availability.
• Simplify your IT landscape with a single, unified data repository

Promotion Management

Leveraging SAP Promotion Management for Retail( PMR), NHS Technologies can help to design and execute the most effective offers to customers. SAP PMR helps reach shoppers across all channels, including e-commerce, with multi-channel promotional strategies. Speed up promotion planning and execution by facilitating collaboration among marketing, merchandising, advertising, and finance teams.

Features of PMR

• Identify offers that will be most profitable based on shopper demand
• Reduce the time required to plan and execute a promotional event
• Target specific locations and products through focused marketing and merchandising offers
• Manage advertising budget by better understanding the expected financial performance of each offer

Allocation Management

All fashion retailers and most of the non-fashion retailers require advanced tools to plan their initial or in-season allocation to stores. SAP Allocation Management for Retail provides intuitive tools to business users to to plan their initial or in-season allocation to stores. SAP Allocation Planning to eliminate the cumbersome manual work and high possibility of lost sales.

• Define the parameters on the level of product groups, stores or distribution centers to provide business users with system-proposed allocation plans.
• Enhanced functionality allows for automated allocation processes at a custom level defined by the business.
• Launch new fashion articles for the first time in your retail in-store based on target stocks.
• Facilitate automatic fill-in during seasonal periods.

Merchandise Planning

SAP Merchandise Planning for Retail, helps retailors to go through the planning process where the objectives are planned revised and executed across different departments. Retailers can work on KPIs such as sales, purchasing budgets, margin or shrinkage goals with several versions and also monitor the progress based on the plans.

• Create companywide merchandise plan from the Forecasting data of UDF
• Develop sales, margin, inventory, and receipt flow at various levels of the merchandise, channel and time hierarchies

Assortment Planning

SAP Assortment Planning for Retail helps retailors to plan their merchandise across stores by identifying performing products and optimize assortments to gain maximum profit. SAP Assortment planning leverages data science and prediction.

• Use predictive algorithms to model product groups across selling channels
• Plan sales and purchase quantities by location clusters.
• Provide initial allocation instructions using approved purchase quantities.

Store Replenishment

Store replenishment is the latest add-on to CAR from SAP that leverages automation to enable faster replenishment planning while optimizing the ordering costs. This is primarily focused on the fresh products and supports replenishment configuration, planning, simulation, and alert management to accommodate the changing replenishment requirements. It is an app on top of CAR that works by importing data from SAP ERP into the Demand Data Foundation module of SAP CAR.

Key features

• Optimized ordering costs for each product at a specific store
• Intraday replenishment with improved demand consideration for order quantities
• Determination of order quantities based on real time inventory data
• Improved orders through prediction of expected spoilage