Submitted by admin on Thu, 08/18/2022 - 15:28

Poor management of stock levels leading to poor inventory turnover and loss of revenue

Sequence Number 2 Industry Retail Banner Poor management of stock levels leading to poor inventory turnover and loss of revenue How 5G enabled

5G enables real-time stock management – AI (ML) predicts demand and analyse optimised stock levels on shelves 

Data Flows
Title Devices Icon Devices Description
  • Sensors & cameras to monitor inventory levels
  • POS data can provide inventory insights
  • Data from other relevant sources: Weather; Temperature; etc. that impact customer behaviour
Title Connectivity Icon Connectivity Description
  • 5G will provide high bandwidth low latency connections, especially for processing video streams
Title Edge Compute Icon Edge Compute Description
  • MV at edge to process real-time visual inventory and customer behaviour data
Title Cloud Compute & Storage Icon Cloud Compute & Storage Description
  • All historical and real-time data stored in Enterprise owned storage
Title Applications & Services Icon Applications & Services Description
  • AI: (MV) monitor current stock levels; (ML) to predict stock demand (based historical, weather etc. data) for re-ordering; and to optimize inventory Planogram [1] recommendations
Title Inform Decision Makers Icon Inform Decision Makers Description
  • Should be an autonomous process; Normally no need to ask decision makers
  • Real-time inventory Planogram change instructions can be sent directly to in-store staff smartphone, tablet, or smart glasses
Title Support Decision Making Icon Support Decision Making Description
  • End of process
Application Logic
Description
  • Smart Shelf Sensors (e.g., Weight Sensors and RFID antennas) to automatically scan and determine store inventory levels Fixed and mobile (e.g., in-store staff smart glasses, autonomous robots) cameras to monitor store inventory levels
  • Data collected will be used for stock management applications and inputs for AI
  • Relevant data will be stored either on-site or in a central enterprise storage from multiple stores
Description
  • Model will be stored and maintained by AI application
  • Consideration for a separate system (e.g., other sensors) for goods that cannot be tracked in the same manner.
  • Model will predict over-time, the optimized stock level forecasts for all SKUs to prevent out-of-stock (OOS) issues and to increase inventory turnover, based on customer purchase behaviour, seasonality, weather etc.
Description
  • Data collection, the execution of models and addressing the outcome will be fully automated
  • AI (MV) models will be improved over time and will be fully relied on in the future
  • SME and Data Scientists will collaborate in developing and deploying MV models and other AI solutions
Expected benefits Key value created