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Robot Monitoring for Shelf Audits in Retail Store

"Annotation Services for a retail store"

Executive Summary

Where supply chain activities are becoming automated, the use of robots has proven optimal for shelf conformity and stock integrity. This case study tries to present the experience of a large retail chain to work with robotic systems for shelf audits and their effectiveness in increasing efficiency and accuracy within the store.

Retail Store

Background

Problems such as stock-out situations, over-stock situations or misplacement of product inventories are generic challenges across the retail industry. Normal shelf checking methods by human beings is tiresome and full of inaccuracies. In order to overcome these problems, such a retail chain signed a contract with a robotics company and introduced identical unmanned robots with purposes of shelf audit. However the Robots needs monitoring to ensure the tasks are accomplished as desired. 

Objectives

  • To Monitor the Robots and ensure proper navigation in the store aisles to perform the task.
    • To run scheduled shelf audits on an automated basis for increasing the accuracy of inventory.
    • To perform manual labelling of SKUs which are unidentifiable by the Robots. 
    • To annotate data for machine learning
  • To minimize the cost of time that staff uses when checking the shelves manually.
  • To enhance positioning and display or the products.

Implementation

 1. Chosen Technology The mobile retail chain chosen technology consists of a series of robotic that comes with imagining technology, RFID scanners, and machine learning. These robots were self-driving and were equipped with capability of recognizing products and evaluating compliance level of shelves.

 2. Deployment strategy The company initially piloted the system in 10 stores before the rollout across the firm’s outlets. The robots were used at certain time of the day in order to reduce their interference with normal business. In order to manage the robots, the staff were trained how to approach them and also on the interpretation of the obtained results.

 3. Data Integration The robots were also integrated with the stores current inventory system so the status of the store stock and the position of the products in the store was constantly updated.

 4. Monitoring The robots are monitored manually to ensure the navigation path and provide remote support and trouble shoot for technical issues. 

Results

1. Efficiency Improvements

  • Shelf audits which used to take several hours were successfully driven down to about half an hour per store.
  • Setting decreased labor costs related to manual audits cut the need and time spent on such actions by 40%, making staff dedicate more time to customer service and sales.

2. Accuracy Gains

  • Increased inventory accuracy from 85% to 98%; this reduces incidences of stock outs and overstocking.
  • The robots, for example, noticed misplacements on the shelves that the human auditors could not, and therefore improved shelf arrangement was achieved.

3. Customer Insights

  • Data analysis synthesized the customer shopping behaviors that enhanced promotional strategies and product merchandizing.
  • From the store managers’ feedback, there was increased customer satisfaction because of increased stock availability.

Challenges

 1. Technical issues - Several emerging problems were noted within the pilot phase: Some of the robots that were deployed initially faced challenges of Navigation when in congested aisles. It was adapted to have remote robot monitoring and navigation and our team members were trained to control robots remotely. 

 2. SKU Identification - It is not usual to have identification of all the SKUs by Robots. There are cases where correctly tiled product is incorrectly detected as SKU. Due to it we mobilized a team to Quality check the data on a real time and annotate where ever necessary. 

Future Directions

The positive results of the pilot study therefore motivated the use of the robotic system in all stores in the chain.

  • Integrating artificial intelligence into the robots for purposes of analytics and prognostics.
  • Stock replenishment through deploying of drones.
  • Carrying on customer access aspects that enable robotic support to the consumers.

Conclusion

Robotic monitoring of shelves for audits in the shop has been very impactful inventions in managing inventories. Not only do these robots increase the organizational throughput improving operational costs but they also facilitate a more optimum customer experience. As we move forward technology wise, the possibilities for more developments on the retail automation systems is highly possible opening up doors for a better retail experience all over the world.

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