Drug manufacturer uses Goods Checker to promptly analyze KPIs for product visibility and employee performance

KPI analysis for brand exposure for a drug manufacturer

Business Challenge

Customer

The customer produces medicines and sells them in Kazakhstan, Uzbekistan and Kyrgyzstan. The customer needs to monitor compliance with planograms and representation of its products in 8,800 pharmacies. Previously, the process was manual: the customer’s medical representatives laid out the goods, took photos of the display and sent them to managers. Managers manually checked the layout for compliance with the planogram. This approach was associated with errors, for example due to fatigue.

The lack of detailed reporting on planogram compliance and the use of inappropriate tools for the task, such as Microsoft Excel and Microsoft Powerpoint, made the process more complicated and could not guarantee effective monitoring of goods display.

Challenge

  1. Automate monitoring of display and POS materials.
  2. Configure a BI system to obtain prompt analytics on compliance with planograms with various breakdowns

Solution

During the pilot project, the customer’s employees used Goods Checker in 1,500 pharmacies and for 46 articles. Goods Checker consists of a back-end, a mobile application for medical representatives and a web application for managers.

Mobile application for medical representatives

Medical representatives use the Goods Checker mobile app on iOS. 

Now, after the customer’s employees have displayed the goods, they take photos of the display. The application processes the image and shows the results – it tags correctly and incorrectly displayed products, required and missing items. When processing photos, Goods Checker combines all images into a planogram and calculates KPI for all photos taken.

The solution does not allow employees to upload photos from the device’s gallery, so only relevant information is included in the analytics. Goods Checker also saves visit history with photos and results so that the manager can fairly evaluate the performance of the medical representative.

The application is able to run offline and show results after connecting the device to the Internet, so the customer’s employees can work anywhere in the city.  

Web application for managers

A web application with analytics is available for managers, where the results of visits by medical representatives are shown in the BI system no later than an hour after the visit is completed. Using Goods Checker, the customer automatically receives data on compliance with planograms, availability of POS materials and compliance with merchandising standards. All data can be viewed with breakdown by medical representatives, chains, brands, etc. 

Resources provided by the customer

  • renderings of SKUs/POSM,
  • photos of layouts for training neural networks,
  • planogram and MSL templates,
  • list and description of retail outlets. 

Difficulties

The customer has a non-standard process for visiting the pharmacy, so we modified the Goods Checker iOS application to accommodate this. In addition, the time difference with the customer is five hours. Despite this, the customer’s and Goods Checker teams promptly resolved any outstanding issues. 

Highlights

143

SKUs

8 800

retail outlets

100+

users

<5

up to 5 minutes visit time

Result

During the month of the pilot project, Goods Checker demonstrated the required recognition accuracy above 90%. In addition, the customer has already noted that the visit time of a medical representative has become shorter and takes no more than five minutes. The customer decided to switch to commercial operation.

For this purpose, the Goods Checker team updated the system by adding new SKUs, users and pharmacies, and also improved the BI system to collect more detailed analytics. Later we trained the system for all SKUs in Uzbekistan. Now Goods Checker is preparing to launch in Kyrgyzstan. 

With Goods Checker, client’s managers quickly analyze all the necessary indicators and make management decisions based on effective and complete data.

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