In our recent article, we discussed how technology is changing the way operational auditing is conducted, transforming the concept from post-hoc reporting to a real-time, continuous and predictive capability.
Today, we look at how digital capabilities can help to not only collect data with greater efficiency and accuracy but to also use it to identify and prevent lost sales and non-compliance in-store.
From descriptive to predictive and prescriptive analytics
Retailers have access to an abundance of data from multiple sources – POS and inventory systems, e-commerce, footfall tracking, online reviews and social media mentions to name a few. Traditionally, retailers have used descriptive analytics (often represented in complex dashboards) to get an overview of KPIs such as transactional history, inventory changes, promotional success, abandoned baskets etc. Descriptive analytics have been useful for improving visibility but have done so in hindsight. In contrast, predictive and prescriptive analytics, using optimisation and simulation algorithms, enable retailers to anticipate trends and issues and offer recommended actions to pre-empt losses and maximise store execution.
This is the difference between a retailer
i) merely knowing that they have been selling 1,000 meal deals every day between 12:00pm - 1:00pm (descriptive analytics with no feedback loop with store level execution)
ii) identifying a higher risk of out of stocks at 12:30pm (predictive analytics) and prompting store associates to re-stock shelves half an hour before noon to prevent stock-outs (prescriptive analytics with a feedback loop to store level execution).
From paper checklists to image recognition
To ensure on-shelf availability, correct placement and pricing – known as planogram compliance – retailers need to regularly audit shelves. Traditionally, planogram compliance audits have been performed with pen and paper checklists which, even if digitized, can be time consuming and prone to inaccuracies due to human error. Image recognition offers a quicker and simpler alternative– store associates simply take a picture of the shelves, which is then digitally analysed. Store associates instantly receive a report on KPIs like missing and present SKUs, price checks and share of shelf and can take immediate corrective action.
In another instance, Tesco’s ‘broccoli cameras’ – cameras placed over the fruit and vegetables section in-store - take pictures of the crates and send re-stock alerts to store associates when they identify low stock. Cameras can also be placed on the inside of fridge doors, taking an image of the shelves every time the door is closed, pushing re-stock alerts to store associates to replenish and merchandise shelves .
Smart sensors - devices which take input from the physical environment, process the data and communicate it with other connected devices – can also significantly improve visibility and compliance. For example, a sensor measuring fridge temperature in the fresh meat section can identify deviations from the HACCP standards and send a real-time alert to the store associates’ mobile devices. This way retailers do not rely purely on a daily routine check but can immediately identify and correct non-compliance with a closed real-time feedback loop between technology and store colleague execution. Similarly, motion sensors can identify and record the location and movement of merchandise, store associates and shoppers. This way retailers are provided with inventory and footfall visibility, can identify out- and over-stocks, misplaced merchandise and prevent potential theft before the items leave the store.
Electronic shelf labels
Like image recognition and smart sensors, electronic shelf labels help retailers to monitor and maintain inventory levels and ensure correct pricing by presenting inventory information directly on the displays. This way e-labels draw store associates’ attention to products that need to be replenished or removed from the shelves, reducing the time needed for a manual inventory check. This also helps store associates to lead data-driven conversations with customers and up- and cross-sell. For example, associates can see if an out of stock product is available in the stock room, online or in another store and inform customers on running promotions without leaving their side to go and check in the back office.
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