The evolution of planogram (POG) automation & compliance solutions

We have seen intense hi-tech innovation in retail store planogram compliance in the last few years. The National Association of Retail Marketing estimated that planograms, on average, go out of compliance at the rate of 10% per week. According to RIS News, lack of compliance and poor retail execution can result in lost sales in the range of $1M to $30M for every retailer in the US. We are now starting to see an evolution in planogram automation and compliance solutions.

For planogram planning and design solutions, it started from virtual planogram designs in 2D and 3D, to data driven optimization of shelf product placements based on sales forecasts, to virtual reality-based planogram design solutions. When it comes to planogram compliance solutions, it began with image processing based solutions for ensuring shelf planogram compliance, to more advanced computer vision and deep learning based shelf scanning solutions to detect products at near 100% accuracy. These artificial intelligence (AI) algorithms are able to address various complexities such as multiple facings of products, varying light intensity, packaging variations, and multiple shapes & sizes of SKUs.

In fact, some latest innovations not only detect faulty planograms, but also provide likely causes such as shelf issue, supply chain issue and theft, and recommend corrective actions such as shelf replenishment, correcting stock locations, etc.

However, there is a huge potential for improving operational efficiency by tapping into cross-functional synergies. In this paper, we have given examples of some synergies that can be achieved with planogram compliance and discussed a framework for designing a successful shelf monitoring solution. Finally, we have illustrated how this framework can be adopted differently across retail segments, based on business strategy.

Synergies that can be exploited

Imagine a store associate scanning a shelf fixture in augmented reality (AR) and not only being able to detect misplaced items, but also identify online orders yet to be picked by his fellow associates, that cause fulfillment delays. Here’s an illustration of a prototype (Figure 2) that we demonstrated for NRF2020.

Figure 2: Illustration of a prototype we demonstrated at NRF2020

Operational synergies can result from combining “hidden” tasks with “visible” tasks and triggering real time alerts. This can be explained in two steps –

1. Detecting “hidden tasks” with “visible tasks” simultaneously
   “Hidden tasks” refer to planogram compliance related tasks that are not executed through any mobile device. This requires manual shelf monitoring such as correcting SKU facings on the shelf, relocating misplaced SKUs to the correct shelf locations, restocking vacant shelves, identifying shelf space gaps due to missing SKUs, etc.
   “Visible tasks” comprise of operational tasks tracked through the ERP systems or tasks executed through mobile devices. Discovering pending operational tasks can bring synergy on scanning a non-compliant shelf. For instance,
   • Discover ageing online orders waiting to be picked and notify associates to prioritize those orders. Moreover, if items reserved for such orders are low in stock, there’s a chance of stock running out if shoppers get there before associates do, leading to order cancellation    
   • Identify items with outdated prices to avoid missing out on promotional sale opportunities
2.  Real time alerts to uplift associate productivity
   Once these tasks are detected, real time alerts can be triggered and integrated with a task management platform to reprioritize ageing tasks. Store associates often use a task management platform to monitor tasks such as online order picking, stock receiving schedules, shifts for managing check-out counters, customer service desks, etc.

Decision framework for designing a smart integrated shelf monitoring solution

Implementing a successful shelf monitoring solution requires many complex decisions depending on the retail segment, business strategy, organization’s willingness to change, and the state of technology maturity. A four-pillar framework can ensure a successful shelf monitoring program – 

1. 4Ws – What, Where, Why, Who
   • What: What tasks need to be monitored at the shelf?
     E.g. – Empty shelf replenishment, restoring location of misplaced items, BOPIS orders (Buy Online Pickup in Store) waiting to be picked up, and items with outdated prices
   • Where: Where are we monitoring – which store, aisle sections and categories?
     E.g. – It is best to start a pilot with your busiest aisles stocking fast moving items such as cereals, beverages, ready to eat, etc.
   • Why: Why are we monitoring these tasks - what are the benefits?
     E.g. - There are high chances your associates are making multiple trips to the shelf per day to fix a planogram. In a single trip, detecting non-planogram tasks that are ageing, such as BOPIS orders awaiting picking, can improve operational throughput
   • Who: Who will monitor – associate, floor supervisor, deputy or store manager?
     E.g. – A floor supervisor may just need to monitor shelves in periodic hours and notify associates, whereas an associate will need to execute the task himself
2. How? User journey & business process
   How should the business user monitor the shelf? Should we remotely monitor from a back room or should we focus on mobility, and conduct patrol rounds? For an effective solution we need to look at both the user journey and the business process. Associates or floor supervisors can be equipped with smart mobile apps for detecting shelf compliance issues, and triggering notifications or alerts to an integrated task management system.
3. Choice of technology to accurately handle the complexities: Choice of technology is very crucial because of the complexities involved in accurately detecting products and their shelf locations from images. The complexities that pose challenges in object detection from shelf images include –
   • Varied size and shapes of products
   • Multiple facings of a SKU
   • Varying light intensities on the packaging surface
   • Packaging variations for the same SKU
   • SKUs appearing at the corner of an image
   • Image distortions impacting quality

Computer vision combined with deep reinforcement learning has proven very effective in successful detection of SKUs and their shelf locations from images amidst these complexities. Artificial intelligence (AI) has elevated detection accuracy to almost 100% in certain cases (E.g. Symphony Retail), compared to 80% accuracy observed with image processing techniques. With computer vision, it’s possible to detect the objects and their locations from a shelf image with a reasonable amount of precision. When these computer vision models are further enriched by data annotation, deep learning and OCR (Optical Character Recognition), the precision and confidence of object detection amplify tremendously. In addition, reinforcement learning can improve accuracy even further by giving associates a chance to provide a feedback if the object was correctly detected or not, and then the AI self-learns from the feedback.

With compliance done right with AI, retailers can consider stepping up associate experience even further by incorporating augmented reality that can overlay virtual instructions for associates on the physical shelf when they turn on the camera of the mobile device. We demonstrated an AR based associate experience at NRF2020 for guided shelf monitoring, as cited in Figure 2.

4. User adoption policy: Driving user adoption is a daunting challenge for large retailers with footprints of over 1,000 stores and more than 50,000 associates. It’s a matter of proactively grabbing a tablet, doing a floor round to detect shelf anomalies. Gamification and AR can play a big role in incentivizing associates. Imagine an associate getting rewards for detecting shelf anomalies such as misplaced items. AR based wayfinding for reaching the right shelf brings a lot of fun to mundane store operations.

Role of retail segment and business strategy

The industry segment and business strategy play a great role in how this solution can be customized for different retailers. Imagine a consumer electronics retailer who has invested large space in experience zones within their stores. Such stores usually have a dedicated backroom holding inventory for online orders. Hence, an associate would only require alerts of misplaced items or empty shelves on the experience zone. Following the “4W” element of the framework, online order picking would not be a relevant task that needs to be integrated to the solution.

Let’s take a different example – a grocery retailer for whom convenience and operational efficiency are critical. The same shelf fixtures would have products on display as well as products allocated to online orders. Hence, online order picking is a relevant task that needs to be monitored so that the right associates can be notified through an alert.

Getting started

To get started with a successful shelf monitoring program, retailers need to look at the final and most important piece of the puzzle – a partnership. The success of this program depends on best practices from multiple fields like visual merchandising, artificial intelligence, process design, complex system integrations, and associate empowerment. The right culture can be cultivated by having a cross-functional talent pool comprising of store managers, business leadership, product managers, retail functional consultants, AI engineers, and system architects. After all, great successful hi-tech business solutions require tremendous depth of industry experience, functional and technical expertise. Only partnerships can bring such expertise under one roof.

References:

Sources for market statistics

https://blog.myagi.com/63-statistics-that-prove-brands-benefit-from-investing-in-retailer-collaboration-tools/

https://www.naturalinsight.com/retail-dictionary/planogram-compliance#:~:text=Improving%20Planogram%20Compliance%20Is%20a%20Major%20Challenge&text=RIS%20estimate%20that%20lack%20of,every%20year%20across%20the%20industry

Sources for market solutions and state of market in planograms, planogram automation & planogram compliance

Medium - https://medium.com/@popprobe/planogram-compliance-the-key-to-retail-success-in-the-2020s-930e2a45fc41

Hive - https://thehive.ai/hive-planogram

Symphony Retail - https://www.youtube.com/watch?v=x63djpVyHtU

Wipro at NRF - https://www.youtube.com/watch?v=5VXhMI3aGQM&t=16s

Prithwijit Mukherjee

Principal Consultant, Wipro 

Prithwijit Mukherjee is a Principal Consultant focused on solving business problems for omni-channel retailers and online brands through frameworks and solution offerings on ecommerce, store operations, customer360 & personalization, AI, & ML. He has successfully delivered solutions to clients, built MVPs for trade shows such as NRF (National Retail Federation) and developed assets spanning across customer experience, retail store operations, inventory optimization, and returns management. Prior to Wipro, he pursued an MBA from IIM Calcutta focused on supply chain, marketing analytics and business data mining.