ECR Retail Loss

Enabling the Retail Sector to Sell More and Lose Less

OSA: What if Toyota Managed Retail Replenishment?

The Toyota Production System revolutionised quality management in car manufacturing, establishing Toyota cars as a market leader. Their system that sought to remove waste, such as inventory, was initially inspired by supermarket retailing. In this meeting, attended by over 70 retailers, we posed the question, what would Toyota do to improve retailers replenishment system? A full recap of the discussion with Dr Paul Chapman is below, here though are three takeaways for retailers. #1: They would drain the back room! A recent study on where inventory could be found in the store revealed that just over 21% of the inventory could be found in the back room, which went up to nearly 39% on frozen food. The study also showed that around 12% of the inventory that was in the back room was NOT on the shop floor (NOSF) , this metric rose to 25% with frozen. Anyone who has had the job of filling the frozen category in store will recognise these numbers and the difficult task of finding items missing on the shelf in the back room in a category where the inventory arrives from the DC in brown boxes, where the space in the back room for frozen is limited, dark and cold! Exploring the data more deeply using R2 analysis, there was a very strong relationship identified between the quantity of inventory in the back room and the quantity that was not to be found on the shop floor. Simply put, the more in the back room, the higher the shelf out of stock number. This is not a new finding, a COO from Best Buy made this same observation two decades ago, where his observation was that the items most often out of stock on the shelf, were items that arrived at the store in case quantities that could not all be placed on the shelf, meaning that the excess items needed to go to the back room [never to be found again!] It follows that to fix shelf out of stocks, first, you need to discover the causes of over-stocks in the back room #2: They would prioritise "One Touch" Planogram Designs Toyota have adopted the "just in time" system with a view to reducing inventory in the system. In their system, parts that are needed on the production line are available at the exact time they are required. See video. The retail equivalent would be a system where the shelf would be replenished, with inventory from the Distribution Centre (DC) arriving at the store and then the shelf, at the exact time the last item on the shelf is sold. It is clear that retail is significantly more complex than a car factory, for example, a big retail store will carry up to 30,000 stock keeping units (sku's) and unlike the car factory, there are non-paying customers, also known as thieves, who corrupt the accuracy of the inventory records upon which the expensive replenishment systems depend. What we did hear though from a number of retailers was an increased emphasis on "one touch" planogram / modular designs that maximised the percentage of inventory shipped from the DC that could flow straight to the shelf with no excess quantity needing to go go the back room. Retailers adopting these "one touch" and JIT planograms have recognised that to achieve them, there is a requirement to increase cross functional collaboration between functions such as store operations, category management and supply chain. Cross functionally agreed choices need to be made on the speed of the supply chain, the minimum ship quantities and frequency of deliveries to the store. Choices also in the store on shelf capacity and the space that can be allocated to every sku, and acceptable levels of OSA per sku. Where there are competing incentives and rewards per function, retailers will need to explore ways to remove those functional KPI's as barriers to collaboration. There was no sense in the meeting such collaboration was or would be easy, however, what was clear was that to deliver more "one touch" JIT planograms, retailers will need to consider building new capabilities and skills behind a more collaborative approach to planogram design. #3: They would increase the automation of Shelf Replenishment Routines Research from ECR Retail Loss revealed that sixty percent of all the inventory records in a typical store are wrong, that means that the system thinks there are either more or less items per record than was found at the time of the physical count. There are multiple reasons that explain why those records might be mismatched, including master file errors, pick mistakes at the DC, items shipped to the wrong store, or items being stolen or damaged but the system records not updated. Retailers believe that counting errors are also a big contributor. For example, an associate may find a gap on the shelf, see that the system says that there are (say) twelve of these items in the store, the associate then tries but fails to find those twelve and zeroes the inventory on that item to zero to trigger replenishment. But what if those twelve were actually in the store, for example, the items were on a secondary location, and the associate did not find them? In that case, when the audit takes place, the auditor will find twelve more than the system is stating. The feedback from many retailers interviewed in our research is that the more you ask store associates to inspect, count and adjust inventories, inventory record accuracy worsens. So how could retailers increase the automation of the shelf replenishment process? Examples of such technology possibilities include the use of shelf images from drones, robots or fixed cameras could replace the manual gap scanning processes. Then there is the possibility of using data science and smart algorithms to predict, identify and then "auto correct" phantom inventory. And then in the back room, computer vision can help store associates more easily find the items that can flow from the back room and onto the shelf. In our working group, many of the retailers are experimenting with these technology approaches, in a meeting planned for November 19th, retailers are going to share their learnings. Retailers, CPGS and academics can register for this meeting by clicking here. If you are a retailer, CPG or academic, please send me an email at colin@ecrloss.com if you would like to see the recording of the full meeting. In the meantime, in the video below, Dr Paul Chapman, recaps his key takeaways from the meeting.

OSA: Eleven Fresh Ideas to Reduce Shelf Out of Stocks

We are very happy to share the pitches and retailer Q&A's from eleven of the top 30 OSA innovations. Click here for list of the Top 30. We present them in the order of their pitches from the online showcase. We highly encourage you to view each one and / or, view all eleven in the recording at the end of this section VusionGroup - They utilise wireless mini cameras to provide live updates and analytics for optimal shelf stocking in retail environments. Contact: roy.horgan@vusion.com  ImpulseLogic  - They enhance retail availability and performance with a cloud-based platform that optimises the final steps of the supply chain. Contact: alh@impulselogic.com  NomadGo - They automate supply chains using advanced technology to improve inventory management and operational efficiency. Contact: andrewm@nomad-go.com EVERYANGLE  - They use AI-powered CCTV analysis to prevent losses and optimize staff costs in retail environments. Contact: malachy@everyangle.ai  Traxlo   - They provide local gig workers for retail store operations to enhance productivity and reduce costs. Contact: paul@traxlo.com Badger Technologies   - They use autonomous robots in grocery stores to address stock and planogram compliance issues, improving store operations. Contact: William_Santiago@jabil.com Retail Insight   - They offer an inventory management system that uses POS data and machine learning to correct stock inaccuracies in retail stores. Contact: dave.b@retailinsight.io Vispera   - They standardise data collection for retail and suppliers globally through an image recognition-based platform. Contact: d.gentry@vispera.co Simbe   - They provide AI and robotic solutions to retail, significantly reducing pricing errors and improving stock management and order fulfillment times. Contact: brad@simberobotics.com ParallelDots   - They offer real-time retail shelf monitoring using image recognition technology to improve sales productivity and drive sales. Contact: jen@paralleldots.com  Gather AI  - They provide drone-based inventory monitoring solutions to enhance accuracy and productivity in retail warehouse operations. Contact: Charlie.reverte@gather.ai The full showcase is here: 

Self Returns: Removing Friction But at What Risk to Loss?

Returns are a significant cost of doing business online, especially in sectors such as apparel and shoes where returns rates can be 30% plus. Our report in 2018 (click here) highlighted the need for retailers to calculate the TRUE and full cost of returns, proposing a true cost of returns model that retailers could adopt to their business. In a quick survey ahead of this meeting, seventeen retailers shared back their best estimates of the true cost of a return., which they estimated was calculated at €10, with the range between €5 and €25. It follows that to make a profit on some online orders will be challenging given the often low profit margins in retailing. This meeting was set up in response to news stories from USA that Kohls were exploring self-returns, this in fact turned out to be "old news" for while Kohls did have a trial, it was then closed down. However, we still proceeded with the meeting, with two retailers sharing their learnings on self returns, with a focus on the dark side, and the cost of losses associated with this proposition. Below are three key takeaways. #1: Self Returns - A Road Less Travelled. In a pre-meeting survey, the responses from seventeen retailers suggested that for this sample at least, the strategy of self returns was not deemed to be a top priority, in fact, it was eighth on the list of the ten identified strategies. See chart. Clearly there needs to be some caution here, the sample size was small and the respondents were more likely to represent operations and loss prevention, hence perhaps explaining why the reduction of fraud and theft were their top priorities. It could be that the CFO's # priority is increasing returns fees. That said, what was striking from the discussion was that for the grocery sector, self returns via an app had already been implemented by many supermarkets. However, in the fashion and apparel sector, this was less the case and very few retailers had yet looked into prioritising this strategy. However, it became clear that those fashion retailers who were not looking at self returns right now were now going to take the learnings from this meeting back to the business with a view to re-looking at this opportunity. #2: Balancing Act: Improve Shopper Experience Vs Risk of Loss To get the meeting started, we had the two presentations. The first was from a leading supermarket retailer, who tested with shoppers, via an app, a new self returns proposition. The other presentation was from a fashion retailer, who had deployed self returns, offering shoppers the opportunity to skip the customer service queue and to simply place their returns in a "returns box" inside the store. See picture. In the case of the grocery retailer, the returns were limited to products where the company would be unlikely to want them back, for example, fruit, yoghurts, eggs, etc that had been spoiled, crushed, damaged, etc. In the early months of their trial, the level of abuse was low, however over time, the abuse started to creep in, to the point where the proposition was unlikely to be profitable unless and until they were able to implement the right controls to monitor, detect and mitigate the risk of abuse and losses. On the other hand, the fashion retailer shared with the group the huge popularity of the self returns proposition, processing over five million returns per year via self returns, reducing the time and effort involved in returning items for 99.8% of their customers. And while for 0.2% of returns there were some concerns, their business had declared that this level of risk was acceptable with the understanding that the loss prevention team would help monitor and manage this risk of loss for the business. #3: Digital Loss Prevention as an Enabler It is said in many retail business that the Loss Prevention team should really be called something else, maybe the Sales Prevention team, or the Good Productivity Idea blockers, and for these reasons they are often locked out of any conversations on change, for example, self-checkouts. However, what we have observed through this discussion on the self returns proposition is how the Loss Prevention team can be the enablers to change, helping the business deliver profitable change. In the fashion retailer example, the retailer was able to offer shoppers the self returns service only because their loss prevention team had in place good measures to monitor the scale & nature of the risk, an alerting system that helped them very quickly determine losses, and then a clear process for identifying and then recovering their losses. With the other case study, other business priorities and the need to build loss prevention controls have held back their ability to offer their shoppers the self returns proposition. If you are a retailer, CPG or academic, please send me an email at colin@ecrloss.com if you would like to see the recording of the full meeting. In the meantime, in the video below, Professor Adrian Beck recaps his key takeaways from the meeting.

Innovating Upstream Design to Boost On-Shelf Availability

It’s now a little over one week until the showcase finale of our On-Shelf Availability (OSA) Innovation Challenge. These initiatives have the power to tackle some of the stubborn problems in retail today. In this final preview, we will shine a spotlight on innovations in Upstream Design. In the complex world of retail, ensuring that products are available on the shelves when consumers want them is crucial for maintaining customer satisfaction and driving sales. This is particularly challenging in the upstream design of the supply chain. Here several key issues can disrupt the smooth flow of goods. Our judges were looking for smart approaches to these unique upstream design challenges ranging from labour shortages affecting transportation and stocking to inefficient shelf space and packaging use. Each obstacle can have a significant impact on managing retail losses. Standout innovations that impressed our panel of 36 global OSA experts, representing dozens of leading international brands, in the Supply Chain category include: AlgoRetail Subcategory: Planning of hours & replenishment routines AlgoRetail's AI platform optimises inventory and on-shelf availability throughout the product journey, streamlining retail operations for improved profitability and efficiency. Arpalus Subcategory: More sophisticated planogram technologies Arpalus uses AI and AR through a smartphone app to optimise shelf space, ensure product availability, and enhance planogram compliance in retail. Badger Technologies Subcategory: More sophisticated planogram technologies Badger Technologies deploys autonomous robots for real-time shelf scanning and data analytics, enhancing planogram compliance and operational efficiency in grocery retail. Centific Subcategory: Malicious loss Centific integrates advanced security features and real-time analytics to enhance retail safety, deter theft, and optimise operational efficiency. Cognitiwe Subcategory: More sophisticated planogram technologies Cognitiwe uses Predictive Vision AI to optimise fresh food retail by monitoring freshness and stock levels, reducing waste, and enhancing availability. enRetail Subcategory: Planning of hours & replenishment routines enRetail employs AI and camera technology to boost on-shelf availability, enhancing demand forecasting and employee productivity in grocery retail.  EVERYANGLE Subcategory: Malicious loss Everyangle employs Vision AI via CCTV to provide real-time analytics and actionable insights, optimising retail operations and reducing loss efficiently.  Focal OS Subcategory: Planning of hours & replenishment routines Focal OS enhances retail efficiency by automating order-writing, labour scheduling, and inventory management, doubling EBITDA within the first month. Leafio Subcategory: Upstream Safety Stock Settings Leafio leverages AI for predictive analytics in inventory management, enhancing retail efficiency and customer satisfaction with proven global success. Recoshelf Subcategory: More sophisticated planogram technologies Recoshelf enhances retail efficiency with smart cameras and computer vision, ensuring accurate pricing and optimal shelf stocking through continuous monitoring. Yoobic Subcategory: Planning of hours & replenishment routines Yoobic optimises on-shelf availability by streamlining replenishment and ensuring compliance through digitized task management and audits for retail operations. Will any of these be among the ten finalists selected to pitch to our judges? The only way to find out is to sign up for our OSA Innovation Challenge showcase finale on May 22nd

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adidas
albert
asda
auchan
best buy
carrefour
coles
desiqual
dollar general
duracell
esselunga
foot locker
gap
ikea
john lewis
kroger
lidl
lowes
m&s
meijer
nike
p&g
primark
river island
sainsburys
sonae
starbucks
target
tesco
walmart
whole foods

FOCUS AREAS

The research priorities are determined by its members – they drive the agenda to ensure ECR delivers research that meets the need of the industry bringing new insights, tools and techniques that enables retailers to sell more and lose less.