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Dan Sturman on category management in a world of constant change
Jan 19, 2021 | By
What you will learn from this podcast: • What next-generation shoppers are looking for on the supermarket and grocery store shelves. Dan advises on how category management should prepare for this change. • How can category management professionals get better at predicting in a world of constant change? Dan sheds light on the shopper behavior during the Super Bowl. What happens if there are no games or the game happens at a different scheduled date and time? What alternative product categories will be impacted and need to be considered? How does this impact no social gathering and tailgating at the football game? What other "stay-at-home" products will be demanded instead? How does it impact food spoilage? Dan answers all of these questions. • How companies prepare for key events, competition moves, and retail reaction. Hint: "war games" scenarios. Is there a way to see the impact of each scenario? As a side note, HIVERY Curate can allow users to easy model these scenarios in the AI engine to present the impact at category, SKU or brand levels or by distribution such as by cluster store or store-specific levels. • Dan shares useful tactics and insights on how CPG manufactures and retailers can enhance shopper expectations and maintain retailer relationships. Dan talks through a fascinating story about how intelligence on shoppers can transform your sales. Make sure you listen to the "Target store and sales of multi-serve meals" story. • How CPGs and retailers can address the "The Paradox of Choice" and why sometimes less is actually more. • How data science can help with better predictions by looking at the relationship with seasonal events such as hurricane season and impact on category assortment. • How forecasting is currently done. Generally, there are several different business groups involved. It all starts with the account team who are closest to the customer. They factor in key events such as promotions and allow other internal teams (i.e. demand planning and supply chain) to add their view. This can be a very intense and time consuming process but generally works well until an event that has not been planned occurs. Responding to change can be an extreme challenge. As a side note again, HIVERY Curate helps. Rapid scenario planning can be conducted to quickly inform new strategy and articulate it to all stakeholder groups. • Dan finally covers what he believes the future of category management is. With the increase in online purchasing, Dan talks to us about the need to have an optimized omnichannel strategy. While shopper convenience (i.e. delivery, in-store pick-up, curbside pick-up) and choice are good, it leads to additional costs. Dan shares a few real examples (Walmart, Kroger) and discusses best practices.Read More >
Mark Lawrenson on the science of optimization methods and solving real-world problems more optimally
Jan 05, 2021
What you will learn from this podcast: • When optimization or applied mathematics was first used to solve real-world problems. We go back to 1947 and George B. Dantzig, when not only the first computer program was written but also new applied mathematics methods were invented, now called linear programming. • The fascinating world of Applied Mathematics. Mark breaks down everything from Operations Research, Linear Programming (using 1 and 0.5 as inputs), Complete Methods (solving problems optimally), Heuristic Methods (solving problems faster although not always optimally), and Genetic Algorithms (inspired by nature's way of optimizing) to relatively modern methods like Integer Linear Programming (using 0, 1 or 2 as inputs). These methods have previously advanced the military to optimize the distribution of weaponry. Now, these methods are used by commercial industries and have found their way into category management to ensure the right products are in the right, specific shelf space at the right, specific store. • Mark goes deep into explaining his fascinating research: "A model-based genetic algorithm framework for constrained optimisation problems"; and his new framework that solves real-world problems differently and more efficiently. • Why HIVERY Curate (formally HIVERY Propel) is different to any other planogram category management optimization solution out there. Marks explains how he has applied and combined optimization techniques (i.e. how much of product X to put on that specific shelf in that specific store) with machine learning methods (what product to put (X or Y or Z) on that specific shelf in that specific store) along with the secret ingredient; the constraints that make HIVERY Curate category recommendations realistic and implementable at a store-level. • If you are interested in learning about how our world can be run more efficiently, love maths and solving real problems. This is a must-listen. Resources: www.linkedin.com/in/mark-lawrenson/ dl.acm.org/doi/10.1145/3067695.3076041 https://news.stanford.edu/news/2005/may25/dantzigobit-052505.html
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Dec 23, 2020 | By
実証実験では最大50％※以上の売上増加も！全体では5.27％※の増加を記録！！ 飲料補充の効率化で、業界の働き方改革も実現！ ※近似環境でAIシステムを使用しなかった自販機との同一期間比較 ... learn more
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Hivery, an Australia based artificial intelligence provider, will roll out its AI driven vending machine management solution to 6,000 machines across East Japan Railway's train stations, according to a press release.
Dec 17, 2020 | By
The two companies have been collaborating since 2017, leveraging Hivery's AI technology to optimize product assortment and column space for individual vending machines in Japan. Validated results from proof of concepts increased sales by 5.27％overall, up to a maximum of more than 50%, as well as reducing replenishment trips and improving operational productivity... learn more
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Australian AI startup, HIVERY, partners with JR East Water Business to optimize vending machines in Japan.
Dec 09, 2020 | By
Retail AI pioneer, HIVERY (headquartered in Sydney, Australia) and JR East Water Business (headquartered in Tokyo, Japan), a subsidiary of East Japan Railway Company, have agreed to rollout HIVERY Enhance - an AI-driven vending machine optimization solution, to 6,000 vending machines across East Japan Railway’s train stations. Validated results from numerous PoCs (proof of concepts) increased sales by 5.27％  overall, up to a maximum of over 50%, as well as simultaneously reducing replenishment trips and improving operational productivity. HIVERY and JR East Water Business have been collaborating since 2017, leveraging HIVERY’s latest AI technology to optimize product assortment and column space for individual vending machines in Japan. During the winter of 2019, the results of HIVERY Enhance showed an overall increase in sales volume by 5.27%, up to a maximum of over 50%. Furthermore, given labor storages due to a declining population, there has been growing pressure to improve operational productivity within the Japanese vending industry. HIVERY Enhance enabled JR East Water Business to streamline operations and reduce replenishment trips by automatically recommending the optimal product assortment and quantity for their vending machines. Based on this success, JR East Water Business has agreed to rollout HIVERY Enhance across 6,000 vending machines on their train stations for East Japan Railway - a first in Japan. Until now, product assortment selection had been decided by individual operators (drivers) who are responsible for replenishing the vending machines at their designated locations. Given those decisions have been based on the operator’s accumulated experience and intuition over many years, it has been an ongoing challenge to transfer that knowledge to new operators and maintain a level of quality. HIVERY Enhance leverages the power of AI and JR East Water Business’ point of sales (POS) data, to automatically determine which products need to be stocked in which vending machine, as well as the optimal timing to swap products for individual machines. This enables any operator to efficiently make the right product assortment choices that will lead to a profitable outcome. HIVERY Enhance helps to: Select products that are likely to sell well – By analyzing the vast amount of sales data from the full fleet of vending machines, it identifies patterns in the sales data and identifies products that are likely to sell well in any particular location. Optimize product assortment - By understanding the demand for individual products and the effects of cannibalization of demand between products in each location, it can determine which products should be inserted and which should be taken out, to lead to the optimal outcome. Reduce replenishment trips - From the demand forecasts of products in any location, it can calculate the number of days before each product is likely to go out of stock and recommend the optimal quantity and column allocation to maximize the time between replenishment trips, thereby reducing labor costs. Optimizing a group of vending machines - Rather than only focusing on individual vending machines, it can also assess a group of banked vending machines in the same area at the same time, and optimize the products for the entire area as if it were one large vending machine. By ingesting vast arrays of data and incorporating intricate operational rules as well as physical and business constraints into its algorithm, HIVERY Enhance can instantaneously provide executable recommendations for the optimal product assortment and column configurations for both an individual as well as a group of vending machines. Furthermore, by leveraging weather data, it can respond to changes in seasonal patterns and suggest the optimal time to insert hot and cold products, while taking into account the effects of cannibalization for the product mix at each location, thereby providing the optimal product assortment at any given time. Voice of the customer: In March 2018, HIVERY invited JR East Water Business’s Vending Division team to its Sydney headquarters to meet with one of HIVERY's first customers, Coca-Cola Amatil, to exchange ideas and share their experience and best practice for implementing cutting edge technology for their respective vending businesses. “We believe the combination of the rich human experience of our operators cultivated over many years and the utilization of big data is our greatest strength. With HIVERY Enhance, we can realise that vision, and we aim to establish a new platform for our vending machine operations that will help us recover from the impact of this year’s pandemic, as well as improve worker productivity which has been an issue for us for many years.” ~ Yuta Higashino, Manager at JR East Water Business Moving into category management: the $US900 billion opportunity. HIVERY Enhance is just the beginning. HIVERY has released its new offering - HIVERY Curate - The world’s first truly hyper-local category management solution, helping companies like Coca-Cola and Walmart transform category management. HIVERY Curate delivers store-level recommendations with sophisticated self-learning AI algorithms that discover buying patterns at each store and make product assortment and space recommendations from this, resulting in a 10X return on investment to date. About HIVERY HIVERY is a multi-award-winning pioneer of hyper-local retailing, combining Artificial Intelligence (AI), operations research, and human-centered design to help Consumer Packaged Goods (CPG) manufacturers and retailers generate a return on physical space investments. HIVERY is transforming category management and retail trade promotion, with innovative algorithms sourced from Australia's national science agency - CSIRO's Data61. HIVERY is venture-backed and headquartered in Sydney, Australia, with offices in the USA and Japan. HIVERY was founded on the vision that Data Has A Better Idea[TM] - and we’re working together with our clients to uncover its full potential. Innovation Leaders Summit Tokyo (ILS) 3rd~12th March 2021 HIVERY has been selected by Austrade (The Australian Trade and Investment Commission) and the NSW Government of Australia, as one of 2 promising startups to participate in next year’s Innovation Leaders’ Summit. Details of the event can be found here: https://ils.tokyo/ For Media contacts: HIVERY Japan K.K. Country Director Hideaki Yoshimura email@example.com HIVERY media release English version Japanese version JR East Water Business Co media release Japanese version only Footnotes:  Compared to vending machines not leveraging HIVERY Enhance during the same period.  “Out of Stocks, Out of Luck How Retailers Alienate Customers and Lose Billions Due to Poor Inventory Practices” IHL Group 2018, G. Buzek
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Zach Simpson on shifts in category management, artificial intelligence and making career changes
Nov 19, 2020
What you will learn from this podcast: • Zach's career journey from baseball to Walmart to his own company and HIVERY. Zach shares his insights into the lack of advancement of retail technology during this journey in category management. • Zach explores the "snowflake" effect of product categories and space; how each store is so different (as a snowflake), yet when it comes to space assortment, the retail industry continues treating each store and their SKU supply the same. • Why Zach, after over 11 years at Walmart with titles like Frozen Food Senior Buyer, Merchandising Director, and VP of Beverages Merchandising decided to "jump ship" to HIVERY, a young AI startup? • Zach provides a sneak preview of product innovation at HIVERY; and how customers play a critical role in this process. •. Zach dives into key problem sets faced by a wide retail segment from wholesale networks to traditional grocery stores in space, assortment, and category scenario planning. • Lastly, Zach gives career advice and shares his insights into personal and professional development, innovating from within and facilitating change.
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Why Food Retailers Need To Embrace AI
Nov 08, 2020
Why Food Retailers Need To Embrace AI? In this Lost in the Supermarket episode, Phil Lempert talks with Jason Hosking, CEO & Co-Founder of HIVERY, The worlds first category management optimization solution.
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Tim Rowland on retail robotics and the future of senses
Nov 04, 2020
What you will learn from this podcast: • Why getting the right product at the right price and in the right amount is becoming more and more difficult for both CPG manufacturers and retailers. Listen to how Badger Technologies and robotics are solving this through "seeing". • Tim explores the concept of "hidden products" - products that are not "shown" in the correct manner on shelves - as well as "hidden price promotions". Promotions are often delayed due to the slow process of getting the actual new sales tag on the shelf or the reverse, with sale promotion tags hung for too long and appearing out of date. With robotic technologies like Badger, old challenges can be addressed effectively. • How robotics can not only assess the status of products on the shelf and price promotion compliance but also help grocery stores, supermarkets and hypermarkets assess floors for spills and hazardous conditions. This helps both shoppers and retail staff encouraging visits and ensuring stores are both clean and safe. • More interestingly, some larger supermarkets and discount stores are using robotics to assess promotional display compliance in aisles ensuring that every marketing dollar is spent accordingly. Display compliance gives CPG manufacturers an "eye" on what is happening in-store and potentially issues contractual penalties for retailers' non-compliance. • Tim also covers the challenges in having robots in supermarket stores and implications of human traffic and their advantages: an ability to scan 40,000 individual store products, responding to hazardous conditions, promotional compliance - all in around 3 hours! • Will robots replace supermarket workers? Tim shares his views on robots and the human labour force; you will be surprised with his insight. • We close with a fascinating view of future robotics in retail stores. Can robots sense "freshness" and ensure our fresh fruit, vegetables and dairy are about to expire?
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Future of retail, category management and AI (video)
Oct 30, 2020 | By
Expert food industry analyst and journalist, Phil Lempert, has a candid conversation with HIVERY's CEO, Jason Hosking, on future of retail, category management and AI. Watch this episode of Lost in the Supermarket... watch video
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