Supply chains are incomplete without an effective and efficient route to the customer. Environmental concerns, corporate social awareness, good product conditions, packaging, and on-shelf availability of products — these elements increase competition from the upstream through downstream supply chain, providing the ultimate economic value to customers. Control over supply chains is a determining factor for competitive performance in the Retail sector.
In the Retail industry, optimal shelf availability refers to a retailer’s ability to consistently keep their shelves adequately stocked. As it stands, stores lack access to reliable data and methods of maintaining optimal inventories, nor do they have adequate business strategies in place with manufacturers to properly manage their supply chains.
Another problem is product waste. This occurs along the entire food supply chain and gives rise to great financial losses and waste of natural resources.
On average, the global Retail industry loses roughly $500 billion in annual profits. $100 billion of this is due to simple product waste and mismanagement such as spoiled goods and shipping issues, while $400 billion is a result of product shortages and understocking.
Stock outs, as they’re commonly referred to, create headaches for both retailers and consumers. If consumers can’t find the product they’re looking for, they have no choice but to settle for unwanted alternatives or look elsewhere, leaving retailers to lose potential sales. In some cases, a customer’s future business is also at risk. Overstocking, on the other hand, leads to product waste, an unwelcome outcome for orders that could have been better spent on shipments for understocked goods.
OSA DC stands for creating value for consumers, retailers, and manufacturers with its AI-driven digital services. The company provides a simple and shared business model to lower the financial threshold for implementing an empty shelf control solution for all retailers. The more clients that participate, the more affordable the service becomes.
Retailers can certainly benefit from OSA’s solution for their data systems. For example, stand-alone image recognition services provide in-store product execution monitoring that helps retailers “win at the shelf”. They include a comprehensive, real-time view of their store’s performance across other retail channels. They collect real life shelf pictures via sales reps, which are sent to the cloud for analysis. The sales rep then receives mobile reports while
management teams receive detailed assessments online.
In-store execution precludes other important facets of the supply chain.
Better than mere in-store services, OSA DC enables customers to understand and analyze issues before the product hits the shelves. In addition to image recognition, the supply chain monitoring tool set includes machine learning, statistical algorithms, and neural networks.
Regarding image recognition, synthetic data learning algorithms substantially lower capital and operating expenditures to develop specific IR models. This allows for more comprehensive coverage of most of a store’s assortment and inventory.
This service can provide product/shelf availability data within maximum 1 hour after a problem occurs, while administering proactive alerts for these issues at the latter stages of service development. This feature allows greater involvement in the business execution process to better serve both customers and store owners. The speed of our problem tracking also enables
more nuanced and insightful forecasting.
Data science algorithms process client information relevant to an incident, providing actionable recommendations based on real-time data landscape and a client’s business record. Image recognition and other instruments allows for coverage of all product ranges sold in large retail stores, including slow-moving products.
Using B2C services on a decentralized marketplace, consumers generate a wealth of unique data on shopping patterns, product preferences, pricing influence on purchasing decisions, and more. With consumer consent, this data is used to enrich machine learning algorithms and improve B2B services.
OSA DC enables a fair share approach and rewards consumers for data sharing. Such data is invaluable for enhancing business solutions to develop better products and services for end customers.
In approaching the development of the shopper’s solution framework, OSA DC has focused its concerns around the technological pillars that can solve them.
Product Master Data Catalog
Product Data Catalog is enriched with attributes specific to a product’s performance characteristics. These characteristics can be objective, subjective, relative, or contextual and allow to link a product to the usage experiences of each individual consumer.
For example, consumers or their personal digital assistants can ensure that their chosen product:
Does not contain salt or any other specified ingredient.
2. Has similar product preferences of other shoppers. Taking into account the required weight or volume of the chosen product, personal digital assistants can determine the most efficient logistics.
Dynamic Reputation Rating (Game Logic)
It is nearly impossible to digitize all factors that influence shoppers satisfaction from a purchase. Yet most of these factors are centered around the processes, objectives, and strategies of manufacturers and/or retailers. In some cases, these are indirect subjective evaluations or completely unknown factors.
Attempting to generate this data, OSA DC relies on game theory methodologies. It develops a dynamic ratings system, which is then used to generate additional attributes and features for every product (or manufacturer of consumer goods) and retail store (or retail chain). Ratings can be categorized as global, local, or individual. They can be applied to the specific decision-making or problem-solving process initiated by a shopper or personal digital assistant. OSA DC’s ratings system is immune to tampering.
Using this option, shoppers or their personal digital assistants can choose the required level of expected: 1) service, when selecting the appropriate store or chain; or 2) Product quality/performance, when choosing the specific product.
Personal Digital Assistant (Intelligent Interface)
This group of concerns is addressed with the help of a personal AI-managed Digital Assistant. It is trained by accumulating, analyzing, and processing of a personal shopper’s data, including the purchasing history and shopper’s preferences.
The Personal Digital Assistant is capable of processing available product offers during independently planned purchases, formulating purchasing strategies and deciding on purchases, or supporting the shopper in making his/her purchasing decisions. The Assistant also provides optimal product logistics and delivery. All data is encrypted and released to the Platform or third
parties upon the shopper’s explicit consent or on a need-to- know basis to enable services provision.
How do we organize decisions in the Personal Digital Assistant?
Each of the sections described above is a modular set in the core of the cloud Platform. Together they make up the Core. The Core Platform analyzes shoppers requirements, assesses the modules relevance and applicability, and provides optimum module combinations to best address them.
Modules and services interact on the Platform in a way of micro transactions, fueled by an internal cryptocurrency.
The Platform’s strategy lies in generating maximum affinity and reach, within a minimum time lapse. To achieve this, OSA DC will offer its Platform services for use by other partners. These partners can build digital shopping environments for specific target audiences. This will effectively offer OSA DC’s marketplace to owners of retail stores, brands, sites, mobile apps, or any service that has a constant target audience. This allows them to develop their own digital environments for personalized shopping.
Digital Environment for Personalized Shopping
Based on the customer journey of an identified shopper target group, the key objective of the customer journey is to lead the shopper through the purchasing process. The goal is to result in a successful purchase. This environment consists of platform services, which are used as LEGO modules, to best reconstruct the customer journey.
Each service or module solves a separate problem along the customer journey, ultimately leading to scoring a positive impression from purchase.
OSA DC envisions its Platform using the following services to develop the customer journey:
Profile AI Kit is a set of intelligent user profile generators, based on generated personal data. They manage personal data access, encryption, and cryptocurrency transactions.
Ingredients Data Tracker keeps a blockchain-secured track record of sensor data related to product ingredients provenance.
Delivery Data Tracker registers blockchain-secured sensor data related to product storage, handling conditions along the supply chain to the shop shelf, and during delivery, from the shop to the end consumer.
Storage Data Tracker registers blockchain-secured sensor data related to product storage and handling conditions on the shop shelf, with the ‘best before’ date.
Search, Comparison and Choice AI Kit is a set of instruments for the real-time intelligent product search, comparison and recommendation, which is based on predefined user criteria.
IR & AR Kit recognizes products from photos or captured by mobile camera and accompanies recognized objects with augmented reality elements. It also manages recognition model training.
AR Kit manages and activates augmented reality objects using fixed markers (QR).
VR Kit creates and manages a virtual reality environment.
Logistic Kit interacts between local and global shipment and delivery options, plans routes and timings.
The shopper assigns which data will be used by the Personal Digital Assistant, which data will be available to selected partners and/or global services (ie. global ratings data).
Solutions for this group of problems in based on blockchain ledger registry of manufacturing, transportation, and handling processes for each product. These processes are traced via sets of sensors assigned to every product unit and can easily be retrieved on demand. This allows shoppers or their Personal Digital Assistants to verify that the particular product is fully made up of organic components and was shipped and handled in full adherence to the
OSA DC unites consumers into a single powerful community, giving them the power over both the manufacturers and retailers of consumer goods, so that consumers will be able to tell what products they really want, when, where, and at what prices.