AI-powered stock tracking
How might we use AI to capture the stock level of people’s household goods and predict when they need replenishment?
You can watch the recording of the Kickoff here.
Why Stock Tracking Matters
To illustrate digital stock for personal households, we can think of a warehouse as an analogy. The main processes in a warehouse are storing, replenishment and consumption. The same steps are happening at home – storage of products in drawers, replenishment through shopping and consumption by cooking meals, for instance.
Tracking the inventory provides information about what is in stock to save time and money, reduce food waste and prevent oneself from running out of essential products. Tracking must be as simple and convenient as possible to ensure user acceptance.
Keeping track of personal household stock is an increasing challenge in consumers’ everyday lives. Many of us are familiar with the problem of missing essentials because we forgot to restock on time. While there are numerous apps for digital stock management, most of them are silo solutions and do not serve the customer journey end-to-end.
kiip platform illustration (Partner examples are illustrative only)
Data as an Enabler of Stock Tracking
Digital technologies, such as the Internet of Things (IoT), big data, and data analytics, are essential enablers of stock tracking. Technology has the potential to overcome the barrier of a lack of information transfer across value chains.
The lack of information transfer is an evident problem in our consumption systems. Data about household stock is siloed, not standardized, not exchanged, and not integrated across the shop-stock-consume journey. Food waste or running out of home essentials often relates to this lack of information transfer. Currently, the information about what we buy remains with retailers. At the storage step, stock data is neither tracked nor integrated with retailers or appliances. And consumption data is not transferred from consumers to retailers.
What if you always knew what you have in your pantry from anywhere and anytime with a digital stock? What if there is a solution that reminds you when to restock your home essentials like washing detergents, toilet paper or oats? What if this happens automatically and solely based on your actual consumption?
AI Revolutionizing Stock Tracking
With advancements in AI and data analytics, traditional methods of inventory tracking and restocking methods are being replaced with more efficient and accurate AI-powered solutions. Using AI, stock data can be seamlessly collected and analyzed in real time.
On the one hand, smart devices can monitor the availability of products and track consumption patterns. These devices communicate with an AI system, which aggregates and analyzes the data to provide valuable insights. On the other hand, AI algorithms can predict future consumption patterns based on historical data, considering individual factors like seasonality, special occasions, and personal preferences. By continuously learning from user behavior, AI systems become better at accurately forecasting stock requirements, reducing the likelihood of running out of essential items.
About kiip
Our mission at kiip is to provide households with a consumption-based replenishment of their favorite home essentials. We want to make consumers’ everyday life easier so that they have more time for important things. With our service, we make sure that your favorite products never run out.
The shop-stock-consume cycle consists of the supply side enabled by various suppliers (retailers, D2C brands, etc.). The demand side includes IoT providers and producers who can monitor and track stock levels. And lastly, the consume side describes 3rd party applications that support end users in their consumption (for instance, recipe providers).
The kiip marketplace will combine demand (stock data) and supply (retailer). By linking both, we enable the customer journey to be served holistically. Connecting partners along the shop-consume-stock journey will make relevant data available to all stakeholders and catalyze product and service optimization. Specifically, our partners benefit by unlocking a new customer base, gaining visibility, exploiting synergies and an overall enhanced understanding of consumer behavior.
The Challenge
Your challenge is finding a solution powered by AI technology to enable accurate predictions of replenishment cycles for individual consumers.
How might we use AI to capture the stock level of people’s household goods and predict when they need replenishment?
To imagine new solutions, look at the services you already use around your Shop-Stock-Consume Cycle. What data can you collect to make predictions? How can you access the data? What data do you need to create an algorithm for accurate predictions? How can the demand and supply sides communicate to transfer data? How can we make stock tracking fun and simple for end-consumers? How might smart appliances integrate stock tracking and how can we make this data accessible?
Your ideas
We encourage you to design a prototype that creates value for end-users and potential demand and supply-side partners. Let’s create new and better ways to track stock and enable stock-based replenishment using AI. Sketch the user experience to show how your solution will work. Come up with creative ways to use data to solve the problem of stock tracking and replenishment predictions. Think about the business model of your idea. Adopt a system approach where the role and benefits of the actors involved are specified.
Create your AI-powered, consumption-based replenishment idea to contribute to the twin transition that our world needs: The simultaneous digitalization and sustainability transformation that can improve our economy and society.
Collaboration incentives
As a participant in the AI-powered Stock Tracking challenge, you will have the exciting opportunity to collaborate closely with industry experts and the kiip team. You’ll receive expert guidance, expand your network, and open doors to future career opportunities. Additionally, the best team is invited to participate in a follow-up workshop to refine your solution in collaboration with the kiip team.