![]() ![]() They have also partnered with Flirtey, a drone delivery service, to test out a drone delivery program. Īdditionally, the company has struck a partnership with Nuro to deploy self-driving delivery vehicles (currently testing in Houston). It hopes to bolster in-store operations, generate revenue and improve the customer experience by using tools such as forecasting labor, streamlining delivery vehicle routes for efficiency, and better identifying real estate locations for new stores. Strengthening its approach to the delivery market has helped Domino’s to rebuild a tarnished profile, and its stock price had risen 99% in three years.ĭomino’s recently announced its partnership with AI company Datatron to automate, standardize and streamline the deployment, monitoring, management, governance and validation of all of its disparate AI models. Source: Īlong with its financial success, the company ranked above the average limited service restaurant’s ACSI score of 78 in 2020, and analysts say that Domino’s was uniquely positioned to meet consumers’ increased demand thanks to its commitment to innovation over the past several years. Īnd while these technology advancements meant adding significant infrastructure, personnel and R&D investments, the strategy proves to be paying off with Domino’s recognized as the number one pizza retailer in the world (by revenue) year-over-year. These enhanced algorithms improved delivery time accuracy from the previous 75% to 95% accuracy rate by leveraging a load-time model that factors in labor variables such as how many managers and employees are working, the number and complexity of orders in the pipeline, operational factors, and even current traffic conditions to improve the order-ready accuracy rate. Using GPUs, the company was able to train the same algorithm in less than an hour (and continuously retrains it using more data every day). With CPUs, it took three days for Domino’s to train an algorithm to predict when orders would be ready. In 2020, Domino’s AI success pushed them to make a substantial investment in migrating from CPUs to GPUs in order to improve the accuracy rate of predicting when a customer’s pizza would be ready. While the cameras’ adoption was not entirely smooth and skepticism of the technology causing initial doubts in some franchises, the overall project was received quite well and franchisees also added that it created a climate of positive competition, motivating employees to improve the quality of their pizzas. For example, in response to the increased customer attention to health and safety during COVID, a cleanliness-checking feature was added to the camera ensuring the cutting bench was cleaned as often as the company’s standards require.ĭomino’s claims to have witnessed a 14% to 15% improvement in product quality in stores that installed the AI tool. The solution has also found unique value in its ability to quickly add additional features. This shared data allows the head office to check products sold under its brand name, score each store, determine how to allocate training resources effectively, and ultimately reduce the need for auditing. The system sends all logged inputs to Domino’s headquarters. ![]() The DOM Pizza Checker is deployed in 850 stores across Australia and New Zealand and now expanding into the U.S. A thumbnail of the picture is then sent to Domino’s tracker, allowing customers to check their pizza, targeting a growing desire for transparency. The manager can then decide either to agree with the computer, in which case the system will automatically re-log the order, or override it, whereby the system will keep a log but move on to the next pizza. If the pizza has an issue, the checker will alert the manager with a visual pop-up and a sound and display the problem detected. If it does, the system matches the pizza to the appropriate order, displaying it on the screen with a corresponding quality score. The camera captures the image of pizzas placed on the cutting bench and analyses the pizza to make sure it meets Domino’s quality standards. It’s main focus is to review the quality of the pizza before delivery, reducing the “my pizza doesn’t look like it should” complaint rate. It scans for pizza type, correct toppings, topping distribution, and aesthetic appeal. The AI-enabled tool sits in the kitchen, checking pizzas when they come out of the oven. The DOM Pizza Checker uses advanced machine learning, artificial intelligence and sensor technology to identify pizza type, even topping distribution and correct toppings. ![]()
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