VENDING SOFTWARE & TELEMETRY


Academic study validates AI-driven vending stock management system


new academic study has examined how AI driven machine-learning techniques can be used to improve stock management and availability in vending operations. The research, co-authored by Broderick’s and Manchester Metropolitan University, has been published by engineering body IEEE and analyses how demand-forecasting models perform when applied to real vending machine sales data. The research confirms the accuracy of the


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Brodericks’s AI-led stock management system, supporting machines designed to be: • Always full • Always clean • Always working • Always online


This reliability is underpinned by a multi-


layered telemetry infrastructure. If internet connectivity ever drops, the machines instantly switch to Bluetooth, ensuring uninterrupted transactions and continuous reporting.


INDEPENDENT SCIENCE Using five months of real sales data from a major Manchester retail destination, the study evaluated several forecasting models including XGBoost, Facebook Prophet, ARIMA and Support Vector Regression.


KEY FINDINGS INCLUDE: • XGBoost delivered the highest accuracy, achieving the lowest mean absolute error (MAE of 8).


• The model outperformed all traditional forecasting approaches.


• Predictive restocking significantly reduces waste and stockouts.


16 | vendinginternational-online.com


• The system adapts intelligently to weekday patterns, public holidays and abnormal sales events.


This research is said to represent the


first academic validations of AI-driven vending operations in the UK and confirms the company’s position at the forefront of technological innovation in the sector. This now ensures the machines are


guaranteed to generate more revenue. They can always stay replenished, remain fully operational and never drop offline, operators and clients consistently 365 days a year. This has impacted clients in the last year by helping them to achieve between 25% and 100% more revenue from their vending solution. This is compared with traditional vending setups built on manual checks, reactive restocking and dated telemetry tools. This uplift is not projected, it is evidenced and now independently verified through the published research.


THE PROBLEM BRODERICK’S AI SOLVES Vending fails for two reasons: machines are empty when customers want to buy, or they’re overfilled with the wrong products that don’t sell. Both of these problems lose clients money. The AI solution solves that problem by knowing what each machine will sell before it runs out. Instead of relying on manual checks or


operator guesswork, the system uses real sales data from Broderick’s machines and applies machine-learning models to predict demand at site level, by product, by day.


THAT MEANS: • The right products are in the machine • In the right quantities • At the right time As a result, machines stay full of what customers actually buy, not what someone hopes they’ll buy.


WITHOUT AI: • Machines run empty between visits • Popular products sell out early • Slow-moving products expire • Operators over- or under-stock • Revenue is lost quietly every day


WITH BRODERICK’S AI: • Stockouts are predicted and prevented • Waste is reduced before it happens • Refill visits are smarter and more efficient • Machines take payments continuously • Revenue increases automatically


STANDARD TELEMETRY • Tells you what’s already happened • Is helpful for reporting • Doesn’t tell you what’s going to happen next


John


Broderick, managing director, Broderick Group said: “We’ve always believed in doing everything


right, not because it’s easy, but because our customers deserve a service they can rely on. This research independently verifies the technology and dedication behind every Broderick’s machine. Our clients benefit from fuller machines, happier customers and significantly increased revenue.”


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