Data and AI: benefits for the Fleet Manager
Mike Branch, VP Data and Analytics at Geotab started his expose with this essential question: “What is AI”. Simply put, AI is the ability for a computer to learn and think, essentially to make predictions. He gave the example of Amazon, who registered its predictive shipping tools a while ago: instead of “shop, then ship”, Amazon’s intelligence allows the company now to adopt a new modle: “ship, then shop”, where the e-commerce giant predicts what consumers are going to buy.
When is AI useful?
Leveraging AI is key when the amount of data is big and the need for analysis important: for a company such as Geotab, that is one of the biggest data processors across the world, data is key to help clients to deal with driver safety, increase employee efficiency, assess vehicle health and understand customers.
Mike shared an example: the delivery point of a client might not be exactly where map applications tell delivery drivers it is located. AI will learn from behaviour: when some delivery people have figured out the correct delivery, the software will learn from this and make it available for future users. Predictive maintenance is another example of what AI can mean for the fleet industry.
Data, Talent and Culture
Mike shared with the audience some insights about Geotab’s organisation and the specifics of AI projects; he was the first to admit that AI projects can be more complex and time consuming, but will eventually change the way we will manage fleets: fuel, charging, downtime and fleet optimisation can work so much better using the correct technology.
As Mike put it: “You don’t have to be an AI expert, but you need to understand what it can do for you!”