Using Mobile Applications and M2M to Improve Productivity and Enable Business Decisions
One of our recent projects focused on the impact that machine to machine to computing can have in places that we’re all familiar with – the food service industry. Not traditionally a sector that relies heavily on new technology in order to manage day-to-day business tasks such as kitchen inventory or product ordering, the ability for food services to now begin to make use of advances like wireless sensors and cloud integration has been allowing businesses in this space to become more efficient, reduce waste, and streamline their product delivery. We’re making use of machine-to-machine technology, cloud services, and mobile devices to help reps from the Orlando Brewing Company make quick fact-based decisions that help serve their clientele – restaurants and other venues – while they’re on the road.
Many food service reps need to ensure that all of the customers they serve have an adequate stock of perishable goods, in addition to working hard to ensure that their brand gets top billing. Traditionally, this was based on making educated guesses about an items popularity with customers and knowing how much you had on-hand. But with the easy availability of machine sensors that provide actual real-time data that can be collected in the cloud, that guesswork is no longer required.
Working with the Orlando Brewing Company, we’ve delivered an open-source sample application that implements just this type of functionality. Leveraging real-time inventory information and sharing that information with Salesforce.com (as well as opening up potential to integrate with other applications like SAP and Amazon AWS), account reps can now provide their customers with even better service. They can follow data from the sensors and determine when a customer is likely to run out of a particular beer, know when consumption is higher than usual, and proactively reach out to customers to let them know that now is a good time to reorder in order to avoid running out based on the current consumption trends. With a solution like the application bitHeads has build for Orlando Brewing, field reps can easily keep their fingers on the pulse of their business, tracking profitability, customer locations, and even keeping track of keg locations with sensors in order to minimize loss.
Want to learn more about how this type of technology was implemented on BlackBerry 10? Check out the archive of our recent webcast, Fact-Based Decision Making Using Context, Location, and Time.
If you’re interested in trying it for yourself, the source code for the Orlando Brewing application is available on BlackBerry’s Github site.