I am at Axeda’s annual Connexion conference which brings together users, practitioners, analysts and providers in the M2M (machine-to-machine) / connected products ecosystem and found an interesting outcome of connecting the physical, digital and data networks of supply chain fulfillment: on-demand ice cream… with toppings no less.
- Single machine: The embedded technology within the dispenser can monitor both performance as well as usage. Data on the performance is shared with the services organization to ensure the machine is always running and enables remote services so that any issues can be proactively addressed before the issue ever impacts a user. Usage data is shared to show what flavors are most often being selected, how long it takes to complete an order and the volume of users. This data can be used to optimize replenishment as well as offerings at the unit level. A demo of the internal monitoring is shown here:
- Extended network: With an aggregated view of all the data across every deployed machine, MooBella can enhance their customers’ experiences by optimizing offerings to maximize availability of the most popular flavors, by reducing cycle times in the user experience and by streamlining offerings to minimize queue times in the busiest locations (like a sports arena).
- Demand management: MooBella’s machines are a clear example of a semi-configurable make-to-order process. These types of processes often lead to variability that will meals demand management more difficult. Analysis of usage patterns will enable better supply alignment with a better understanding of short and long-term demand. Offerings per machine can also delimited where needed to actually shape demand.
- Supply chain services: With a remote diagnostic of any issues, the services organization can align repairs and service parts management in a more efficient manner. Not only does this reduce costs associated with downtime and multiple repairs, it ultimately delights customers by avoiding any disruptions to their use of the product.
- Cycle time management: Data analysis on the time it takes to start an order to get your ice cream is monitored as an indication of how difficult it is to complete an order. This time can vary, say between an elementary school and a corporate office (the kids most likely being much more adept with the technology). Based on this data, offerings will be aligned at the machine level to ensure the supply matches the individual demand. This same methodology can be used to reduce the time per order in high volume areas.
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