Last week I spent a very productive day with a leading technology analyst discussing the Internet of Things (IoT). The analyst had recently switched to covering IoT instead of B2B integration and EDI, so we had a very interesting discussion relating to the role of IoT in the supply chain, and how it will help to introduce more self-sensing, closed-loop processes to companies across multiple industries.
I have been closely following the IoT sector for nearly three years now and have posted a few blogs on this subject. In this blog I wanted to highlight one significant area that I covered in an interview for Forbes magazine last year. I hadn’t realised the significance of the article at the time, which discusses how in the future, connected devices or things could potentially initiate some form of procurement process by themselves using analytics-based techniques to measure usage or consumption patterns for the connected device concerned.
Say hello to Device Managed Inventory (DMI)!
The analyst was quite surprised that this concept had not been mentioned before, and asked the ten participants in our meeting to search for the term “Device Managed Inventory” on Google, and only our reference was found. It’s rare to lay claim to a new industry term, but I certainly believe that we will see rapid adoption of DMI as more and more supply chain-related devices get connected to IoT platforms around the world.
DMI is really an evolution of Vendor Managed Inventory (VMI) which has been around for years. Companies across the retail and high tech sectors have deployed VMI processes with key trading partners to help streamline their supply chain operations. VMI is part of a family of business models in which the buyer of a product provides certain information to a vendor (supply chain) supplier of that product and the supplier takes full responsibility for maintaining an agreed inventory of the material, usually at the buyer’s consumption location.
A 3PL provider could also be involved to make sure that the buyer has the required level of inventory by adjusting the demand and supply gaps. The aim of VMI is to essentially prevent the buyer from running out of stock and to minimise inventory across supply chains, for example in warehouses or regional fulfillment centres. EDI has been central to this particular process for many years.
The key to making DMI work smoothly is to efficiently collect information from sensors attached to the connected device, as in the case of the vending machine example shown below, and then feed this information into an analytics platform. Analytics routines would then continuously monitor consumption patterns, compare with stock levels, and when the levels get near to or below a predefined level, a procurement process would be initiated by the connected device and an automated EDI transaction would be generated and sent to the supplier for fulfillment.
This application of DMI is really a form of Proactive Replenishment, the aim being to ensure that stock levels are always within a certain set of min/max levels and hence ensure that customer satisfaction levels are maintained. DMI would certainly be useful for replenishing stock levels in retail stores, maintaining fluid levels within gasoline storage tanks or parts quantities in storage bins located next to manufacturing production lines.
This type of scenario, whereby the connected device initiates an EDI transaction, could also be applied in a Predictive Maintenance scenario. So for example sensors fitted to a vehicle’s water pump could detect water flow rate changes, perhaps due to a leaking seal or crack in the casing. This information would be transmitted to a vehicle service centre where new parts could be proactively ordered with the relevant supplier. The driver of the car would be notified that the water pump would likely fail within a 1000 miles and their vehicle would be booked in to have the replacement part fitted.
I have discussed both of these scenarios in an earlier blog, where I looked at use cases for IoT across the supply chain and how analytics could leverage information flowing across the supply chain to make more informed decisions. Many of the key building blocks to make the above scenarios a reality actually exist today. MQTT, for example, is a relatively new open source communications protocol used to connect devices to a network. To learn more about how analytics will drive future supply chain operations, take a look at this earlier blog.
Read more from the analyst I spoke with, who described DMI as a “Gob-Smacking B2B IT Mash-up”, in his blog here.