How IoT Based Analytics Will Drive Future Supply Chain Operations

Over the past couple of years we have seen an exponential growth in interest around the Internet of Things (IoT). My interest in this space started at Cisco’s IoT World Forum in Barcelona in late 2013.  Back then many of the software and solution vendors were just starting to define their IoT strategies due to the various estimates that analysts had put out about the expected value of the IoT market over the next decade.

There were two interesting IoT related announcements this week, firstly GE placing all their IT and software solutions into a new division called GE Digital. Slight irony here in that this is the second time GE has done this, the first time was when they established and then spun off their former IT division which later became GXS!  The second announcement came yesterday at Salesforce’s annual conference where they announced their own cloud based IoT platform.  So the IoT cloud market is certainly hotting up.

In 2013 I posted my first blog discussing where I believed IoT would impact supply chain operations and from what I could tell back then, based on the number of IoT and Supply Chain articles that had been published, I was early to predict how IoT would transform tomorrow’s supply chains. Many argue that some components of an IoT environment, such as RFID tags, have been around for many years and in fact IoT has now given RFID tags a stronger sense of purpose.  However other technologies such as Big Data Analytics are really only just starting to be applied in the supply chain space.

For me, I see three areas where IoT will add value to supply chain operations, I call these the ‘Three Ps’ of supply chain focused IoT, namely Pervasive Visibility, Proactive Replenishment and Predictive  Maintenance.

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One common aspect to all three of the above scenarios is big data analytics.  Earlier this year OpenText acquired a leading provider of embedded analytics solutions, Actuate.  Over the past few months we have been busy embracing the world of big data analytics and recently announced a cloud based analytics offering. This is quite a game changer in the big data analytics market as companies look to take their first steps into the world of analytics and OpenText Big Data Analytics in the cloud allows companies to scale their analytics platform over time and align with the size of the analytics project being undertaken.

In fact yesterday, OpenText was ranked number three in a new report from Dresner Advisory Services, they looked at the Business Intelligence market in the context of IoT. It is worth noting that the chart and vendor analysis conducted by Dresner was carried out before the launch of our cloud based analytics solution, so we would probably have been ranked higher than number three out of seventeen vendors.  When you consider the size of the analytics market and the number of vendors in the space, this is quite an achievement for our solution and it puts us in a good position for companies looking to process the huge volumes of data coming off millions of connected devices in the future.

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OpenText Big Data Analytics is a core component of OpenText’s cloud strategy and early last year OpenText acquired another key cloud solution provider GXS.  OpenText now operates the world’s largest B2B integration network with over 600,000 companies connected to the network and these companies are processing over 16billion transactions per year.  Now wait a minute, 16billion transactions!, now that is a lot of information flowing across our network that could add a lot of value to companies if they had a way of analysing the transactions in real time. As you would imagine we are busy looking at how our Trading Grid platform could leverage the capabilities of our new cloud based analytics solution.

I have spent the past two years keeping a close eye on the IoT market and it is great to think that our cloud based analytics solution provides a stepping stone into the ever growing IoT market.  But what happens when you bring the world of IoT and supply chains together?  I wanted to use the following diagram to explain how OpenText Analytics and Trading Grid could in the near future provide support for the three supply chain scenarios that I mentioned earlier, namely pervasive visibility, proactive replenishment and predictive maintenance.

The diagram below illustrates a desktop demonstration of how consumption trends from a connected device can help to initiate a ‘purchase to pay’ process.  When I say purchase to pay I am talking about an order being created, goods being delivered and then payment made to the supplier.  Let me now break this diagram down into a few key steps.

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The first stage is the connected device itself, now it could be any type of connected device, but for this example I have chosen a WiFi enabled coffee machine. In addition, for the purposes of this demonstration, a connected coffee capsule dispenser, so as you remove a capsule this will be recognized by a proximity sensor placed underneath the capsule.

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The second stage is to then capture the consumption trends from the coffee machine.  So as each capsule is taken from the dispenser, a signal would be sent to OpenText Analytics which will essentially be used in this case to monitor consumption patterns and overtime trend related information and graphs etc can be displayed. The key step in this process is when OpenText Analytics detects that a certain number of capsules have been used and an order can be placed via Trading Grid for replacement capsules to be delivered from an outside supplier. This in essence is Proactive Replenishment, where analytics data is driving the ordering process.

Back in January this year an article on Forbes.com discussed how in the future connected devices would potentially be able to initiate their own procurement process.  Thus taking manual ordering of replacement goods out of the supply chain process.  Now we are some way off achieving this at the moment but the IoT industry is heading in this direction. For now though a trigger from OpenText Analytics would alert a user to create a Purchase Order for ordering replacement coffee capsules. This ordering process would be initiated through one of our SaaS applications on Trading Grid and this application, Active Orders would also monitor the end to end life cycle of the order.  Mobile access to the progress of the order from the supplier to point of delivery would be available via a mobile app.

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The order for the capsules is received by the supplier, represented below by a robot arm, which selects the replacement capsules from a rotary capsule dispenser and then loads them on transport provided by the 3PL carrier. Now over time sensors on the robot arm would detect any potential failures with its operation.  From a maintenance point of view, the operational information coming from the sensors on the robot arm would be fed into our analytics platform and overtime you would be able to predict when a part of the robot is likely to fail.  In the real world you would then initiate a repair before the robot fails and hence your supply chain operations are not interrupted in anyway.  This is a perfect example, albeit scaled down of how IoT can drive Predictive Maintenance procedures.  In fact predictive maintenance is widely regarded as one of the most important industrial applications for IoT at this moment in time.

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For the purposes of this example the 3PL carrier is operating a model train!, which will carry the capsules to coffee machine on the other side of the table.  The location of the train would be monitored via an RFID tag attached to the train. The potential for improving end to end supply chain visibility using IoT and connected 3PL providers is huge and Cisco and DHL recently released a white paper discussing this opportunity. The RFID tags in this case are being used for the purposes of this demonstration but in real life a combination of RFID tags and GPS devices would be used to track the shipments. The ability to connect every piece of supply chain equipment, whether fork lift truck, lorry and pallets etc will transform supply chain visibility and will contribute towards the Pervasive Visibility across an end to end supply chain.

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So there you have it, a very simple example of how IoT could impact future supply chains.  The IoT market is moving incredibly quickly and who knows what new technology will be introduced over the coming years, but one thing is for sure OpenText can now provide two key components of the IoT enabled supply chain, OpenText Big Data Analytics and OpenText Trading Grid.  The world of B2B integration just got exciting.

About Mark Morley

Mark Morley
As Director, Strategic Product Marketing for Business Network, Mark leads the product marketing efforts for B2B Managed Services, drives industry and regional alignment with overall Business Network product strategy and looks at how new disruptive technologies will impact future supply chains. Mark also has over 23 years industry experience across the discrete manufacturing sector.

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