To continue from the Introduction we published in the last issue of the brief, in this segment let’s review the evolution and the various types of technologies that go into making a visibility solution. Though technologies like EDI often claim they provide a visibility solution, our view is that it is an incomplete picture of our supply chains. In the last few years, many useful — and now essential — methods and technologies have become mainstream, allowing us to have a crisp and current1 picture of the live action across the chain. Supply chain networks that leverage technologies like IoT and AI-based predictive analytics and alerts allow us to have multiple, concurrent participants in the technology.
Before we discuss the technology, it is useful to have a working definition of supply chain visibility in order to assess the merits and limitations of the various methods and technology.
In this section of our report we look at the base technologies, their benefits, and limitations, noting that in reality it is the concomitant use of these technologies that allows us to have that clear, current, and shareable picture. In the next section, we will bring these concepts together and show how that information is leveraged into meaningful applications.
The market has evolved these base technologies, which are often converging, to provide the best dimensionality, views, and opportunities for visibility today:
- Messaging: EDI, AS2, and other B2B methods of transmission;
- IoT: mobile, cellular, RFID and sensors;
- Geospatial Information Systems:2 satellite, geological mapping, and other temporal data;
- P2P: Person-to-person such as texting, social supply chain, and of course, email (still the most prevent P2P technique used);
- Blockchain: beginning to appear in financial and supply chain tracking and tracing applications.
At each stage of the technological evolution, supply chain management systems are exploiting these innovations to improve visibility. Let’s walk through them.
The most common shareable technology on the market is messaging/B2B communication — that is EDI or AS2 messaging from system to system. Rich in information, and standards-based, EDI is highly leverageable into traditional enterprise and supply chain information systems such as purchasing, inventory management, transportation, invoicing, and a myriad of status notifications.
From a supply chain visibility perspective, notifications and status messages are sent from multiple sources either as transactions such as purchase orders, acknowledgements, change orders, transportation (bidding, tendering), POS data, invoicing and payment, and retail; or as rich product and graphical information used for sharing item catalogue data such as apparel and other products.3 EDI is used for status messages – SNs, receiving, time of arrival and so on. Status is highly relevant to visibility since it is much more reflective of an ‘event.’ These events reflect a move or change in some way.4
Why EDI Is Important and Isn’t Going Away
EDI is not just a technology, but a set of trading partner data standards developed over decades of collaboration. We are often asked what will replace EDI. But the fact is that all the new methods are additive and generally leverage the data standards of EDI. It is so ubiquitous and so well entrenched and, often, so economical to support, that pulling the plug is probably counterproductive. It serves as a reliable and essential function in B2B communications, but when relying on it for a visibility solution, it is found wanting.
Advantages and Disadvantages of EDI and Messaging
Compliance and timing are huge challenges in the supply chain. Smaller organizations usually have no or limited tools, and use spreadsheets or log on and manually enter their data using web forms to comply with a large customer’s systems. Often data, even from larger players, is non-standard and needs to be translated. (Of course, this is not an issue just for EDI.)
EDI is inherently latent, due to passage between firewalls and the need for translation — often multiple times — to harmonize proprietary data formats from a variety of constituents who are communicating with one another. There are some pretty ancient EDI systems still in operation that use the ‘modem paradigm’ (synchronous communications where EDI companies charge by character bits, but this method has been dying for some time) as well as a myriad of more modern approaches. Most often there are ‘store-and-forward’ EDI hubs that batch messages before they pass them to the recipients.5 More responsive systems respond as feeds arrive, and translate and transfer the data to recipients as required, which reduces latency. (When seeking an EDI partner, look for these more modern EDI cloud solutions that support cross-functional and real-time communications.)
The lack of collaboration when a big anchor OEM or retailer (a hub) is the arbiter of all the data stymies timely and accurate communications. Peer-to-peer sharing in hub and spoke (one-to-many architecture) is limiting. Trading partners such as carriers or 3PL who need this information to coordinate shipping and hand-offs do not receive timely data about when and how to execute their tasks. These stammers in data transmission become a vicious cycle of delayed requests/responses. Newer supply chain architectures provide a many-to-many architecture which enables sharing of concurrent information and synchronizes the incoming data.
EDI systems are based on decades of industry agreements pertaining to systems and data and standards.6 Buyers can rely on the foundational data to be integrated into a variety of systems and hardware in a fairly standard way.7 There is also a system of records that gets created from this data, when intelligently used, to feed transaction and reporting systems.
EDI networks or collaboration solutions with large subscriber bases8 offer other advantages. New customers can tap into these existing networks and begin gaining value with less start-up effort than if developing their own solutions by building unique integration to the many data sources.
However, a critical limitation is that EDI’s data structure does not allow for context and condition data. This is the chief issue in its use for supply chain visibility applications such as transportation coordination as it needs to change course direction, timing, and so on while processes are in motion. This requirement to change and divert activities based on current conditions in the supply chain is the chief and essential desire of supply chain professionals, as almost nothing happens according to plan.
Today, users’ ability to make decisions for a process in motion is limited. Without precision and context, it is hard to call the shots. Not only is the context lacking (specific location, weather, temperature, and so on), the conditions under which the scans took place and the condition of the goods is not known. Those who need condition data don’t have that need met. Visibility is limited, since all these communications are based on past events.9 And considering the number of disputes about product damage, lateness, etc., there is surely financial value in understanding the conditions. Scan data is error prone and EDI transactions are often built on it.
For supply chain applications that require exactitude at the product/container level or carrier level, EDI is truly problematic. For example, what is the actual vs. estimated time of arrival (ETA)? The exact arrival time is needed to coordinate all the other subsequent processes, for example, inbound transportation management and scheduling of dock reservations and consolidation or pooling of transit merges. In intermodal coordination, when will the ocean vessel actually arrive in port? And then, when will the cargo actually be available to be loaded on the truck? Lack of coordination means demurrage, lateness, congestion at gates and dock doors, fines and fees — missed opportunities and expense. One can often drive past rail stations, ports, or warehouses and see long lines of vehicles waiting to pick up or drop shipments, an indication of the many companies that have extremely poor coordination due to lack of visibility across the process from source through destination.
Messaging systems provide an ETA as the vessel gets close to port. ETA is useful for planning, but as the actual time of arrival nears, it falls short. Transportation carriers provide departure and arrival times, but no data about the conditions under which the freight moved through the chain. The data arrives far too late to address ‘problems-in-motion.’ (Nor does this allow for analytics over time to assess the approach and pick other potential routes, carriers, countries of origin or many other aspects of the game plan.) The time sensitivity of narrow appointment windows is another issue. Short-haul or outbound transportation such as direct store delivery, home delivery, and service response need situational information to manage routes in real time.
Another example is track and trace. Diversion, theft, and loss occur too frequently due to the lack of actual data about asset location. Post-delivery data feeds may help with government compliance or retrospective analysis, but they do nothing to help address and mitigate issues as they are occurring.
Another area in supply chain in which this single-dimension EDI is weak is in demand sensing. Demand planning systems are great for planning, but probably don’t capture the continuous view required at the point of experience.10 Today, retailers, especially, want to see the consumer in action and have the opportunity to respond to upside demand opportunities. In general, EDI solutions lack the ability to do something about what you see.
IoT, Wireless, Mobile, RFID, and Sensors
We are living in a world of digital everything and millennial complexity. As Peter Lucas, author of Trillions,11 stated, “We are entering an era of unbounded millennial complexity.” He was referring to the trillions of devices that will have built-in sensors and microprocessors on every person and thing, creating a trillion-node web. The world is becoming sensor-rich. Estimates of the number of connected and unconnected devices vary, from sensors in your car or your toaster or on your body; to equipment monitoring devices in warehouses and factories; or in the billions of wireless smart phones and scanners,12 but they number in the trillions already. Mobile devices, smart phones, RFID, and sensors provide data about the condition of an asset by transmitting information to readers and to Wi-Fi/internet, cellular, or satellite networks. GPS-based devices provide data about locations. If used concurrently, for example RFID and GPS, or RFID in sensor grids, they can provide dimensional information such as proximity, location, and speed of movement.
This is the era we are in now. From a visibility perspective, this is a great stride forward and a huge opportunity. Sensor information has been leveraged for decades in control systems within facilities. Now we have solutions that leverage these wireless devices to keep track of assets in motion outside facilities and across the globe. The attempt here is to obtain the actual situational data and feed that data into monitoring systems in the cloud.
If analytics are not used just to track assets, but in combination with other data, historical data analytics can derive important evaluations (i.e., learn) creating trends, ranges and safe boundaries, providing alerts when, say, an item is out of tolerance. Temperature, range, exposure and so on are big issues in terms of product — and people — protection. Especially in perishable product supply chains13 such as cold chain or with products requiring more security, these methods are slowly but surely being adopted.
Advantages and Disadvantages
Sensor data is a step up from messaging systems as far as visibility is concerned. It provides the potential to capture data about the asset or item. But sensor systems are limited because they still rely on a chokepoint (a scan location) as the integration point. When combined with active devices or with GPS to provide asset condition and location, they add an important dimension in our quest to ascertain real-time item and asset condition. Fortunately, GPS is quite prevalently used in the transportation industry. And in other industries we are combining sensors with our smart devices and leveraging the now ubiquitous cellular wireless networks.
Active RFID and GPS have become the technologies of choice for rail and ocean carriers, with many of the ocean carriers now providing mobile apps for consignees, shippers, and freight forwarders to tap into the vessel location very close to real time.
When combined with messaging systems (ASNs), users can obtain shipper and carrier data and get a much richer picture of goods in motion. Frustratingly, most of the so-called visibility hubs have eschewed tapping into these data sources, preferring to receive EDI-only messaging from carriers. However, some power shippers are pushing back on that methodology, and are requiring better data. Track and trace, with context, is now at the top of the list of what companies want for visibility.
Logistics Service Providers are being pressured by their customers to provide more timely data to each other and to their customers. In fact, the transportation service market is so competitive that freight forwarders and 3PLs consider visibility a critical element in gaining and keeping customers. They have to stay ahead of the shipper/consignee when it comes to visibility in order to spot problems and attempt to solve them before their customers do.
The above techniques and technologies have taken us a long way, but they still don’t give us a window into the causal environment. They provide a limited vision of the environment that impacts the asset or process, whereas causal data is critical to preventing future problems.
Geospatial Information Systems (GIS) are more than maps. Location-based technologies are becoming the must-have capability for a range of solutions from supply chain and healthcare to consumer apps. But location alone is not enough.
GIS systems have been used in logistics for decades to design routes; in weather systems to inform a variety of applications such as road repairs, farm/agriculture, and logistics and transportation applications; recently, in demand planning to reformulate plans based on current weather conditions; and to manage all sorts of remote operations from defense logistics to construction and mining operations.
Not Maps Alone
Base maps are available from many sources to form a visual and informational foundation for visibility solutions. GIS systems should go beyond mapping, and go beyond using GPS to provide location data. Location-rich, multi-dimensional data should provide a deeper context beyond “the truck is on the corner of First and Madison Avenue.” Certainly that is a huge step forward. But we need to combine that with environmental data streams such as real-time weather, traffic, etc., so that a user can get a context rich, current and continuous picture of unfolding events. State-of-the-art GIS does go beyond base mapping, using real-time data from other streams to provide content-specific applications.
Many applications use older generation maps, which are essentially nothing more than digital, but static, renditions of print maps. More active mapping allows for overlays of dynamic data to plot current conditions. For example, we are used to checking current traffic conditions because current traffic data overlays static maps. From an application perspective, users can manually or systemically optimize their routes.
GIS can also look at broader issues, that is, understand multiple moving parts: not just two dimensional locating, but things like multi-dimensions, altitude and in-motion convergence of vehicles, people and so on (for example, an aircraft’s speed and altitude as it approaches a runway.) We need to be able to analyze multiple data streams to view events and determine their causes. Weather, people, geopolitical activities, labor strikes and slow-downs; local news such as holidays, fires, and more, all impact supply chain performance, and many can be happening at the same time. Over time, by collecting and analyzing data, we can get a clearer picture of what is happening and why. We can then build rules: if this happens, then we may need to take a specific action. And seeing patterns emerge we can change our methods. These advanced analytics, Complex Event Processing (CEP), help us make better decisions in real time and, over the long term, avoid unpleasant results and embrace the upside.
People-to-People: Social, Mobile/Texting
Social supply chain has become a steadily increasing application area. As impactful adverse events happen across the supply chain, often the first go-to task is to talk to someone.14 (Of course, email is still the dominant communication tool.) But the integrated supply chain social network allows participants to see the live data and talk to each other concurrently.
Another element that may be used in certain applications is a data stream about people and populations; but how does this fit into supply chain? Telematics systems can help drivers avoid people and traffic density. Roadside repair services can locate a specific customer. Municipal services such as utilities, or trains and buses can be planned based on the current crowd.
Work crews and drivers can alert one another about issues in weather, impassable roads and delays, or recommend better routes. Weather alerting has been used for a decade in retail, road repair, and maintenance. Now crowdsourcing data can be used to enhance expertise and communications. Social data can also be used by municipalities to pinpoint crime scenes, determine requirements for emergency response, repairs, etc.
In retail, having customer visibility allows retailers to create spot promotions and inform customers about available products and the closest place to find them.
Community activities such as fairs, road races, concerts, etc. can be promoted to bring people together, enhancing the community experience.
What About Blockchain?
Blockchain is the new promising (and slightly over-hyped) technology in the market. Some of the largest vendors are betting big that their customers will embrace (and pay a lot for) this newer approach. The most prevalent use in the general market, of course, is in financial applications. Some of the characteristics of Blockchain become useful, as you will see, in a variety of application areas in supply chain. Blockchain creates a permanent, auditable record of data. Blockchain data is encrypted.15 For example, in a contract negotiation, if the seller posts an offer price, that price is now a permanent part of a ledger. Both buyer and seller can then reference that price which will reduce contentious invoicing issues. In supply chain, freight audit and pay is standard activity since so many invoices are in error. In addition, ticket pricing which is sent by the retailer to the 3PL for the manufacturer often seems to fall through the cracks leading to rework/re-ticketing and chargebacks from the retailer to the supplier. Another characteristic of Blockchain is the decentralization of the data. So unlike a cash transaction which is stored in the accounts receivable system on the vendor’s server only, Blockchain data is distributed and accessible by all relevant parties. This characteristic makes it useful for other supply chain applications — track and trace, epedigree and other ‘labeling’ applications. This is the kind of data that needs to be shared across a supply chain network: suppliers, manufacturers, carriers, customs, distributors and retailers, as well as customers who want to know origin, purity and authenticity of the products they buy.
Cloud-based Blockchain technology can partner with IoT/auto-id devices which automate various types of data collection, and then append (chain), adding a new block as goods and people go from location to location through processes.
The question remains whether the requirements of traceability are already being solved by existing means and how much more Blockchain really adds to the picture. Ultimately, the buyer will decide.
Again, if we consider the definition of visibility, concepts of time (Figure 2), context, multi-dimensionality, and many-to-many communications all are critical aspects of the data we need to receive and process. It is also clear that no one single technology will achieve the goal of traversing the time, the accuracy, and completeness of data we receive. Solution providers who do attempt a very complete solution continue to pursue all the trends and innovations because the concept of visibility is ever expanding.
In our next installment we will discuss what we do with all that data and some of the problems that visibility is designed to solve.
1 I hesitate to use the term ‘real-time,’ as it is overused and sometimes inappropriate to the situation. — Return to article text above
2 Geospatial technology is visualization based on data received from multiple sources such as satellite, maps of geological data such as terrain, and weather, sensors, municipalities, and traffic/transportation systems. See references at the end of this report. — Return to article text above
3 We will be discussing more product information attributes (PIM) in an upcoming report. — Return to article text above
4 They are derived at a hand-off/choke point and usually take the form of a scan as assets move from location to location. — Return to article text above
5 As well, small companies log into portals at the end of the day and manually enter their transactions or upload spreadsheets. — Return to article text above
6 Electronic data interchange — Return to article text above
7 In the last decade much as been done to speed up the transaction process with memory-resident ‘fast servers,’ using MFT for EDI and AS2 transmissions, bypassing the multiple VANs so that senders and receivers can receive status updates in a more timely way. — Return to article text above
8 Such as the GLN from Descartes — with ~220,000 user connections managing billions of transactions per year, or GT Nexus or ONE with about ~30k to 40K 30,000 connections each. — Return to article text above
9 In addition, EDI just does not have the requisite data elements to provide context, nor do EDI systems have the tools — event analytics to understand their meaning. — Return to article text above
10 What is meant here is as the customer is browsing, shopping and evaluating before Point of Sale. — Return to article text above
11 Peter Lucas’s book: Trillions: Thriving in the Emerging Information Ecology — Return to article text above
12 Here we are discussing mobile as a data source. Later we will discuss desktop and mobile as user platforms. — Return to article text above
13 Food, Pharmaceuticals, Health and Beauty, Chemicals — Return to article text above
14 For more on social supply chain, see ChainLink’s Social Networking Collection. — Return to article text above
15 Often, in a definition of Blockchain, the term ‘secure’ is used. I don’t include that here since the term secure has a general meaning in the market and society that means that the data can be accessed exclusively based on permissions, whereas Blockchain’s meaning of secure is that once the data is posted, it is locked and cannot be changed. And the fact is that several of the financial Blockchain applications have been hacked, including the grand Bitcoin. So its claim of security is not any stronger than any other technology or database. — Return to article text above
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