Visibility, as a characteristic or condition of the supply chain, has been sought for over two decades. First, we just sought to gain visibility across our own operations — from plant to plant and warehouse to warehouse. Suppliers were tied to the performance of the terms and conditions in the contract, so we did not peer too closely. However, outsourcing changed all that, and we now see trading partners as an extension of operations. Together, outsourcing and globalization have heightened our awareness of supply chain risks. Knowing our fragility in this new world order, we have a new sense of urgency to create visibility across multi-tiered operations and with suppliers through much finer grained information.
The internet has provided the first real hope of achieving visibility: there has been an explosion of cloud-based visibility solutions for supply chain. The weak link is that most of the data comes from a series of partners and their technology choices. This source data can be unavailable or of dubious quality to begin with and then be propagated others in the chain.
In addition, the data we seek today is beyond digital (those rows and columns emerging from traditional systems) and it is beyond static data processing schedules and timing. We want our data to be real time, item level, and context aware. Meeting these objectives required a whole new generation — actually, several generations — of technology that we are just beginning to see deployed in enterprises.
Visibility has huge value and does provide concrete business benefits. Yet, enterprises still cling to the traditional database-enterprise ERPs that, though they have their place, do not solve the problem of supply chain-wide visibility. In addition, semi-manual approaches are often used for trading partner communications with spreadsheets, phone, fax, email, and EDI as the rule. Surely not scalable. New technologies have emerged to significantly enhance the chance of attaining visibility. In addition, significant progress has been made in creating interoperable platforms that help manage large trading networks.
The term ‘control tower’ had emerged as a new product offering from many supply chain providers. However, control, which variously may mean to have command, have power, or be in charge, is an elusive phantom, in ChainLink’s opinion, and may not even be a desired goal.1 No doubt a large customer has some ‘rights’ in wanting to control, but clearly they have no control over the weather, for instance. Visible, real-time insights and the ability to influence outcome, where possible and appropriate, may be a more realistic and achievable goal.
‘Supply chain networks’ is a term in vogue now, representing a new architectural approach to supply chains, and mirroring the business models of the participants who partner together. Understanding the architectures of these networks is critical in selecting the solutions that meet the goals that you and your trading partners are attempting to achieve.
The internet of things, also a significant set of concepts and technologies, has matured to the point where enterprises large and small can deploy smart, connected products, leverage their data, and share that information across the chain.
ChainLink has been looking at this issue since our inception, exploring trends from networks, on demand, cloud, B2B integration, and location-based IoT technologies to social collaboration. All those architectural approaches have become important in the last few decades and play a vital role in our ability to achieve visibility. And now we also have blockchain to add to the supply chain lexicon.
The challenge in the past decade as technologies became ruggedized, scalable, and easily deployable was that each domain was a separate shopping list for the enterprise, increasing the integration challenges. Now we see the emergence of a platform (surely another overused word today) that does provide substantial integration and often relevant applications to serve the objective of visibility.
This series is an update from The Journey to Visibility, which we published in 2013, and will cover the current state of the visibility solutions. Firstly, we will define what visibility is. We will walk through the evolution of the technologies from simple messaging to the current state. We will look into emerging techniques and how they fit into the visibility footprint. Then we will discuss many of the supply chain sectors and solutions today that can serve as modern visibility and network solutions for various industries.
What Is a Visibility System and What Should It Provide?
Managing any process requires information. The characteristics of information today are not only the type of business data — order, plan, and information about the thing itself; inventory status; and so on, but the time state of the data, as well as the support and influencing conditions (temporary or temporal data) that may impact the process or product. We call that context. Hence, visibility should be context-aware. That is, the data streaming in should be about the thing, where it is, what is happening to it and why. For example, an item is expected at a location at a certain time (a plan), but due to rain (temporal data) it will be late by two hours (predictive). (See Appendix for a discussion about data states.)
Visibility addresses the ‘now’ event and analyzes it as it unfolds. That event has dimensionality: the event’s other attributes — exactly where is it occurring, how fast is it occurring? Why is it occurring? Hence, multiple streams of data are required to create the true picture.
Answering ‘why’ often means analyzing a series of events, so the visibility system needs event processors (commonly called Complex Event Processors, CEP) to process and analyze multiple events. Complex Event Processing2 should be part of the lexicon of supply chain professionals today. Complex Event Processing leverages multiple streams of data and provides the ability to determine the causal and provide predictive analytics. Often coupled with AI/Machine Learning, the CEP is an important addition to supply chain systems,3 since it enables us to understand what is happening and why. A current supply chain system may provide an expected arrival time followed by the actual time (after the fact). From that information, we can determine that the delivery was late. But we want our system to alert us ahead of time that this might happen and why. As we (or the system) learn, we can develop mitigation strategies to change plans now, or avoid that type of occurrence in the future.
Another sought-after example is real-time customer data. A customer picks up an item in the store, studies it and puts in down. Why? Or they pick up that item and put it in their cart. That may be the time we want to guide them to other items or offer promotional pricing for buying more. As items leave the shelf, how urgent is it to replenish those items?
The service change is an area in which we see visibility and IoT systems being deployed. Monitoring equipment to ensure uptime through rapid response and automating the technicians’ tasks to respond, repair, and log the event is a huge value proposition for manufacturers and their service provider partners. These are commonly-desired examples; there are many other profound examples too numerous to mention.
Another critical element is the need to reduce inaccurate data due to dependence on manual data input. So-called auto-id is not new, but it is interesting to note that implementing basic scanning is not only the foundation of many of the applications, but also the more active projects and investments for manufacturers, warehouse operations, and carriers at this time.
Of course for planning, humans are still best, but the data has to be accurate, relevant, and current. If your partner’s plans change, shouldn’t you be acting on that data? The idea of not disrupting the planning process with fresh information is passé. The argument that it disrupts the plans means that that enterprise’s systems are just not responsive to the markets they serve. The very nature of customers is that they do what they do, whenever they do it. Demand- or market-driven planning should not be a concept, but an enterprise’s ability to be agile — and relevant — to their customers.
Customers and your trading partners want precision. Lack of precision costs money. Precision is required across the chain. Today, in-house systems such as manufacturing and warehousing provide this, but logistics is still to be conquered. And with global chains that have to deliver right to the consumer’s frontdoor, we have to get that right!
The above is not just an academic discussion about data. Supply chain organizations are anxious about multi-tiered and far-flung activities which they can’t see or control. Customer safety, supply chain performance, brand, reputation, and sales are all at stake. Beyond just visualizing and analyzing, visibility is about reducing cost and seizing time to market. Today, with dynamic pricing for products and spot rates in transportation, visibility provides the extra competitive edge.
Visibility systems are based on the concept of current data. Often we use the term real-time, but in actuality, real-time data is hard to come by.4 So we need a better definition of what a visibility system is and what it should provide.
A Visibility System definition: A system that provides a current picture of events as they occur. The data is continuously refreshed, so the user gets the most current multi-dimensional picture of what is occurring. Further, the system should have methods with which to understand the cause of events and provide the ability to impact future outcomes.
My best analogy is watching live sports. Imagine your supply chain system is like watching a game on your 60-inch HDTV. You can see all the plays, often better than being there. During the broadcast, commentators feed statistics about the players and teams, and describe the implications — based on one play or the other — for the future. The TV provides the viewer with richer resolution as well as multi-dimensional views — multiple streams of high-definition information. In a business context, the analogy would be live, continuous streams of information about remote operations and environments while seeing them in real-time.
Now we can have that for supply chain. The journey to get there has been long, with some false starts, but mostly with a cynicism within much of the user community toward just how good it can get. But as they say, the situation on the field is dictating strategy and the enterprise has to respond to intense competitive threats.
So the standards are a lot higher now — and so are the stakes!
In the next installment we will walk through examples by industry, applications of visibility technologies, and some companies and how they meet the visibility challenge.
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1 There are many reasons why control is not viable. Strong brands will chafe at the concept; even large powerful retailers or OEMs may not seek ‘control’ due to financial or liability reasons. For mid-market companies, the best path is influence and responsiveness. — Return to article text above
2 Complex event processing.– Return to article text above
3 Weather systems are examples where complex event processing is used. Risk Management systems are other examples. — Return to article text above
4 A discussion of systems and their information states is discussed in Transportation Systems Redefined. — Return to article text above
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