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SCRC Meeting Insights Part II: Management Principles for Executing Visibility Strategies

As organizations move towards visible, high velocity, transparent supply chains, a number of questions arise that are fundamental to the business, but which executive often struggle to answer with any clarity.

  • How do we extend the concept visibility and control beyond our four walls to drive better execution in our supply chain?
  • How do we get materials from our suppliers to our partners to our customers – given that we rely primarily on spreadsheets and email to interact.
  • How do we understand and limit the data we focus on for decision-making? The problem in most supply chains is “not enough data”, because data is being created from machines, from people, from systems, and from external sources. No, the problem is too much data, not enough!
  • What do I care about and therefore focus on, that is the primary factor that will hinder my ability to get products and services to customers? This means finding the right data, the right tools, and finding the exceptions, and rendering decisions based on the data excerpts available. No easy task.
  • How do we identify problems that may be surfacing, that are hidden in the mass of unfiltered data we have today? Often the sources of information are hidden in piles of data that we don’t think about. For example, Elementum identified the Tianjin explosion when someone took a photo of the explosion, tagged it and posted it on Sina Weibo, the Chinese version of Twitter. Social media feeds are just one more form of intelligence that can be leveraged to deal with the flood of information. But the challenge is that although companies have all sorts of news and media monitoring, very little of it is actionable information.
  • The problem thus becomes contextualized into the following sets of questions: How do we take information and data, and put it in the context of our company and our situation, and leverage this information into actionable insights? How will real-time intelligence help me any more than what I’m doing today? What impact does digitization (the internet of things, or IoT) have on my organization and my employees? Will digitization change the way we measure things and monitor metrics?

In addressing these questions, Dana Martin from Elementum emphasized the need to think about the next generation of supply chain. Vertical integration went away because we have moved in the direction of running virtual vertical integration. Brand owners are a key part of this. Companies like Flex are looking for ways to integrate vertically, not just on product manufacturing, but also in terms of how to collaborate better to drive more efficiency. This also implies the need to restructure contractual terms to be able to ensure that as problems arise, (whether due to fluctuations in demand or other factors), managers can quickly adapt to these changes in the supply chain to drive the right outcome.

This ability to contextualize data into decision-making does not occur overnight. It is an evolution that occurs in stages. Today, we are mostly reactive, because we are so close to the problem. Although you may not realize it, but executives really aren’t making many decisions, because there aren’t many to make! We are forced down a path because you found out too late. But if we can begin to learn about problems earlier and earlier, we have more options available to us, and very often these options happen to have much lower costs.

Data Crosses Functional Silos

Dana emphasized “This is a journey people are taking as they drive visibility into the supply chain. The responsive piece is all about how to align teams within the organization, not just internally, but across the organization. We are used to operating in functional silos that involve managing people and keeping them in buckets, and the data these people are exposed to reinforces these silos. And very often, the processes those functions have are within silos as well. A problem in procurement can impact manufacturing and logistics and planning, but often these dots are never connected, so there never emerges a cross-functional approach to working on them. But when we connect the dots linking a problem to other functions, we are now able to create a coordinated and multi-disciplinary team that together is able to solve the problem faster.

OK, great! We now know that cross-enterprise data can tie people together and be automated. Big deal – people have been saying that for years! But the real challenge here is not only automating this process, but ensuring that it is only the exceptions that are used to pull the functional silos together to solve problems.

Let me emphasize that: it is the exceptions that govern and bring the right team of people from silos together to solve a problem! So as you look across the enterprise, there is a need for a mechanism that pulls exceptions and pulls together in real-time a cross-functional team that can across the end to end supply chain, (including manufacturing sites, 3PL, 4PL, transportation, distribution sites, and suppliers.) This mechanism must be driven not simply by external impacts, such as floods in Houston or explosions in Tianjin. The mechanism must be at a far more finite level to extract data showing events that impacts the overall efficiency and throughput of our supply chains.

Monitoring Small Events, not Black Swans

The mechanism for screening data is therefore not just about tracking Black Swans. Black Swan events don’t happen very often, and you don’t optimize your supply chain in the expectation of a Black Swan. The challenge is to be able to filter out small issues and events that happen day to day. Customers change the quantity they ship inside of lead times set by the supply base, and the quantities double. There is a quality problem in production and the schedule falls behind while the problem is resolved. The server goes down for an hour and shuts down communication. Or there is a quantity shortage on a critical raw material at a sub-tier supplier that delays shipment by a day.

These types of small but important events require the attention of a cross-functional team, composed of individuals from multiple functions, including design, marketing, sales, order fulfillment, logistics, procurement, manufacturing and suppliers. A demand fluctuation or a planning issue, if left unresolved, can quickly escalate into a bigger problem, unless it is solved using the right team of individuals. The later delivery may be escalated if there is a contractual obligation with the customer. Small issues represent friction on the flow of the supply chain that drive up cost and impact customer satisfaction. To address these issues means taking a small team for the initial assessment, and building a larger team if the problem is bigger than anticipated. The speed at which teams are drafted and combined to solve problems is in direct proportion to the ability to solve the problem quickly at a low cost and minimize this friction.

Going back to this example – a problem in on-time customer delivery – really only becomes a major problem if the problem is not visible across a multi-carrier network route. The ability to quickly become aware of the problem and solve it means having the right data pulled and put in front of decision makers at the right place and the right time? Improved decision-making occurs when data is presented in a fashion that escalates the nature of the issue to decision-makers. This is also challenging if we have dispersed decision-makers in Brazil, the UK, the US, and other locations. The worst case scenario is that everyone believes everything is fine until the customer notices recognizes hasn’t got his stuff, and contacts the company to inquire about it. This is effectively the first recognition that the delivery is late, but it is too late in the process to do anything about it. The late delivery has already occurred. So buyers are now in a firefighting mode to try to find the right data to explain where the shipment is, why it’s late, etc., which isn’t about solving the problem before it impacts the customer. No matter what happens, the customer is upset now that the shipment is already late.

Assumptions for Creating Transparency

The problem of course is that information in the supply chain is never complete, and will always contain bad data. Even as US-based companies worldwide invest in software such as SAP and Oracle, the standards, availability and consistency of the data produced by these systems will never be 100% stable. And when you now expand your supply chain to places like China, Vietnam, and Latin America, where emerging country customers are located, the variability in data standards and integrity will only increase, as many individuals are still using fax and phone calls in these regions.

So the de facto position should automatically be that data is relatively easy to get, often contains errors and incomplete datasets, and is produced by a multitude of technologies. Any visibility system must be constructed with these basic tenets in mind.   Elementum uses non-relational databases that have no set data schemas, allowing them to input any kind of data that will be stored and analyzed. Graphical interconnections between people, parts, and functions are constructed that enables a problem in one area to be immediately linked and related to another area, where the problems can be quickly scanned and potentially solved. This approach of linking data through non-traditional forms of relationships is the true “secret sauce” behind effective visibility systems in real-time supply chain systems. It is a characteristic that makes the approach powerful and actionable.

How are these connections identified, established, and hard-coded into the visibility system? Dana notes that “We want to understand your end to end supply chain, and begin by literally mapping the entire supply chain from supply distribution through to customers.   We want to know where your subassemblies come from, at as granular a level as we possibly can, which is the level at which there is specific risk. We want to know how you are organized, where you have external dependencies, whether it be a location, a supplier, or something else, and how these elements are interconnected to your supply chain.” This mapping activity is something that should be happening anyhow – but companies often overlook this simple process mapping tool as a vehicle for driving continuous improvement, as well as visibility.