5 Elements of a Healthy Digital Supply Chain

Posted by Brian Hoey on Mar 5, 2019 9:00:00 AM

Supply Chain Digitization-1Pop quiz: how many of you reading this are wearing a Fitbit right now? We’re willing to bet that at least a handful of you answered in the affirmative, maybe even a large percentage of you—and on some level that makes sense, because step-counters and other pieces of wearable technology give us insight into and control over our health in ways that simply weren’t available to previous generations. A mere couple of decades ago, most people presumed themselves healthy until they received some evidence to the contrary, whether that came in the form or new pain and discomfort or a stern talking to from a primary care physician. Now, with just a wristband and a smartphone you can monitor your sleep habits, your heart rate, and your physical activity in real time, meaning that if something changes in your health status you’ll notice early and take immediate action.

Perhaps surprisingly, this is a pretty good metaphor for the modern supply chain. In previous eras, you’d only know that there was a problem with your supply chain if something actively went wrong—say, a shipment arrived late, or a production line ground to a halt. But in the modern, digital world, it’s suddenly possible to collect, store, and analyze enough data to identify early warning signs when it comes to any potential supply chain disruptions. More than that, it’s possible to assess the health of your digital supply chain even when things seem to be working smoothly. How? By looking for these five elements.  

 

1. E2E (End-to-end) Visibility

One of the most important signs of a healthy supply chain is visibility. If you have a fully digitized value stream, but you can’t access mission critical data for your planning or production workflows, you’re almost certainly not reaping all the benefits of digitization. Conversely, if data streams from IoT devices and RFID chips are being collected in a centralized, connected IT environment, you’ve probably established the foundations of an efficient, agile supply chain. The mere fact of being able to access a given piece of information from anywhere up or downstream in your sourcing, production, or transport processes means that when it comes time to make a decision or respond to an event, you’re already positioned to choose the optimal path forward.

 

2. Real-time Data

The natural step up from E2E visibility is real-time visibility. And, to be sure, this is another good sign of a robust digital supply chain. If your organization has the IT infrastructure and wherewithal to create live data streams that can be accessed across all touchpoints on the value chain, you’re probably doing something right. Not only is real-time integration an important end in itself, it also helps pave the way for S&OE workflows and other important functions, like the one we’ll be discussing in the next section:

 

3. Analytics Integration

Of course, much of the data that a highly visible supply chain produces will have considerable latent value for analytics processes. Where a human planner might be able to turn the information she’s gathering into useful insights, advanced predictive and prescriptive analytics flows can go one step further, powering improved forecasts and process improvements via careful data analysis. If your digital supply chain is equipped with these kinds of workflows, it’s proof positive not just of a high degree of visibility, but of a cohesive IT infrastructure that’s optimized to address real business needs. With advanced analytics flows in tow, you should be able to take a proactive approach to things like sourcing, production planning, and transport routing in order to best meet shifting demand levels and market conditions.

 

4. Automated Workflows

At this point, the line between a digital supply chain and an Industry 4.0 supply chain is a little bit blurry. Both of them rely on cohesive IT infrastructures to build added visibility and data processing into existing workflows, but only Industry 4.0 requires the creation of cyber-physical systems and autonomous machine and computer workflows. We would argue, however, that there’s less of a binary and more of a spectrum when it comes to supply chain digitization vs. Industry 4.0—and as such, a healthy digital supply chain might edge into Industry 4.0 territory more often than not. Thus, an especially robust digital supply chain might have exactly the sort of automation flows that we’d expect to see under Industry 4.0. This means that digital planning processes might be able to self-correct based on changing demand information. For example, you might see transport logistics processes that automatically update freight routes based on the latest traffic and weather information—exactly the way that Google Maps does for driving directions, but on an industrial scale accounting for a complex set of factors pertaining to your value chain operations. This could be a way of adding value by reducing the need for human intervention, yes, but it can also act as further proof that connectivity is being prioritized in a way that has tangible effects on your operations.  

 

5. Reduced Waste

Now, let’s say your digital supply chain has checked all of the boxes so far. It’s got a high degree of visibility and smart processes that help you to make better decisions. Sounds like your supply chain must be pretty robust, right? Not necessarily. Each of the elements listed above is important, but it’s just as important to make sure that they’re all working in tandem to create a more agile, efficient, and profitable value chain. After all, isn’t that the goal? In order to make this dream a reality, you’ll need to ensure that your supply chain functions are all fundamentally helping to reduce waste and increase overall effectiveness. You could easily find yourself managing a supply chain that was equipped with the most sophisticated technology, while still being mired in waste and inefficiency. This state of affairs can be identified in a few different ways, but the easiest is to utilize prescriptive analytics processes to automate the process of uncovering waste. Given that our suggestion here is to use advanced analytics, it might seem like reduced waste doesn’t deserve its own section—but the point here is not just to see whether you can gain insights from your data: it’s to see if your digital supply chain can actually implement those changes in a value additive way. 

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Topics: Digitization, Advanced Analytics, Industry 4.0