Can Supply Chain Integration Improve Your Forecasts?
Brian Hoey - August 04, 2020
In a study conducted a couple of years ago, fully integrated supply chain businesses were found to outpace their competitors in terms of revenue by about 20% on average. This makes sense—after all, we’ve been talking for years about how important integration can be for a healthy, responsive, and data-driven supply chain. Because integration produces insights and information both up and downstream in the value chain, it can give planners and decisionmakers the holistic overview of their operations that they need to weed out waste and avoid disruptions.
As it happens, one of the most powerful ways that planners can leverage that influx of information is by putting it towards improved forecasts. Simply put, the more high quality information you have to work with, the more effectively you can predict future demand levels and plan accordingly. Of course, that’s assuming that you have the necessary planning and analytics processes in place to turn the data you’re collecting into meaningful insights.
How Demand Volatility Causes Disruptions
Fundamentally, all disruptions spring from the unexpected: if you magically knew in advance that a flash flood was going to trigger a pile up on the highway and thereby make your transport routes impossible, there would be no reason that it should actually impact your able to deliver goods on time—on the contrary, you would simply adjust your routes ahead of time to avoid the impacted areas. In the same way, the more stable your demand picture is, the easier it is to avoid any sorts of pitfalls. Unfortunately, in most industries demand is anything but stable, and it takes years of experience to be able to recognize the telltale signs of an impending spike or dip. Even then, there’s no surefire way to calculate demand levels in advance if you’re just doing back of the envelope math or simply going with your gut.
Since demand volatility isn’t something that planners can effectively grapple with unaided, spikes or dips in demand for particular parts or finished products can come out of nowhere and wreak havoc on your supply chain. If you don’t see a large influx of orders coming in time, you’ll likely have to pay for premium freight to fulfill the later orders in a timely way, which will eat into your margins. For some orders, you may not be able to fill them on-time at all (especially if you weren’t operating with much buffer stock), and you’ll risk losing out on future business from those customers. If the opposite happens and demand suddenly evaporates, the results can be just as bad: in addition to lost revenue (compounded by the fact that you may have already used up resources creating products for which no demand is emerging), you might be looking at added costs arising from the need to store the unsold stock. Ultimately, the only way to minimize the impact of these sudden changes is to see them coming in advance—which requires the collection and analysis of digitally-derived data.
Supply Chain Integration Means More Data
With advanced predictive analytics, it’s possible to turn operational data from a wide variety of sources into estimates of future demand levels, thereby giving you the chance to better prepare yourself for what’s coming down the pike. The trick to making this work is to capture the right data in a timely way—which is exactly where supply chain integration comes in. If production planning, inventory management, and logistics planning all operate in separate silos and rely on disparate IT solutions, there’s no way to create a holistic view of those areas that offers insights about the entire value chain. Likewise, there’s little chance of actually collecting the data that your analytics algorithms are going to need. And this is before we even talk about the possibility of integrating data from your suppliers, logistics partners, or even your customers.
If, on the other hand, you’re able to break down these silos by establishing some shared IT infrastructure, you can collect and centralize more information than ever before. With that data in tow, you can begin to run complex analyses using AI and machine learning techniques. In this way, you can begin to move away from informal demand planning towards a more robust, data-driven, and, yes, integrated system. All of a sudden, your odds of seeing the disruptions we discussed above coming in advance shoot way up—and with the proper tools in place for managing demand changes from a sequencing and scheduling perspective, you can leverage those increased forecasts into reduced disruptions and a leaner, more responsive supply chain overall.
How to Integrate Your Supply Chain.
If the preceding sounds fairly attractive from an operational standpoint, you probably have one big question: “How can I make supply chain integration a reality throughout and beyond my operations?” Indeed, it can be a daunting task—but also one that’s eminently doable if you know where to start.
- First, you’ll want to perform a full IT audit of every touchpoint on your internal value chain. Find out who’s using the approved solutions vs. who’s using Shadow IT, and try to understand how and why different teams use the IT that they use.
- Next, identify any existing silos that crop up between different departments and impede the flow of data; this will give you a sense of how far you have to go to achieve integration, as well as the key areas where you should concentrate your efforts.
- Adjust your IT ecosystem to better enable connections between disparate touchpoints—this might involve adopting new solutions, or simply reconfiguring or promoting the ones you already have. Here it’s often helpful to adopt a Postmodern ERP mindset.
- Actively seek out buy-in and engagement from users. Ultimately, the goal is to show how valuable this kind of connectivity can be, and to encourage users within (and, later, outside) your organization to prioritize and take advantage of that connectivity.
Often, the success or failure of your integration efforts will be a factor of a) how successfully you promote engagement, and b) how effectively you choose your solutions. You want to make sure you’re selecting supply chain technology that’s actually designed to network with other solutions to promote integration. In this way, you set yourself not just for improved forecasts, but improved demand management in general.