Imagine having to shut down the production line of your most popular–and profitable–product because of a disastrous fire at one of your crucial suppliers. Such a scenario has the potential to be catastrophic because of the slice of revenue it represents. Sure, you can move quickly to reduce the impact of the incident, but the temporary shutdown will haunt you for months—or years—to come.
This type of disaster is certainly not predictable, but the consequences unfortunately are. How can you ensure that you’re prepared for future disruptions such as this? And, even if there are no disruptions, how can you make your supply-chain analytics better? The answers lie in how you implement analytics, manage the process, and who you listen to for answers.
Even small companies globally source parts these days, and their complex production processes reflect that. In order to manage such a complex, tightly-orchestrated sourcing and production environment, many companies are implementing digital supply networks (DSN). With a DSN you create an ecosystem where information flows from suppliers, to producers, to logistics partners seamlessly. Information flow is on-demand, near real-time. That flow creates almost instantaneous insights that are accessible to all interested and authorized parties.
To be sure, a catastrophic fire is almost impossible to predict. However, more predictable disruptions—e.g., labor unrest, economic uncertainty, shipping delays or bottlenecks, and global political issues—can be better managed when information flows more quickly, and insights can be acted on in near-real-time to anticipate and solve problems.
Perhaps even your supplier’s catastrophic fire could have been less disastrous if your management had had better insights and realized that the supplier was a potential bottleneck, due to its unique function within the network, and had more effectively spread the sourcing of these unique parts.
Manage from the Top
The C-Suite must drive the process to embed supply chain analytics into the fabric of the organization. One-off analytics initiatives on a department-by-department basis won’t cut it. Your information—and thus your supply chain—will be fragmented. Moreover, the chain will remain just that—a chain in which links are easily broken and disruptions become disasters.
It’s absolutely critical that efforts to use analytics to build better supply chains (DSNs, if you want my humble opinion) be a fundamental objective of the strategic plan, and that executive performance be measured—in part—on the company’s ability to improve its supply-chain performance. Otherwise, the C-suite will be focused on other issues and supply-chain analytics will take a back burner. This will leave you under-prepared to predict and/or deal with eventual disruptions.
Listen to the People who Know your Business
Most investment bankers likely know very little about designing cars, and I probably wouldn’t trust the VP of production at auto company to underwrite an IPO. What I’m getting at here is that industry knowledge is important. This is true for analytics implementation—especially when you’re talking supply-chain analytics.
You can hire all the quant jocks you want, but if they don’t have some industry knowledge, they won’t be able to produce many helpful analytical insights, because they don’t really understand how the whole process works—and how information flows, and needs to flow.
They may focus on the wrong data, or they may miss crucial pieces of information that someone with industry knowledge wouldn’t. So whether you build in-house, or you outsource to consultants, a critical requirement for implementing supply chain analytics is to make sure that the data scientists and analysts you hire are steeped in your industry enough to understand what the data is telling them.
Further, they must be willing to engage with, and listen to, people within the organization that do have that knowledge. Otherwise, you’re just getting a lot of fun facts and numbers that may or may not tell you the entire story. And with the potential for disruptions to turn into disasters, you don’t need that. You need actionable information that drives quicker reactions to problems and more effective decision-making.
Nothing is Certain
The connections in your business environment are more fragile than you think. Catastrophes such as this one are rare and unpredictable, but others, not so much. You can be better prepared to handle disruptions if your analytics strategy is sound. My advice is simple: go digital as much as possible to derive faster, better insights; lead from the top to drive coordinated implementation; and listen to the people who know your business best so that you get better answers and make better decisions.