Use data to prepare for the unexpected
Back to normal is not happening anytime soon – if ever – when it comes to supply chains. "We can't wait and see. Luck is not a strategy," said Bindiya Vakil, CEO and co-founder of Resilinc, a supply chain data monitoring company. On the positive side, Vakil believes that because we now have so much more data, artificial intelligence, machine learning, and predictive analytics, we're far better equipped to manage the many risks we face.
Risk is fundamentally a data issue. We need to invest in capabilities that reduce it, such as predictive analytics to anticipate and plan for different scenarios. Then we must translate this information into revenue impact and prioritize accordingly.
This starts with identifying your most mission-critical resources, then setting up a solid supply chain for those and being flexible about the rest. Keep in mind that mission-critical does not necessarily mean most expensive. Although we're conditioned to think about our supply chain in terms of spend, it's often the low-cost items that can bring us to our knees.
Collecting data on all your suppliers and applying a risk algorithm to determine which are financially risky is essential, too.