Economic fallout from the COVID-19 pandemic has illustrated how many companies weren’t fully aware of their supply-chain vulnerabilities to global shocks. The effect has been increased focus on supply-chain optimization, and businesses are investing in forecasting and other technologies to prepare for a post-pandemic landscape that will depend on flexibility and speed.
Effective endeavors will require data-based insight into supply chains both vertically and horizontally in order to identify any binding constraints in materials, production, distribution or other areas.
One of the lessons during the early days of the pandemic was that many forecasting models simply could not adapt fast enough to keep up. Their rigidness led to empty shelves, unhappy consumers and missed revenues.
The initial lack of data made it impossible for businesses to create reliable forecasts in response to the unfolding crisis. This held true for businesses leveraging machine learning or other statistical techniques. In this difficult situation, many companies’ demand planning teams resorted to making manual forecast adjustments based solely on their market view and experience. While this might have been essential in the circumstances, such an approach is often very time consuming and highly inaccurate.
As businesses build more resilient supply chains, forecasting tools will play a major role. Critical Tier 2 and Tier 3 suppliers are beginning to share more transparent data, which allows companies to scale production more smoothly than if data was only shared with a Tier 1 supplier. Or, if a Tier 3 supplier is off-line, all supply-chain partners will know and adapt in real-time.
In addition, machine learning is a critical part of faster, more accurate forecasting. The technology can drive a forecast planning system that’s more adaptable, scalable and able to provide actionable insights from all data sources — no matter how fast or unexpectedly market changes occur.
Outlook
The post-pandemic landscape will see more forecasting solutions that leverage artificial intelligence and machine learning technologies — and higher adoption within supply chains to increase resiliency.
