Manufacturing Analytics in the Age of COVID-19

Many manufacturers are facing planning problems, scheduling challenges or both. SAS can help by enabling your planners to boost productivity and unlock new possibilities. We can enable your schedulers to maximize results despite extensive constraints. And we can help make tackling unique challenges – such as reducing the number of employees on a shift to maintain safe distancing requirements or preventing crossover of employees between lines or plants – more manageable. Software and services from SAS can help you create plans for:

• Supply – Where to purchase raw materials.
• Allocation – How to resolve constraints in the context of limited supply.
• Line optimization – What to produce, on which production line, in which order and with which team members.

Significant changes in demand patterns and constant market disruptions have many manufacturers struggling to stabilize end-to-end supply chains. SAS can help you take a comprehensive approach to supply chain planning so you can:

• Provide the best response across your end-to-end supply chain using an optimization model that balances supply chain costs and constraints with meeting sales goals.
• Create consistent, synchronized plans for purchasing, inventory, transportation, sales and manufacturing.
• Run multiple scenarios for demand forecasts based on different recovery expectations, or potential markdown and promotion strategies.
• Capture effects across your entire product portfolio, including regular, perishable and seasonal goods

You're facing the critical challenge of how to predict and plan for significant changes in demand. SAS can help you improve demand sensing decisions across the supply chain – in the short term during the disease outbreak; in the midterm during the recovery period; and in the long term once the pandemic has subsided – with:

• Analytical recommendations for improving demand forecasts across all phases of the pandemic.
• Powerful data preparation capabilities for capturing both internal and external variables in forecast models.
• Machine learning algorithms to quickly assess demand shifts and automatically learn over time as new data is available.
• An iterative framework – from data to analytics to insights – that drives agile, improved forecasting decisions during times of uncertainty.

With limited production of supplies, companies around the world have worked quickly to find alternative suppliers of critical goods similar to what they normally purchase. Sometimes they've overpaid for those supplies or been exposed to risk from bad players who are abusing the situation. It's now apparent that many supply chains were overdependent on certain suppliers or were not well balanced. Some have even found that they’ve overlooked instances where they were fully dependent on a sole supplier for specific goods. SAS can help you ensure the integrity of your suppliers through continuous monitoring and analytics so you can:

• Conduct due diligence around critical suppliers.
• Comply with contractual conditions.
• Accurately analyze procurement spending.
• Optimize supplier choices in situations that demand fast, continual supplier onboarding.