Most transactional supply chain activity can become automated. Automation coupled with cognitive computing’s continuous self-learning handles increasing complexity and helps the supply chain be more dynamic, flexible, adaptive and efficient. Digital technology platforms can deliver real-time data feeds. Analytic modeling converts multiple data into real-time insights to inform decisions. This allows operational resources and management to focus on what the engine is solving for, continually adjust it per business goals, and resolve issues where and when needed.
Companies need to employ an integrated model that breaks down existing silos and connects all functions—from planning to execution. Capabilities need to be realigned so that the entire value chain works together to achieve specific business and customer segment outcomes, which will continuously vary. These outcomes include improvements in costs, inventory, quality, customer service or asset utilization.
89% of supply chain executives report that customers see their current operating models as too complex, and for half of them, “decision-making speed” and “flexibility to respond” are key sources of that complexity.
Current supply chain skills are often functionally-specific. Future operational decision making can be enhanced by people who understand cross-functional, end-to-end dependencies or the financial and operational impacts of respective decisions. Today’s data explosion presents opportunities to gain deeper insights into market trends and digital consumer behaviors, i.e., scenario modeling with predictive analytics. Additionally, supply chain network planners can use insights to adapt plans and address issues as they occur.
85% of supply chain executives report already considering outsourcing portions of their supply chain. “Logistics and distribution” (52%) and “supply chain analytics” (49%) are the areas considered most.
Shifting in-house capabilities to a broader ecosystem allows businesses to leverage capabilities and potentially resolve problems faster, seize growth opportunities and enhance the customer value proposition. Collaboration on social platforms enables interaction with colleagues and ecosystem players to share qualitative information and up-to-the-minute quantitative data from supply chain systems. Sharing, discussing, reviewing and approving scenarios as they occur speeds execution. Sales and operations planning processes can be in virtually real time.
Unlike today’s model, the supply chain of the future is not built for high volume and only a few SKUs. Rather, it is structured to serve the unique needs of each customer, patient or consumer. As supply chain operating models become more granular, they are better able to deliver customer personalization by channel, service level and even market area. This enhanced, deeper segmentation enables improved inventory placement that can facilitate improved sales in an optimized cost structure.