Demand-driven Inventory Replenishment Planning
As per the world reports of global goods shortages, optimized replenishment planning with demand drivers, has become a necessity. A Demand-Driven Inventory Plan enlists both strategy and execution for resilience and profitability in the midst of economic upheaval. Planning for demand while ensuring order fulfillment and waste elimination are the components of a successful replenishment plan.
Supply chains across the world are facing unusual levels of demand fluctuation, making it critical to regulate the road to replenishment management in supply chains. The pandemic led to an escalation in demand for different categories of products, which supply chains managed to meet. However, markets and vendors struggled to fulfill this demand the second time around. Fluctuations in demand caused a series of changes with 25% of supply chains delivering goods consistently late and 38% performing unevenly. The second and third waves of the coronavirus pandemic have enhanced the need for resilience in supply chains and through it – efficient replenishment planning.
Demand forecasting is a means to not just anticipate demand, but also strengthen systems that cater to this demand. Replenishment planning with a demand-driven module ensures inventory optimization, reduces rework, and eliminates bottlenecks in the supply chain to enhance resilience.
Need for Replenishment Touchpoints in Supply Chain Management
Triggers and touchpoints across the supply chain can lead to optimized replenishment planning with minimal monetary investment.
The touchpoints can indicate the need for expedited procurement, new vendor relationships, or enhanced delivery speeds. They also are indicative of internal levels of inventory, orders, and demand across the supply chain.
External Replenishment Triggers
External replenishment triggers are those that exist outside the control of supply chain managers. These are generated due to external factors that are difficult to anticipate and automate. It is essential to monitor these due to their advanced degrees of influence on replenishment planning.
External replenishment triggers constitute elevated demand due to seasonality peaks and global trends that might lead to enhanced variability in the supply chain.
Internal Replenishment Triggers
The need for internal replenishment triggers is as crucial as external ones. It is also beneficial to monitor them closely to ensure minimum inventory with high levels of service.
Projected stock levels
Stock levels need to be projected with accuracy, and inventory has to conform to these projections. Accurately projected stock levels can optimize replenishment and eliminate wastages.
Vendor Delay Cycles
Since vendors are an important part of the supply chain and the inventory replenishment network, their activity patterns need to be gauged. To optimize demand-driven inventory replenishment planning, it is important to optimize delivery cycles across vendors serving the supply chain.
Warehouse Stock Levels
The warehouse stock levels are a key indicator of how demand fulfillment will unfold. Warehouse stock levels need to be matched closely with demand forecasts, sales orders, and reorders.
5 Inventory Replenishment-Planning practices to drive profitability
Effective replenishment planning can drive sales and considerably amplify profits. Demand-driven replenishment planning can be rendered effective by enhancing internal supply chain touchpoints.
Warehouse management is integral to all supply chains, especially at the replenishment level. To ensure that backflow in the supply chain doesn’t drag all the way back to raw material procurement, it is necessary to monitor intermediate checkpoints such as warehouses, transport operations, and so on.
Warehouse management can be optimized greatly through hyper-automation across warehouse workflows, floor lays, and inventory. Hyper-automation in warehouse management coordinates shipping with order schedules to establish touchpoints in the supply chain. This practice leads to faster replenishment operations enabling demand-driven replenishment management.
Process-oriented replenishment planning can be a game-changer in optimizing supply chains due to the inherent accountability of the system. Determining lead times is a key component of process-oriented supply chains. When lead times are accurately determined, they can cut down communication delays and reorder fulfillment in a demand-driven network.
Vendor delays affect all channels of the supply chain, from procurement of raw material to sales order fulfillment. Accounting early for vendor delays can ensure rapid back-order fulfillment and cutting down time-lapses in inventory replenishment planning.
Internal supply management, if optimized via automation, tracking, and demand forecasting, can greatly optimize replenishment management. Where all cogs in a system work well individually, the system becomes more efficient.
Enhancing Supply Chain Visibility
Enhanced supply chain visibility can highlight gaps in the supply chain where leakages of time and resources might take place. Automating both the communication channels and the supply channels in the supply chain will lead to faster replenishment. Demand-driven replenishment planning can only be carried out in a supply chain with high degrees of visibility. Transparency in supply chain operations leads to efficiency in order-fulfillment, demand forecasting, projecting warehouse levels, and internal stock levels.
Leveraging Machine Learning and Artificial Intelligence (AI)
Supply chains trapped in legacy systems of replenishment planning are struggling to scale in a world largely governed by AI. AI in Supply Chain can create feedback loops between demand, inventory, and sourcing, enhancing supply chain operations.
These feedback loops also eliminate bottlenecks by providing accurate data moving forward. Demand-driven replenishment planning becomes a by-product of effectively leveraged AI and machine learning in supply chain management.
Machine learning can group data about sales orders, seasonality peaks, and demand history into a comprehensive format. These comprehensive insights can then be employed to ensure accurate demand-driven replenishment planning.
Gone are the days where sales patterns could be reviewed quarterly to anticipate demand for the coming quarter. With multiple players entering the same markets and e-commerce platforms providing purchase suggestions by the second, real-time forecasting has become crucial. Forecasting demand in real-time can lead to an updated and automated supply chain, eliminating bottlenecks and unnecessary delays or halts.
Real-time forecasting directly feeds the demand generation in replenishment planning while also gathering input independently.
Solutions for profitable Replenishment Planning
ThroughPut’s AI Solution aligns with demand drivers to ensure the reduction of surplus inventory and lead times. Employing machine learning, ThroughPut’s AI solution can ensure expedited replenishment, which is fed via a demand-forecasting model. To access the complete suite of services offered by ThroughPut, book a demo here.