Replenishment planning is essential in determining the best balance between customer service level and inventory.

Effective replenishment planning enables rapid response to the change needs of customers with the distribution capabilities of a retail organization. For small retailers operating 1-2 retail stores, this process is simple enough to be conducted using excel sheets and rudimentary demand forecasting methods. Nevertheless, the scene shifts dramatically in the case of large retailers operating hundreds of stores and thousands of SKUs. Demand has to be predicted at every store and warehouse level with a myriad of factors affecting replenishment planning.

Factors Affecting Replenishment Planning

Accurate Demand Sensing Capabilities‍

Retailers need a reliable system that can accurately predict the demand at a
Branch + SKU + Category level derived from its individual trends, seasonal patterns, pricing, and holiday effects. It is important for these industries that deal with perishables, fast-moving, and high-demand SKUs to maintain a balance between accurate demand prediction and stock-outs. Demand Sensing reduces demand latency and includes daily PoS data to gain insights and improve service. It also gives demand planners the capability to right-size their SKU inventory by incorporating marketing campaign data, and price changes based on price elasticity, seasonality, and weather.

Assessing Optimal Service Levels‍

Every retail company has to manage its inventory costs. The most common way is to set the desired inventory level and then buy constantly more of a product as it becomes close to being out of stock. This process, if not done efficiently, tends to lock up working capital by overstocking certain products. Optimizing service levels can help solve this problem. Managers should identify the SKUs that bring in the majority of sales revenue and ensure high service levels so they never miss out on sales opportunities for products that are in high demand to ensure earnings.  They can achieve this with  ABC classifications to maintain adequate service levels by classifying the entire SKU group. Class A products bring in the majority of the revenue and 95% of service levels should be maintained for them. In Class B the service level can be 80%-90% and for class C service level can be 75%-80%.

Calculating Dynamic Safety Levels‍

Retail businesses need to maintain a high inventory turnover ratio and thus need to plan their safety stock more to avoid wastage. They need to build a dynamic safety levels plan by assessing lead times, fill rates, shelf life, current inventory levels, open orders, and current safety stock levels. Dynamic safety levels should be assigned based on the demand variability and service level. High dynamic safety levels for high selling products with high demand variability should be maintained and optimizing service levels is a very efficient way of avoiding overstocking inventory and service levels.

Replenishment lead times‍

Replenishment lead time is the lead time between the higher-level node to the lower-level node. Retail companies should focus on reducing the lead times as much as possible. Inventory is required for demand variability, lead time variability, and service levels but lower inventory or days on-hand is a key to a resilient and responsive supply chain.

3 Modes of Replenishment Planning with Kronoscope

Fixed Duration Replenishment Plan

A fixed duration replenishment plan offers maximum flexibility to users to define the replenishment period and offset. Kronoscope users can also override default replenishment lead times from one node to another. Users can set the replenishment duration (or inventory cover days) and offset to generate order recommendations. Nevertheless, users have to review this before the end of the plan period of the previous replenishment cycle and generate transfer recommendations for the next order cycle. Three user inputs are needed to generate a fixed duration replenishment plan.

• Replenishment duration: This is the number of days for which the inventory cover is required
• Offset: This is a specific number of days from the start of the planning cycle to the date of execution for which the inventory levels need to be accounted for.‍
• Replenishment lead time: The lead time between the higher-level node to the lower-level node.‍

‍Fixed Schedule Replenishment Plan

A fixed schedule replenishment plan follows a set schedule for replenishment - transfer recommendations for specific SKU-branch combinations will be generated by Kronoscope on a specific date. Replenishment cover/ duration days is based mainly on order schedule. Transfer recommendations will only be generated on specific days for specific SKUs/suppliers. The replenishment schedule is fed into Kronoscope on the backend. This schedule can be defined at SKU/location/Category level.  Kronoscope automatically infers replenishment duration from the replenishment schedule. If the replenishment schedule is every Thursday, then cover days are automatically inferred as 7 days.

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Dynamic Replenishment Plan

In a dynamic replenishment plan, no user input is required as replenishment norms including duration, cover, and frequency are suggested directly by Kronoscope’s AI engine based on the SKU shelf life, current inventory runway, and safety stock required. This allows the system full flexibility to recommend how stock should move between higher to lower nodes in the network to avoid/minimize loss of sales and prevent overstocking.  

Kronoscope uses a proprietary dynamic norm recommendation engine that uses shelf life, replenishment lead time, and predicted demand to suggest the replenishment quantities and inventory norms (safety stock days, DOH norms) which is optimized for each SKU-location combination. When there are instances where the SKU at a particular branch gets stocked out (or comes close to getting stocked out) this leads to an increase in DOH norm recommended for the next replenishment cycle as previous replenishment cover norms lead to a shortage. Similarly, when an SKU spends too many days in an overstocked situation, the DOH recommendation for future orders is smaller.

This combined with dynamic safety buffers provides the ideal solution for companies looking to build fully agile supply chains. This continuous improvement system is inspired by the Theory of constraints (ToC) methodology of inventory planning. However, we also make this approach much more powerful by augmenting it with demand sensing technology which accounts for future events & promotions, pricing changes, and corrects for historical stock-outs and anomalies.

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