Inventory Replenishment Planning – How much should you buy?
By Richard F. Vaccaro, President and CEO, Valogix, Inc.

This is the third article in a series covering new techniques in Inventory Planning and Management.
The first article entitled, New Advanced Inventory Planning Technology – Generates Positive Cash Flow, covered the new, affordable technology that automates the entire planning and replenishment process, saving substantial time and money. The second article published in April of this year entitled, Inventory Forecasting – The Beginning or End of Planning? covered the importance and proper use of demand planning.

This article continues the inventory planning process flow by discussing Replenishment Planning. Note: The terms replenish and replenishment in this paper refers to both buying and internal transferring of inventory.

Basic Inventory Planning - The 40+ Year Old Model
The diagram below illustrates the most basic model of the inventory planning process.

When the item's inventory level falls below a "reorder point" (min), an order goes to the item supplier for a "reorder quantity" (max). Because it may take some days (lead time) to obtain the item, the reorder point must be greater than zero. The replenishment arrives and then the saw tooth pattern repeats until inventory falls below the reorder point again. Actual demand is never as steady as the diagram above suggests.

The second diagram shows a more typical situation.

"Safety stock" is required to account for randomness in demand, uncertain lead time, and review periods. The concept of a reorder quantity determined by "order-up-to" level" is typically applied.

The problem: A planner or planning system working on a weekly review cycle, for example, may not notice that the inventory fell below the reorder point until some days later.

Common Approaches to Calculate the Inventory Control Parameters
How should a planner set the reorder point and reorder quantity (or order-up-to level) for thousands of items, perhaps at multiple locations? Due to the absence of an 'intelligent' planning system, three commonly used approaches have been Brute Force Review, Economic Order Quantity, and periods of supply.

In Brute Force Review, planners examine each item at each stocking location and manually set the min and max controls. This is such a time-intensive process that the results get out of date, yet nobody has the time to update them. Moreover, without good tools there is no guarantee that the controls will be set well even at the start.

Economic Order Quantity (EOQ), a simple calculation of the reorder quantity as a tradeoff between the cost of carrying inventory and the cost of placing an order, is another commonly used approach. Frequent re-orders minimize inventory holding, but incur high ordering costs. Likewise, buying in quantity reduces the ordering cost, but results in low inventory turns and high carrying costs. Although EOQ calculations are frequently available in Enterprise Resource Planning (ERP) systems, planners have difficulty determining the two driving parameters, order cost, and inventory holding cost.

Another common approach is to apply "periods of supply" for the max quantity. For example, average demand may be 120 units per week over the last four months. Taking 2 weeks of stock for the min and 8 weeks for the max, this approach would calculate min of 240 units and max of 960. Such an approach has the advantage of being easy to calculate. Although it is safe for high volume items, it works poorly for low and medium volume items.

The biggest problems with both EOQ and 'periods of supply' are neither of them: 1). fully considers the real potential or level of a spike in demand; 2). the impact of short life cycles; or 3). the timing of trend or seasonal changes. These inefficiencies combined with situations where the planner may not have a system that handles 'every' item requiring to be planned, accounts for the over or under buying that occurs daily.

Improving Replenishment Planning
Intelligent replenishment planning includes several components, of which forecasting is just one element. Complete automated planning systems handle all behavior including low volume items as part of a total process. Advanced planning solutions also incorporate inventory optimization, which dramatically improves replenishment planning, making it highly effective. Why? Because optimization considers the wild cards in planning, e.g., how random the demand of an item is, i.e., standard deviation and service level objectives, and it does it for each item at every location, leaving nothing to chance.

Time-phased planning examines a sequence of periods, looking at projected demands and replenishments, and determines both the timing and quantity of future orders.

Other factors that should be included in the calculations are: