Cycle stock (inventory), which can be also known as "working stock", "lot-size stock" or "base stock", owes its name to its periodic nature. Cycle stock is the amount of inventory needed to meet normal demand during a given period. It is the portion of inventory determined by batch activity, meaning its purpose is to specifically satisfy regular sales orders based on demand forecasts, so it doesn’t include the amount of “safety stock”, nor it predicts an excess stock to arise.
Average Cycle Stock Under Conditions of Constant Demand
The interval starts with the cycle stock being at its maximum, which assures inventory (lot size) is big enough to meet customers’ needs for entire period – [Q]. At the end of the interval, after we have met the demand, cycle stock reaches its minimum – . The averages of these two extremes is what is called average cycle stock:
- (Q+0)/2 = Q/2
Inventory Reduction Tactics for Cycle Stock
The primary method to reduce cycle stock is just to reduce the lot size in the supply chain. However, such cutback could be disastrous if no additional changes are made as, for instance, ordering costs can escalate. In such case, there are two strategies proposed to be used as a solution:
- Reducing ordering and setup costs by streamlining the methods for placing orders and making setups:
By doing that we can allow the lot size (Q) to be reduced. This could be done also by redesigning information flow’s infrastructure or by improving manufacturing processes that can lead to reducing costs of the above.
- Increased repeatability:
The practice of doing the same work again, whether it is in the supply chain or in the manufacturing process, can lead to reducing or even eliminating the need for changeovers. Increased repeatability can result in reducing transportation costs, granting quantity discounts from suppliers or establishing new setup methods. Increased repeatability can be achieved on account of:
Finding Economic Order Quantity (EOQ) for Cycle Stock
- The demand rate remains constant.
- There's no limit to the size of each batch (e.g. truck capacity, materials handling limitations).
- There are only two significant costs – the inventory holding cost and the ordering or setup fixed cost.
- Decisions can be made separately for each item.
- The lead time remains constant and the amount received arrives as ordered in one batch.
Such ideal situations are very rare and it is important to remember that EOQ was never intended to be an optimizing tool. Nevertheless, the EOQ still can be quite helpful in finding a reasonable approximation when not all of the above apply.
These are the guidelines for using or modifying the EOQ:
- Use the EOQ:
- If there's a quite stable demand for an item and the "make-to-stock" strategy is applied,
- If the inventory holding cost and the ordering or setup cost are relatively stable and certain.
- Do not use the EOQ:
- If the customer specifically asks for the entire order to be delivered in one shipment and the "make-to-order" strategy is applied,
- If the size of the order is limited, for example by capacity limitations or the number of delivery trucks.
- Modify the EOQ:
- If ordering larger batches benefits in significant quantity discounts,
- If the replenishment of the inventory is not immediate, which can occur when items must be sold or used once they are finished without waiting for the entire batch to be completed.
- Paul D. Larson, Robert A. DeMarais, 1990, p. 28
- Ravi Anupindi, Sunil Chopra, Sudhakar D. Deshmukh, A. Van Mieghem, Eitan Zemel, 2011, p. 126
- Lee J. Krajewski, Larry P. Ritzman, Manoj K. Malhotra, 2012, p. 311-312
- Ibidem, p. 313
- Ibidem, p. 315
- Anupindi R., Chopra S., Deshmukh S.D., Van Mieghem A., Zemel E., (2011) Managing Business Process Flows: Principles of Operations Management 3rd Edition, Pearson, p. 126-131
- DeMarais R.A., Larson P.D., (1990) Physic Stock: An Independent Variable Category of Inventory, "International Journal of Physical Distribution & Logistics Management", Vol. 20 Issue: 7, p. 28-29
- Krajewski L.J., Ritzman L.P., Malhotra M.K., (2012) Operations Management: Processes and Supply Chains 10th Edition, Pearson, p. 311-315
Author: Monika Ptasińska