May 17, 2017
Alek Test Post
Incorrect levels drive excess inventory
It may seem a bit obvious to say that incorrect levels can lead to excess inventory, but let’s dive in on this for just a minute. Levels are determined by various planning inputs, and it’s those inputs that need to be examined. No matter the applied methodology in calculating levels, if the inputs are off, the end result will also be off. To fix incorrect levels and refine the inventory planning process, we need to check the inputs first.
Before the reign of the desktop computer, most businesses relied on simple processes to determine their inventory levels. Often, a planner’s gut feeling provided most of the ordering insights; something like “there’s a big order coming in so let’s plan for that” or “these bins are looking a little light, let’s top them off.” As companies and supply chains grow, more people get involved and more complexities are on the table. For now, let’s characterize these complexities in two main camps. First is a “re-order level” that defines when re-ordering should occur. Second is an “order-up-to level” that defines the quantity up to which should be ordered. Crunch this number: current stock minus any commitments plus any stock coming. Then compare that to the “re-order level” — if the item is below that level, it’s time to place an order that hits the “order-up-to level.”
The factors that go into these levels are the buffer stock (aka safety stock), the lead time (LT) and the replenishment cycle (RC). The resulting order should be modified by the minimum order restraints or order multiples, of course, but these restrictions shouldn’t be factored into level calculations at the risk of making the levels too high. It’s usually best to make these measurements in terms of days, but measuring in weeks may be more appropriate in some instances. Other demand streams that may apply could include sales orders, manufacturing demand (MRP) and/or other warehouse requirements (DRP).
Earlier in the crash course, we zoomed in on the importance of lead time. It is critical to stay on top of product lead times, including the status of ongoing orders that are en route, so that no unnecessary orders are placed. The way lead time interacts with safety stock is key, as well.
For example, if a supplier delivered the exact quantity needed at exactly the right time, without fail, and that perfectly corresponds with the timing and amount of all customers, then there wouldn’t be a need for any safety stock. Even if the lead time was quite long, a planner could make that work without safety stock. But that’s simply not how real life works in the supply chain, and it highlights exactly why safety stock calculations are so critical. Suppliers aren’t that reliable and customer demand isn’t that predictable, which means safety stock is a necessity to bridge the gaps as they occur.
Additional concerns to factor in here include order cycle and lead time. These are the must-have inputs that go into calculating the safety stock levels that correspond with different fill rates; the higher the ideal fill rate for a product, the higher the safety stock should be. The most important products will need the highest fill rates, and that means holding additional safety stock is probably necessary.
Furthermore, if two items had the same target fill rate but very different supplier risk, they would also have very different safety stock levels. It is this sort of dynamic approach that allows you to cover each item based on its own unique profile and reduce the overall investment while improving customer fill rates at the same time.
With bad inputs, the process is going to be out of whack, regardless of the tools used to forecast. A quality tool will help a planner identify places where data purity can be improved so the tool will work better. For those on spreadsheets doing calculations as best they can, there is no hope of improving the data. Weak data purity is not a reason to keep using the same old process and tools; it’s a wake-up call to improve the warehouse and the business.
With excess inventory, business growth is stymied. With a balanced inventory, a business is free to grow and tackle new opportunities. Achieving that balance can be complex, as we’ve seen while examining forecasts, new items, supplier constraints, and incorrect levels.
Relying on outdated tools and methods is guaranteed to prevent a balanced warehouse. What do you need to improve your inventory? How does your current process use and manage the complexities we discussed throughout this course?