Spare Parts Inventory Management. Phillip Slater
is even worse than that because the answer that is based on guesswork is often cloaked in the guise of management science. It is this guise of management science that helps people pretend that they are not really guessing. But consider the following.
How often have you heard someone justify a position on inventory stocking levels by saying:
• It’s based on the formula, or
• It’s based on our historic data, or
• Our forecast shows . . .
Or something similar?
Often the statement is made as if the statement itself were a full justification. Each of these things may be true (and are based at some level on management science), but they also each involve some degree of guesswork. For example:
• Many people use the wrong formula for determining their stock level; they are guessing that they should use (say) a Gaussian function (most typical) when maybe the function should be Poisson based, or maybe neither.
• Many people have extensive historic data on their spare parts, but that data doesn’t actually reflect the real demand history—though these people are assuming (guessing) that it does. Their data usually reflects the movement of spares out of the storeroom, not the use of those spares on their equipment.
• By their nature, all forecasts are based on assumptions—which, in effect, make any forecast a guess. Even worse, many people don’t even try to determine the likely basis of future demand for the item; they merely extrapolate the past into the future without necessarily questioning if that is an appropriate approach to take. This is the basis of most software packages. The use of software makes it easy to abdicate responsibility for decision making.
• The granddaddy of all guesses is the ill-informed assumption that spare parts inventory management follows the same rules as other types of inventory management. This is the underlying assumption that is at the heart of statements, often made by accountants, that there should be a clear-out of any spare part that hasn’t moved in two years.
Someone once said that all management problems end up in the warehouse. By this they meant that the warehouse (or storeroom) becomes the place that provides the buffer for problems that are actually created elsewhere. These are problems with issues such as the setup of satellite stores, rotable spares management, lead time variability, stockouts, operations engagement, determination of criticality, spare parts availability, management of redundant stock, logistics, cannibalization of spares, and location mix-ups. These issues are “managed” by stocking more inventory than would be needed if the issues were properly addressed.
When considering engineering spare parts, used to support operations through returning failed equipment to a fully operational state, it is fundamental to establishing a reliability and maintenance system that you consider the likely cause of failure and from that the appropriate course of management. Having done that, it ought to be possible to at least state the basis of the future usage of a part—whether that is condition monitoring, time-based replacement, random failure, or some other approach.
By identifying the basis of the forecast, it can then be reviewed for reasonableness or even currency. Yet this connection is rarely made in practice, and the “guess” becomes the basis of the stock holding. The result is that the inventory ends up being overstocked.
The same can be said of the engagement of operations, the involvement of procurement, and the input from finance, where an unchallenged assumption (a guess) results in overstocking.
Why is this so? Well, one answer is that it is easy (or is that lazy?) to not work through all the available information and to use a guess that is disguised as know-how as the proxy for information. A better answer might be that as long as the spare parts warehouse is overstocked, everyone can get away with this approach because it is easier to spend the company’s money on excessive parts holdings than it is to work on developing a more accurate or reasonable stock-holding requirement. It is usually when you tighten up on the wasted expenditure on spare parts, that the failures of the rest of the management system really come to light. By removing the excessive stock, the other systems lose their buffer for relying on guesswork.
There is another old saying along the lines that identifying a problem is half the solution. In this case it might be that identifying (and admitting) that the basis of the estimate for the future use of a part might be really just a guess then helps lead to a better solution. So if the basis of a stocking decision is unknown, or is really just a guess, then be clear and honest about that. Then you can get on with filling in the real data gaps and solving the real problem.
1.6 The Big Picture—Putting Spare Parts Management in Context
Now that the characteristics that define MRO and spare parts inventory are understood, let’s put management of that inventory into the context of the big picture. To do this, consider the reason that spare parts are held—to support the maintenance requirements of your plant and equipment. Once this is understood, it makes sense that understanding the maintenance and operations support activities will help with spare parts planning, and this flows on to stocking levels. (This is discussed further in Section 3.3, “Reliability-Centered Spares.”) Therefore, it makes sense that in order to better understand spare parts management, you need to also understand the basics of maintenance management. The following is not intended to be an exhaustive explanation of maintenance activities but should be sufficient to put spare parts management into context with maintenance.
A Simple Model of Maintenance Activities
Figure 1.2 is a simple model of maintenance activities. At the center of the model is “operational results.” This is the goal for everyone in the company and is about driving your plant and equipment to achieve your production plans. It is not just about minimizing downtime. Surrounding the goal of operational results are four activities that are at the heart of maintenance—they support the achievement of the company’s operational results.
Figure 1.2 A simple model of maintenance activities
Technical
In Figure 1.2, “technical” refers to the technical and reliability engineering aspects of maintenance. Think of this as identifying the work that needs to be done and determining how the goals will be achieved—that is, which strategies and techniques will be applied. Key aspects of this include:
• Identifying which assets are to be maintained. This might also be broken down into the subassemblies and parts level.
• Identifying the potential failure modes of those assets, subassemblies, and parts. Understanding this helps to determine the maintenance management policy that will best address that failure mode and keep the plant running.
• Determining criticality, which helps determine the priority of tasks that are subsequently planned.
• Identifying the appropriate maintenance management policy, which means determining what approach to take for maintenance given the detail set out in the above points. Some options include: