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Chapter 2

The Mechanics of Inventory Management

Simple not Simplistic

The purpose of this section is not to provide an in-depth understanding of all the mechanics of materials and inventory management (there are hundreds of other books that can do that) but rather to revisit or recap the mechanics in a way that puts the rest of this book in context.

Certainly this section addresses some basic elements of materials and inventory management but, as in many situations, the real value comes from looking beyond the basic element and understanding the implications of that formula or process that the element represents. Anyone can look up a formula on the Internet; however, it is an understanding of the nuances that provides value. For example, one of the major reasons that organizations have so much difficulty with materials and inventory management is that they confuse simplistic with simple. Although the concepts and formula are simple — in that they are readily understood — they should not be thought of or applied in a manner that is simplistic, that is, free of any complicating factors.

Too often people take the basic concepts and formula and do not think through the complicating factors when implementing the concept or formula. This does not mean that we need to make things overly complex; it just means that we need to understand the implications of our choices. This section aims to provide some insight to assist in that understanding.

Materials or Inventory?

One of the most common confusions of terms is that between materials and inventory. Many engineers, in particular, concern themselves with materials management but show little interest, and sometimes don’t want to be involved in, inventory management. However, when subject to some scrutiny this does not make any sense.

Materials are the physical parts and components and materials management is concerned with the logistics associated with the procurement and supply of those materials in a timely manner. Inventory is the gathering of those materials in order to provide a ready supply when they are needed. Inventory can also be defined as those parts purchased for future use without knowing exactly where and/or when the part may be used.

Inventory management, therefore, is a subset of materials management as it is primarily concerned with managing the procurement and supply of those materials held as inventory. Anyone who is involved in materials management must therefore have an interest in inventory management if their materials are being held for future use. Inventory management is much more than just managing the storeroom.

Relevant Terms and Expressions

Before working through the rest of this book and to ensure a common understanding of some relevant terms and expressions, review Table 2-1, which shows the most immediately relevant terms and expressions, and Appendix A, which contains a comprehensive glossary of materials and inventory management terms and expressions.

Term	Definition
Cash flow	The net gain or loss of cash in a business through its business cycle.
Inventory	Materials and spare parts that are held for future use without knowing exactly where and/or when the item will be used.
Lead Time	Measured from when the ROP is reached to the actual physical restock.
Materials	All items that are purchased for use in, or for supporting, manufacturing and engineering activities.
Max	In some systems, this is used to determine the reorder quantity when the minimum is reached.
Min	In some systems, this is both the safety stock level and the reorder point.
Reorder Point	The trigger point for reordering stock (ROP).
Reorder Quantity	The quantity to be reordered when the ROP is reached (ROQ).
Safety Stock	An allowance for both demand and supply variations during the lead time to restock.
Stock Keeping Unit	Refers to any individual inventory item; also known as an SKU.
Stock turn	The number of times in a year that, in theory, the inventory is completely repurchased. Higher is better.
Storeroom	The area for storing the inventory; sometimes referred to as the warehouse or the store.
Stores	Sometimes used as a synonym for inventory.
Working Capital	The cash invested in inventory.

Table 2-1: Relevant Terms and Expressions

What is the Purpose of Having Inventory?

Before moving on to develop an understanding of how to manage and optimize inventory, it must first be recognized that inventory exists for a purpose. In fact there are three main reasons that companies invest in inventory:

1.To enable supply in a timely manner.

Companies invest in inventory to ensure that the item is available when needed. The investment is based on an assessment that without the inventory there will be a loss of profit due to missed sales. This is true even for spare parts where equipment downtime may ultimately result in a lost product sale — obviously not all customers are willing to wait for delivery.

2.To provide purchasing/manufacturing efficiencies.

Order quantities and batch sizes sometimes force companies to buy more than they need or want in the short term. In this case, they invest in the inventory in order to avoid the extra cost associated with small quantities or batches. (See also Chapter 6: Issues, Myths, and a Few Home Truths.)

3.As a temporary measure to accumulate stock prior to major events/projects.

The major event or project could be a marketing program or an engineering upgrade. In either case, an investment is made in inventory because there is only a small window of opportunity in which to use/move the parts and it is considered that the supply chain cannot provide the quantity of parts required in that window of opportunity.

In all three cases, the real driver for investing in inventory is to minimize the risk of other potential costs or losses. Therefore, it is essential to continue to think of inventory as an investment made with the purpose of minimizing risk.

Why Spares and Indirect Inventory Are Different

While the process and actions discussed in this book can be widely applied to many types of inventory, they are particularly effective on spare parts and indirect inventory. Indirect inventory can be defined as the stock of all the “bought in” materials that companies might use. This includes parts and components (in assembly operations), finished goods (for wholesalers), service parts, OEM spares, operating supplies, engineering spares, industrial supplies, and MRO (maintenance, repairs, and operations) parts. Conversely, ‘direct inventory’ is those materials that a company controls and manages along its own supply chain. This includes work in progress (WIP) and finished goods that are created by the manufacturer.

When most companies (or consultants!) work on improving the management of spares and indirect inventory, they typically fall back on the solutions that are applicable to direct inventory. These solutions are well known and proven for direct inventory. However, when it comes to indirect inventory they do have one fatal flaw — they are applied in a ‘one size fits all’ approach. This works perfectly well with direct inventory because large quantities follow the same supply path and have reasonably predictable usage, but this is not the case with spares and indirect inventory.

There are in fact six reasons why spares and indirect inventory are different and why the ‘one size fits all’ approach does not work.

1.The demand is less predictable.

With most types of inventory, demand forecasting receives a huge amount of attention. With stable and predictable supply chains, an accurate forecast is seen as being the best way to manage inventory. In these cases a forecast that is wrong by 10–20% can cause significant problems. However, with some spares and indirect inventory, the demand could vary by 100% and this would still be acceptable. Consider an engineering spare where the usage is twice what was expected or where there has been no demand, yet the item is kept in stock. Managing this order of magnitude difference in predictability requires a different approach to spares and indirect inventory management.

2.There is usually a large number of Stock Keeping Units (SKUs).

It is common for organizations that are managing spares and indirect inventory to have thousands or tens of thousands of SKUs. There are few manufacturing organizations that can claim to have that number of SKUs in their direct inventory.

3.The supply characteristics may be different for each and every SKU.

In addition to the large number of SKUs, another attribute of spares and indirect inventory is that the supply characteristics of each and every SKU may be different. The items will, almost certainly, come from a wide range of individual suppliers and rarely does an organization purchase sufficient quantities of a single item to be able to dictate the logistics of supply.

4.The value and volume of SKUs varies greatly.

Not only is there a large number of SKUs with different supply characteristics but also the value of individual items and the volume of individual items will vary significantly. With spares and indirect inventory, management must be able to economically order, receive, handle, and store components that cost a few dollars and components that cost thousands of dollars — all with the same system and approach. Some of those components will be supplied in ones or twos and some in the hundreds. Again there is significantly greater variation than with direct inventory.

5.Stockout costs can be disproportionately high.

When a company runs out of direct inventory, the cost of that stockout is generally limited to the profit margin from the sale that is lost. With spares and indirect inventory, stocking out of a two dollar component may result in thousands of dollars in lost production. This potential for significantly disproportionate costs for a stockout drives many companies to overstock spares and indirect inventory ‘just in case.’

6.In some circumstances a low stock turn may be acceptable.

A high stock turn rate is a goal for most inventory management. This figure can be used as an indicator of the efficiency of inventory management. However, with spares and indirect inventory, it is sometimes acceptable to have very low stock turn rates. In those cases, the low stock turn rate is usually a function of the unpredictable demand, the high stockout costs, and long lead times for supply. Companies should always seek to maximize their stock turns. But they also need to recognize that an acceptable stock turn for one type of inventory may not be acceptable for another.

The degree to which any one of these issues impacts an organization depends upon the organization’s individual circumstance. However, one thing is certain. With this number of issues to differentiate spares and indirect inventory from direct inventory, the solutions used for direct inventory management cannot be applied in a ‘one size fits all’ fashion to these types of materials.

An Introduction to the Materials and Inventory Management Cycle

Materials and inventory management involves much more than just reviewing the maximum holding level and checking items into and out of a storeroom. Materials and inventory management involves a cycle of activity that starts when the initial need for an item is recognized and then works through setting parameters, procurement/ordering, delivery, storing, issuing, and reordering. This Materials and Inventory Management (MIM) cycle is shown schematically in Figure 2-1.

Notice that each of the steps in Figure 2-1 has an arrow that feeds back into the step in which it originates. This arrow indicates that an internal process exists for that step; it is shown to indicate that at each of these steps the decision making is not a simple one dimensional activity. At each of these steps there are a number of internal processes and even individual behaviors and biases that can and will affect the outcome of that step. In addition there is the internal activity of Return to Store (RTS) that can short circuit the rest of the use–reorder–restock cycle. Although this figure is a simplified representation of the materials and inventory management cycle, it demonstrates that inventory management is anything but simplistic. This point is discussed in greater detail in Chapter 4: People and Processes.

Figure 2-1: The Materials and Inventory Management (MIM) Cycle

Comparison of Theoretical and Actual Inventory Management and Control

Inventory management and control refers to the actions associated with keeping the stock level of a particular SKU within predefined parameters. Figure 2-2 shows a classic ‘saw tooth’ diagram representing the theoretical movements of an SKU as it is used and reordered. In this diagram, the x-axis represents elapsed time and the y-axis represents the quantity on hand. This figure also shows how some of the definitions mentioned previously relate to the classic saw tooth representation.

The key simplifying attributes of the theoretical model are linear demand (that is, constant and equal demand over time) and instant and complete replenishment. In theory, when demand hits the reorder point (ROP), an order is placed for a predetermined quantity without need for further reference to the users of the item. There is then constant consumption over the lead time while the items are delivered. All items are delivered in one delivery so the item is completely restocked. The theoretical maximum is the Safety Stock level plus the ROQ. In the event that delivery takes longer than expected or there is greater demand than expected during the lead time period, then the quantity on hand dips into the safety stock (which is OK) and the item is completely restocked during subsequent cycles.

Figure 2-2: The Classic Theoretical Saw Tooth Diagram

The problem is, of course, that reality almost never looks like this. For engineering and spare parts, the chart in Figure 2-3 is far more representative. This graph has four characteristics that separate it from the theoretical profile. These are noted as A, B, C, and D on the chart and explained subsequently.

Figure 2-3: Actual Component Demand/Supply Chart

Point A: For this particular component the decision was made to set the initial parameters with an ROP of zero. That is, there is no safety stock. This level is more common for engineering materials and spare parts than many people realize and is not presented here to suggest that this ROP is either right or wrong. It is mentioned because this does not fit the common simplistic theoretical model that insists upon safety stock.

In this specific case, the ROQ was set to 10; hence, the theoretical maximum is 10 (ROQ + Safety Stock). Notice, however, that for the majority of the elapsed time in the chart the actual holdings are much higher than 10. Also, as the holdings rarely reach zero, there is nothing to suggest that setting the ROP at zero is inappropriate. Curiously, there are two instances where the holding increases without having reached zero — this is a clue to what is really going on, which will be discussed shortly. Thus, a traditional review of the ROP and ROQ would provide no improved understanding of how to manage this inventory item because the other elements of the MIM Cycle have far greater impact on the result than just the basic ROP and ROQ settings.

Points B and C: Notice that for this item there are long periods of no movement followed by short periods of multiple movements. Compare this to the theoretical model that assumes a constant and linear usage of items. The difference with the actual profile tells us that the average demand value that is so often used would vary enormously depending upon the point in the timeline at which the snapshot is taken; it is not constant or linear.

It is also interesting to note that the item is expected to be used in sets of 10 (hence the 10–0 setting). Yet of the nine issues of stock within the time line, only three are for the full set of 10. Clearly the management of this item requires insight beyond the obvious idea of setting a simplistic maximum and minimum.

Point D: Now notice the large spike in holdings on the right hand side (at the end of the timeline). This is the real issue with this particular component that was alluded to previously. This spike did not result from additional purchasing, but from a massive and sudden return to store (RTS) of items previously removed. Thus the apparent cycle of usage at point C was not usage at all (although the items were definitely removed from the storeroom). The purchases that were made to replace these items that were not actually necessary. (However, this was not known by those doing the purchasing; they were following their process.) The problem was that the maintenance people who removed the items did not advise anyone that they were not used (or that they may not be used). So, when they eventually had a cleanup and returned the items to the store they were now overstocked, compared to the theoretical maximum, by 21 items or 210%!

This example shows that the theoretical model and the actual situation can be sufficiently different so as to make the application of simplistic solutions not only pointless, but also even dangerous to company finances. A smart inventory solution is to ensure that the influence and complicating factors of all the elements of the MIM Cycle are considered for their impact.

Determining the Re-Order Point (ROP)

Now that some limitations of materials and spares inventory management theory are recognized, we must also acknowledge that someone must at some time determine when to order more stock. Deciding when to reorder requires calculation of the Reorder Point or ROP.

A number of different approaches are used to calculate the ROP, but once again a simplistic approach will not provide the best result. Calculation of the ROP requires consideration of a number of characteristics which help determine the approach that is best for that specific inventory item. Considering these characteristics is a reality that is missed by many software solutions that use just one approach. (Recall the previous discussion that the word inventory is used a collective noun to describe all the items held, although an inventory is actually made of many separate items that each have their own distinct characteristics).

In determining the ROP, the three main characteristics to consider are the level of demand, frequency of demand, and the probability and impact of a stockout.

Level of Demand

As we saw in the example above, demand is often represented as a perfectly linear equation. However, a linear outcome is more usually not the case. It is the variability in the level of demand that adds complexity to the calculation. This is why forecasting of many inventory types is such a widely-studied discipline. In order to calculate the ROP, you must understand the variability in the demand, not just know the average demand. Here’s why.

If the demand for an item is always for the same quantity on each demand event — for example, one electric motor or a set of four spark plugs — then a Poisson distribution is the most appropriate statistical model. (See Figures 2-4 and 2-6 for a summary of different statistical models). Note that at this stage we are considering the quantity, not the frequency, of demand.

If, for any demand event, a variable number of items may be required (for example 3 one time, 2 the next time, 5 the next time), then a Gaussian (or normal) model would be more appropriate. Without understanding both the level and variability in demand, you cannot select the most appropriate method of review.

Frequency of Demand

If the item in question has infrequent demand (sometimes referred to as slow moving), then there will most likely be insufficient data to use a Gaussian model. Again, a Poisson model will be most appropriate. Conversely, high levels of demand will lend themselves to a Gaussian model.

A word of warning: be sure to understand the demand pattern over as long a period as possible. As we saw previously, demand data in a short time frame can be misleading.

Probability and Impact of a Stockout

Strictly speaking the probability and impact of a stockout are two characteristics, but here they are treated as one decision variable because they actually give each other context and are often misused.

The probability/impact decision is often used by practitioners as a reason (or excuse) for overstocking their inventory. The argument that is most often used is that the impact of a stockout is so costly that it overrides any consideration of the cost of the items stocked. This is especially so in industries where the cost of operational downtime is high. However, stocking more than might be needed based on physical limits or probability is pointless and a waste of money. (See also the section in Chapter 5: When is Critical Really Critical?) In terms of calculating the ROP, the probability/impact decision affects the service factor component of the calculation. It is, in effect, a risk decision.

Using a Gaussian model, the service factor is a part of the safety stock calculation (see Figure 2-4) and the values can readily be looked up in widely published tables. Figure 2-5 shows a sample calculation of the ROP using a Gaussian model.

Using a Poisson model (Figure 2-6), there is no explicit service factor and the risk element is accounted for in the probability part of the model. Here’s how that works. The Poisson function calculates the probability of a certain level of demand over a period of time. If you set that quantity as your ROP, then the probability can be treated as your service factor. Your risk of a stockout is 100 minus the probability of that level of demand.

So, if you look at Figure 2-6, the probability of 7 or fewer demands is 96.4%. Therefore, the risk of a stockout, if you have a reorder point of 7, that is — the risk that there will be more than 7 demands during the lead time for restocking — is:

100 − 94.9 = 5.1%.

The major issue though with the probability/impact decision is the Service Factor Trap. The service factor is the percent of time that the storeroom can supply the required item when it is needed. So a theoretical service factor of, say, 97% sounds high, but in reality for engineering materials and spares, this may not be acceptable.

First, if measured across the entire inventory, no one will care about the 97% figure if the 3% includes critical parts and your plant is shut for a week while they get air-freighted in!

Second, you can have a high overall service level and still be significantly overstocked in individual items, meaning that you have still spent money on items that are not needed.

This is the Service Factor Trap. It can be misleading in terms of the inventory being able to fulfill its actual requirements and in terms of how efficiently money has been invested in inventory. Sweeping statements relating to service factors are convenient and reassuring, but add no real value to the practice of materials and inventory management.

The impact characteristic also depends upon where are you located. Consider a situation where a machine will not run without a specific part. Without doubt, this part would be considered critical and the impact of a stockout significant. However, if you are in an urban center with lots of suppliers close by you, may be able to convince one to hold the part for you and then get the required part delivered within an acceptable time frame – for instance while you remove the failed part. However, if you are located in a remote area where delivery takes days, then the stockout has more significant implications. Both situations have the same probability of failure and at one level the same impact — that level is the plant stops. However, the real impact is different if the full materials management cycle is taken into account. The one size fits all solutions that get rolled out to every situation do not bring the required results.

Location, culture, operating mode, financial status, reliability, and risk tolerance are all things that need to be taken into consideration when determining the ROP.

Figure 2-4: The Normal or Gaussian Distribution

Notes:

1. This calculation uses a Mean Average Deviation (MAD) rather than a Standard Deviation. MAD is a simplified way of determining the deviation and is calculated by determining the average value by which demand deviates from the mean, in absolute terms.

2. The Customer Service Factor is based on a MAD scale, not the Standard Deviation of a Normal curve.

Figure 2-5: Example ROP Calculation

Figure 2-6: The Poisson Distribution

Determining the Re-Order Quantity (ROQ)

The other key decision for materials and spares inventory management is to calculate the Reorder Quantity (ROQ). The ROQ is usually not so highly discussed as the ROP but it has as much, if not more, impact on the quantity of inventory that is held. This is because the point at which a company actually commits to holding inventory and tying up working capital is when the items are ordered. The classic formula for calculating the ‘economic’ ROQ is as follows:

Where:

Order Cost = the company internal cost for processing requisitions, issuing purchase orders and receiving deliveries.

Demand Rate = the expected demand over a year.

Item Cost = the purchase cost of the item, including delivery costs.

Holding Cost = the financial charge for holding inventory (see Chapter 3: The Financial Impact of Inventory).

Although simple in concept, there are some complications in practice.

1.The order cost is crucial to the calculation.

Of the four variables in the calculation, this is the least simple to determine because there is no set rate. The actual order cost will be different for every company and is dependent upon internal company efficiency, local pay rates, and so on. To calculate the order cost, some companies use an Activity Based Costing approach; some just use an estimate such as $100 per order. Note that it is a mistake to use a simplistic calculation such as the total cost of the purchasing and stores departments divided by the number of orders placed because this assumes 100% capacity utilization. No matter which approach you choose, the key is to understand the impact of an error in this value. From the formula you can see that the ROQ varies directly with the square root of the order cost. So, if your estimate of order cost is two times the actual order cost, you will be ordering 41% too much stock and that could be a lot of money. (Recall that the square root of 2 is 1.41.) This estimation error is simple to make. Let’s say the real order cost is $50 per order, but you decide to use $100, just to be sure that everything is covered. This doesn’t seem like much, but will add 41% to the quantity of inventory purchased.

2.The formula assumes that the order cost is fixed.

Your actual order cost may vary due to efficiencies related to the supplier. This could include extra costs at your end due to the supplier being inefficient, losing paperwork, hard to contact, requiring follow up, and order expediting. Or the costs could be less due to acceptance of blanket orders, use of electronic methods, and so on. A blanket approach could result in significant overstocking and the calculated ROQ should be reviewed for any orders of a significant value.

3.The formula assumes that the demand is constant.

We have already seen an example where the demand varies significantly over time. If the calculation is performed when the demand is high, the calculated ROQ value will be high and you will be overstocked.

4.The formula assumes one delivery per order, no allowance for scheduling or batching.

Not all orders are delivered in one delivery and each delivery costs you money in terms of workload.

When faced with determining the factors used to calculate the ROQ, it is suggested that values are used that minimize the order quantity rather than maximize the order quantity as this is the lesser of two evils.

If you overestimate, you will spend too much on stock and unnecessarily tie up money or, worse, spend money on items that might never be used. This type of error is rarely addressed because it does not automatically trigger any action. However, if you underestimate your ROQ — and assuming that your ROP is appropriately set — then you will only end up ordering more frequently and this can trigger the need for a review. You can then set the ROQ at a more appropriate level. The effect of different order costs is shown below.

1. Assume that:

Order Cost = $100

Demand = 1,000 per year

Item Cost = $10

Holding Cost = 25%

= 283

Therefore, the ‘economic’ ROQ is 283 items.

This means that this item will be ordered, on average, 3.5

times per year (1,000 per year/ 283 per order).

2.Let’s look at the impact of changing the Order Cost. Assume that:

Order Cost = $50

Demand = 1,000 per year

Item Cost = $10

Holding Cost = 25%

= 200

Therefore, if the order cost is really $50 per order the ‘economic’ ROQ is only 200 items – approximately 30% lower than if the order cost is $100. This means that this item will be ordered five times per year (1,000 per year/ 200 per order).

A Word on Monte Carlo Simulation

Monte Carlo simulation is a complex analytical technique that uses random numbers as input variables and applies them to a known function (or formula). It is reportedly named after the random inputs that occur in table games, such as roulette, at the casinos in Monte Carlo.

With inventory analysis, it removes the constraint of having to make assumptions about the frequency or level of demand as these would be randomly generated values. When used in a computerized simulation, the technique can run through a high number of cycles to demonstrate under which scenarios supply would not be available. From this perspective, it appears to be an attractive option for inventory review and is widely used in the academic analysis of inventory management.

The technique does, however, suffer from the same shortfall in practice that limits most analytical approaches — it does not easily enable consideration of the entire materials and spares inventory management process. Instead, it focuses solely on the mathematical evaluation of the ROP and ROQ settings.

Do You Hold Too Much Inventory?Check Your Stock Turn Ratio

There are a number of measures that get used for tracking inventory performance. One of the most popular measures is stockouts. A stockout occurs when there is demand for an inventory item but there is no stock.

It is essential to measure the availability of stock. After all, that is why the investment is made in the first place. However, measuring stockouts can be a limiting way to measure inventory as it only measures one dimension of inventory, that is, availability. This approach is limiting because one way to ensure a low number of stockouts is to overinvest in inventory so that stock is always available no matter what. This is sometimes referred to as ‘just in case’ inventory.

What Is a ‘Stock Turn’?

Because inventory requires a significant financial investment and that investment involves significant ongoing costs, it is also important to measure the financial performance. Tracking the value of inventory is important for cash management purposes. However, an additional financial measure that often gets overlooked is the stock turn ratio.

The stock turn is calculated by dividing the annual usage of the inventory (in dollars) by the value of the inventory held (also in dollars).

For example, if a company holds $5M worth of inventory and issues $2.5M worth of that inventory in a year, the stock turn ratio is 2.5/5.0 = 0.5. That is, the company turns over its inventory at the rate of one half per year. Obviously, the higher the stock turn ratio, the better.

What Stock Turns Tell You

Stock turns measures the efficiency of the inventory investment by telling you whether you have overinvested in inventory and whether you have the right mix of inventory. (Note, however, that it won’t tell you about specific inventory items.) For example, if the number of stockouts is low (which is good) and the stock turn ratio is also low (which is bad), you have an indicator that there may be an overinvestment in inventory. If the number of stockouts is high (which is bad) and the stock turn ratio is low (which is also bad), then you may have invested in the wrong inventory. That is, your money is tied up in stock that doesn’t turn over and you hold too little of the stock that is in demand.

Stock Turn Targets

An appropriate target for stock turns in your business will be influenced by a range of issues, some within your control and others outside of your control. For example, if you have spares that are imported from somewhere far away or you are in a remote and isolated area, then you are likely to hold more safety stock and, therefore, have a lower stock turn. Conversely, if you are located in a densely-populated area surrounded by similar industry and many suppliers, you should be able to achieve a high stock turn. But this isn’t the whole story because if your processes don’t adequately control decision making on materials and spares inventory stocking, you are also likely have a low stock turn.

Using Stock Turns as a Key Measure

The key thing to remember when using a stock turn ratio is that it must be applied across the entire inventory. You cannot ‘cherry pick’ elements of inventory. The reason for this is that some inventory items will naturally have a high turnover and some will be low. The aim of the ratio is to measure the overall efficiency of the inventory investment.

In one recent case, an inventory manager tried to justify the size of his inventory by pointing out that one section of inventory had a stock turn of 5 (very good in his circumstance) and that another section had a stock turn of 0.2 (very bad). The justification was that insurance spares caused the low stock turn and, therefore, nothing further could be done. This analysis, however, ignored a large component of inventory that could be managed down and it ignored the possibility of consignment stock for the fast movers.

As mentioned above, stock turns is also a great measure to use when you have multiple sites or locations within the one company. As an internal benchmark, stock turns readily shows which sites have better control over their inventory.

Stock turns is an essential measure of inventory performance because it measures the inventory efficiency. When used in conjunction with other measures such as stockouts, the overall performance of your inventory investment can be determined.