should assess their inventory performance with respect to financial and service targets. While service targets are needed at SKU level, assessment of service targets at higher levels of aggregation elevates an operational task to a strategic issue. A strategic view of service and costs is essential because there is often a trade‐off between these two aspects of performance and looking at just one aspect may lead to poor decisions.
3.3.1 Aggregate Financial Targets
A financial target can be set in a variety of ways. One way to express it is in terms of the average inventory valuation, obtained by recording the financial value of inventories at a number of times during the year and averaging them. Sufficient times during the year should be included to obtain a reliable average, especially if inventories are seasonal. The exact method of valuation depends on the accounting rules employed; for further discussion see, for example, Muller (2019).
An important issue to be addressed is the ‘write off’ of obsolescent stock if it has no residual value or its ‘write down’ if it still has some value, for example as scrap. Once stock becomes so slow moving that it is unlikely to be ever sold, then these adjustments to the balance sheet are necessary. The record of inventory written off, or written down, is useful in two ways. Firstly, it can be used to assess the additional percentage inventory holding cost to allow for the potential obsolescence of slow moving SKUs, as discussed in Chapter 2. Secondly, the write‐off and write‐down values can be monitored to assess the effectiveness of measures to prevent the build‐up of obsolete inventory.
Inventory turnover is another useful financial measure. It is calculated as the ratio of the cost of goods sold (COGS) to the average inventory valuation. For example, if the annual COGS is £8 million and the average inventory valuation is £2 million, then the inventory turns four times a year. This measure is useful because it takes into account the growth or decline of sales. If COGS rises by 20% but inventory value increases by only 10%, then the inventory turnover will improve. It is possible to benchmark a company's performance on inventory turnover against competitors, but care is needed in drawing conclusions from the comparison. Inventory turnover is strongly influenced by the breadth of products in the stock range. If it is necessary to include slower‐moving stocks, because of contractual obligations, then the inventory turnover will necessarily be lower. If required, inventory turnover can be assessed for categories of SKUs (e.g. by volume of sales) or at the level of an individual SKU. It is most commonly measured at the aggregate level and provides a useful headline figure. It should be monitored over time, so that the effect of any changes in policies or practices can be assessed.
A full financial assessment of the impact of stockouts can be difficult to achieve. If stockouts lead to backorders, then it may be possible to estimate the costs of expediting orders to minimise the delay in satisfying the order. It is more challenging to assess the costs of lost goodwill from clients. For this reason, aggregate financial targets are usually complemented by aggregate service level targets, to which we now turn.
3.3.2 Service Level Measures
Johnson et al. (1995, p. 57) observed, ‘The rhetoric on customer service has grown from a quiet whisper to a deafening roar’. Twenty‐five years later, customer service is still a prominent issue in supply chain management and is likely to remain so. There are many aspects of service relating to customer orders, including user‐friendly ordering systems, availability of accurate order status information, delivery of the correct goods at the promised time, and the prompt and courteous response to customer queries or complaints. In this book, we are concerned with just one aspect of customer service, namely the availability of stock to satisfy customer demand. We refer to this as the ‘service level’, whilst recognising that there are many other aspects of customer service.
Some organisations have formal service level agreements (SLAs) with their major suppliers. These usually specify target service levels and may include financial penalties for missing these targets. This highlights the importance of using appropriate forecasting and inventory management methods. Otherwise, as Willemain (2018) emphasised, suppliers will incur financial penalties much more frequently than they were expecting. An SLA will specify either lump‐sum penalties or penalties proportional to underperformance. This choice needs careful consideration as it can influence ‘gaming’ behaviour by the supplier (Liang and Atkins 2013).
It is essential that the service level measure is clearly specified in an SLA, and that performance is regularly monitored against target. Indeed, even if an SLA is not in place, it is vital that there is a common understanding of how service is measured, and that the measure is appropriate for the business. A number of measures have been proposed and we now proceed to review how these measures are calculated and how they should be used.
From a customer perspective, it would be ideal if all of their orders could be met in full, immediately from stock. Consider the example of a single customer order shown in Table 3.1.
There are three levels at which service may be evaluated:
1 Orders: In this example, the order is not completely filled because the order lines for SKUs B and E are not fully satisfied, and the order line for SKU C is not satisfied at all. To calculate the proportion of orders completely filled (the order fill rate [FR]) would require data on all relevant orders. If the order in Table 3.1 were included, it would be counted as unfulfilled.
2 Order lines: Two out of the five order lines are completely filled, for SKUs A and D, giving an order‐line fill rate of 40%.
3 Units: Table 3.1 shows that 18 out of 25 units are filled from stock, giving a unit fill rate of 72%. Alternatively, this could be calculated according to value. A value of £5100 is filled from stock, out of a total value requested of £6000, giving a value fill rate of 85%.
This example is restricted to a single order, but each of the measures can also be calculated at the aggregate level, over a whole collection of orders. We can find the total number of orders completely filled, the total number of order lines (over all orders) completely filled, and the total number of units filled (over all order lines and all orders). These totals can then be divided by the total orders, order lines, and units demanded, respectively.
Table 3.1 Order comprising five order lines.
| SKU | Ordered | Filled | Ordered (£) | Filled (£) |
|---|---|---|---|---|
| A | 5 | 5 | 500 | 500 |
| B | 10 | 8 | 1000 | 800 |
| C | 4 | 0 | 500 | 0 |
| D | 1 | 1 | 3000 | 3000 |
| E | 5 | 4 |
|
