• ChapterLogistics and Transportation• pp 214-234• Logistics performance metrics• Raja G. Kasilingam• http://link.springer.com/chapter/10.1007/978-1-4615-5277-2_9

• Logistics metrics are quantitative measurements that track certain processes within the logistics framework. The best design for a logistic system or component(s) of a logistics system truly depends upon the metric(s) used for measuring the performance. A system that measures up very high in one metric may not measure very well in some other criteria. The objective, however, is to design a system that meets or exceeds the expectations in most of the selected metrics. Logistics metrics vary based upon the boundary of the system (the various functional areas included such as production, distribution, inbound transportation, storage, vendor selection etc.), the functional requirements of the system and the different areas and the ability to define and measure them quantitatively. Hence the first step in designing the metrics is to define the system that needs to be measured and its components. The second step is to determine the functional requirements or expectations of the system. The third step is to identify metrics that can quantitatively measure the functional requirements. It is also important to understand the relationship between metrics. One or more metrics may drive the performance of another metric. For instance, in the case of railroads, customer service in terms of the percentage of on-time delivery of shipments depends upon the on-time arrival and departure of trains and terminal dwell time for cars (time spent at a terminal).

Transportation Metrics:

• Freight cost per unit shipped: Calculated by dividing total freight costs by number of units shipped per period. Useful in businesses where units of measure are standard (e.g., pounds). Can also be calculated by mode (barge, rail,ocean, truckload, less-than-truckload, small package, air freight, intermodal, etc.).

Outbound freight costs as percentage of net sales: Calculated by dividing outbound freight costs by net sales. Most accounting systems can separate "freight in" and "freight out." Percentage can vary with sales mix, but is an excellent indicator of the transportation financial performance.

Inbound freight costs as percentage of purchases. Calculated by dividing inbound freight costs by purchase dollars. It is important to understand the underlying detail. The measurement can vary widely, depending on whether raw materials are purchased on a delivered, prepaid, or collect basis.

Transit time: Measured by the number of days (or hours) from the time a shipment leaves your facility to the time it arrives at the customer's location. Often measured against a standard transit time quoted by the carrier for each traffic lane. Unless you are integrated into your customers' systems, you will have to rely on freight carriers to report their own performance. This is often an important component of leadtime. Transit times can vary substantially, based on freight mode and carrier systems.

On Time Performance

• OnTime Shipping Performance is a calculation of the number of Order Lines shipped on or before the Requested Ship Date versus the total number of Order Lines. Throughout the following text, I refer to "shipped" ontime. BUT if actual "delivery" data is available, it may be substituted and compared to the Requested Delivery Date. (such as with an EDI#214 ).

*OnTime: Shipped on or before the requested ship date (except if the receiving party does not accept early shipments).

Sample OnTime Metrics:• OnTime Line Count: The amount of order lines shipped OnTime* versus the amount of lines ordered.

example- ABC Company orders 10 products (one order line each) on its Purchase Order #1234. The Order has a Requested Ship Date of March 1. The manufacturer ships out 5 line items on February 28 and 2 items on March 1 and the remaining 3 items on March 10. The OnTime LineCount for this Purchase Order is 70%. It is calculated based on the Requested Ship Date OR, if available, substitute actual Delivery Date vs Requested Delivery Date. Calculation: Number of Order Lines Shipped on or before the Requested Date / Total Number of Order Lines Ordered(7/10 = 70%)

On Time Performance

• OnTime SKU Count: The number of SKU's (Stock Keeping Units) ordered and shipped is taken into consideration. Above, we consider each Order Line to have an equal value (1 ). Here, we count the SKU's per Order Line.example: If on Line 1, the order was for 30 skus of product "AB" and on line 2, they ordered 10 skus of item "AC". The Requested Ship Date is April 1st. If Line 1 ships on March 28 and line 2 on April 20, the the SKU Fill Rate is 75%Calculation: Number of SKUs Shipped OnTime / Total Number of SKUs Ordered (30/40 = 75%).

• OnTime Case Count: The amount of cases shipped OnTime versus the amount of cases ordered. example- ABC Company orders 6 products that total 200 cases, on its Purchase Order #1235. The manufacturer ships out 140 cases on 3/1/01 and the remaining 60 cases on 3/10/01. The Requested Ship Date is 3/1. The Case OnTime Rate for this Purchase Order is 70%. The number of Order Lines is not considered in this calculation. This OnTime measure gives "weight" to the order lines that are shipped out. Calculation: Number of Cases Shipped OnTime / Total Number of Cases Ordered . (140/200 = 70%)

• OnTime Value Rate: Same as above, except the order line value is used instead of cases.Calculation: Value of Order Lines Shipped OnTime / Total Value of the Order ($400/$500 = 80%)

Cycle Time Measurements

• Here are just a few of the many Cycle Times you should consider for your Supply Chain. All of these measures should not only calculate the days (or hours) from the start and finish, but also between the various steps in between.

Customer Order Promised Cycle Time: The anticipated or agreed upon cycle time of a Purchase Order. It is gap between the Purchase Order Creation Date and the Requested Delivery Date.This tells you the cycle time that you should expect (NOT the actual)

• Customer Order Actual Cycle Time: The average time it takes to actually fill a customers purchase order. This measure can be viewed on an Order or an Order Line level.The measure starts when the customers order is sent/received/entered. It is measured along its various steps of the order cycle. Through credit checks, pricing, warehouse picking and shipping. The measure ends at either the time of shipment or at the time of delivery to the customer (sometimes tracked by using an EDI #214). This "actual" cycle time should be compared to the "promised" cycle time.

• Manufacturing Cycle Time:Measured from the Firm Planned Order until the final production is reported. It usually takes into account the original planned production quantity versus the actual production quantity. Example: X% of the planned quantity must be completed on a production run or the cycle time should not be considered.

• Purchase Order Cycle Time:Measured from the creation of the PO to the receipt at your location (Distribution Center, Hub etc). One of the keys here is not not have your RDD (Requested Delivery Date) exceed the agreed to lead time. If it does, it may artificially inflate your Lead Time. Additionally, any in-between points available will add value to the metric. Example: Creation of the PO, Shipment from the Vendor, Receipt at the DC. This will tell you the manufacturing time vs the transit time.

DPMO: Defects Per Million Opportunities

• DPMO is a Six Sigma* calculation used to indicate the amount of defects in a process per one million opportunities. To calculate: Total Number of Defects / Total Number of Opportunities for a Defect. Then multiply the answer by 1 Million.• The challenge here is determining exactly what qualifies as a defect. Some defects can

pass through a quality inspection and have little impact on the end product. Other defects can result in re-work or scrap.• DPMO is sometimes used instead of Defect per Unit to allow for comparison between

processes with different levels of complexity.• *Six Sigma uses statistical analysis to measure a companies performance by

identifying defects in a manufacturing process. The goal of Six Sigma is to reduce process output variation to + or - six standard deviations. This results in no more than 3.4 defects per million opportunities.

Perfect Order Measurement

• Perfect Order Measurement: As with most other Supply Chain Metrics, there are many variations to this measurement. The Perfect Order Measure calculates the error-free rate of each stage of a Purchase Order. This measure should capture every step in the life of an order. It measures the errors per order line. But how do you capture errors? Let's look at what happens when an error occurs. Say for example, your warehouse picks and ships the wrong item. Once the customer receives the order and notices the error, they contact the manufacturer and notify them of the mistake. The manufacturer then enters a credit for the item not shipped and an invoice for the item shipped in its place. For almost all errors that occur, a corrective credit is issued. It is through an analysis of these credits that you derive your metric. Most systems require a "reason code" to be used when entering a credit. Tracking these reason codes and assigning them to a category allow you to group them for the Perfect Order Measure.Example:

Order Entry Accuracy: 99.95% Correct (5 errors per 10,000 order lines)Warehouse Pick Accuracy: 99.2%Delivered on Time: 96% Shipped without Damage: 99%Invoiced Correctly: 99.8%

• Therefore, the Perfect Order Measure is 99.95% * 99.2% * 96% * 99% * 99.8% = 94.04%

• There may be other fields used such as "The Sales Representative recommending the correct item" or the "FillRate".