The standard cost for a manufactured item provides the basis for variance analysis on a production order. Variances identify the differences between an item s standard cost and actual production order costs, and are summarized on the statistics window for a production order. Variances indicate potential problems in manufacturing an item, and diagnosis requires an understanding of how variances are calculated. Explanations here focus on a one-line production order, but they also apply to a multiline order.
The total variance for a given production order is graphically represented in Figure 8.3 as the distance between two lines representing the standard cost and actual costs for the order. The difference between the two lines consists of five types of variances. The figure also displays a separate line for an expected cost. These three lines provide the basis for an explanation of production order variances.
Standard Cost The standard cost data for a manufactured item reflects company-wide information and a cost roll-up calculation as of a specified date. Chapter 3 explained standard cost roll-up calculations. An item s costs are segmented into material, capacity, capacity overhead, subcontracted, and manufacturing overhead. These cost elements provide the baseline for calculating the five types of variances.
Expected Cost The expected costs for a production order reflect information in the order-dependent bill and routing. This information initially reflects the master bill and routing (and versions if applicable ) assigned to the production order line item. Manual changes to this information typically represent substitute materials and/or alternate operations. The Production Order Statistics window displays the differences between expected costs and standard costs, but these are not considered variances from an accounting viewpoint.
Actual Costs Actual costs for a production order reflect the reporting of production activities and the costs at transaction time. Differences between actual costs and standard cost can be segmented into five variances, and the basis for each variance differs . The typical basis for each variance is shown in Figure 8.3 and described below.
Material Variance . Actual costs are based on reported material usage, so that variances indicate differences with information used to calculate the item s standard cost for material. This typically stems from over- or underreporting component quantity usage, or the component s SKU cost differs from the cost used in roll-up calculations.
Capacity Variance . The reported capacity usage for an internal operation differs from that used to calculate the item s standard cost for capacity. A capacity variance is typically caused by over- or underreporting of time for an internal operation. Other causes include a production order quantity that differs from the parent item s accounting lot size since this affects the amortization of setup and fixed scrap amounts.
Capacity Overhead Variance . The same explanation for capacity variance applies to a capacity overhead variance, where an internal work center has overhead costs.
Subcontracted Variance . The invoiced quantity and/or price for an outside operation differs from that used to calculate the item s standard costs. Each outside operation typically has a specified unit cost in the routing information
Manufacturing Overhead Variance. The parent item s received quantity differs from the production order quantity, which leads to differences in the incurred manufacturing overhead costs.
The general ledger is updated with variances for finished production orders after running the batch process to Adjust Cost-Item Entries. The value entries for the finished production order and for the parent item provide a transaction audit trail identifying each calculated variance.
The statistics window for a multiline production order summarizes standard, expected, and actual costs for all line items. However, the system retains information about variances related to each line item and displays it in the value entries for the finished production order.
The All-and-Anything company wanted to improve coordination of manufacturing activities by enhancing suggested planner action messages. Building on the concept of planner responsibility assigned to items and production order line items, they extended the scope of suggested action messages on the planning worksheet. Additional message types included follow-up on past-due receipt, review an order placed on hold, review an existing order affected by changes to the master bill or routing, and review an item when its primary source is changed to production. Message filters were also defined for various message types.
The cost accountant at the All-and-Anything company required several customizations to improve the usefulness of information about variances. For example, the costs for purchased material were segmented into material and material-related overhead cost elements, and the cost of sales was segmented into each cost element for posting to the general ledger. Additional variances were calculated for each production order, including variances between expected and standard costs, and variances related to issued components not on the order-dependent bill. This supported a better comparison between standard costs plus variances against actual costs. The cost accountant also required several reports to understand and analyze production order variances. One report provided a detailed breakdown (by component and operation) of standard versus actual costs to fully understand the cause of production order variances. Another report provided a historical analysis of each production order s variances by parent item, component, and work center.
 See Maximizing Your ERP System for further explanation of planner responsibility (pp. 116 “117, 285) and types of planner action messages (pp. 290 “292).
The Batch Process company produced a pharmaceutical product with stringent quality criteria concerning compliance with regulations and requirements for a validation audit. Starting with various lot-controlled ingredients , a batch is mixed, made into tablets, and then packaged in a bottle with a label. Each batch requires a unique lot number. Tablets are treated as phantoms since production flows from the tablet machine immediately into packaging.
The quality criteria in this regulated environment impact system usage in several ways. Systems security plays a larger role, such as authorized access to update information about bills, lots, inventory dispositions, and transaction audit trails. It requires strict label control, conditional releases of lot-traced material, and lot genealogy for historical analysis purposes (see Case #37 in Chapter 7).
The Equipment company occasionally used customer-supplied material in production processes. They required identification of component requirements in the bill, visibility of scheduled receipts, a receiving process, and material tracking for customer supplied material. The item number for each customer-supplied component represented a unique item and was valued at zero cost.
The Fabricated Products company required APS capabilities to minimize setups and avoid additional equipment purchases for its line of extruded plastic products. Multiple extrusion machines produced plastic pipes of varying diameters and colors. Scheduling considerations included sequence-dependent setup time (based on diameter and color ), machine capabilities for handling different products, machine-specific run rates, and secondary resources of tooling and skilled operators. To integrate APS capabilities, the routing data was extended to specify a work center (the resource group ) and a machine (the preferred resource) for an operation; operation attributes such as setup matrices for handling sequence-dependent setup times; and machine attributes such as resource type. The APS capabilities were also used to support capable-to-promise logic.
 See Maximizing Your ERP System for further explanation of APS integration, including a summary of APS logic and the theory of constraints (pp. 30 “34), resource types and resource groups (pp. 92 “97), operation attributes (pp. 106 “108), and using APS for capable-to-promise logic (pp.197 “198).