How to calculate the costs of idle capacity in the manufacturing industry.
Issues relating to the costs of unused capacity have gained in importance in recent years. This is due to further fluctuating changes in customer demands, in combination with the seasonal nature of products and rising costs in fixed capacity. The financial crisis, which has been destabilizing world markets, has also had a very negative influence on the ability of producers to sustain the profitability of operations in situations of a high portion of fixed costs of a company. All these factors have made executives take a closer look at the management of idle capacity.
Unused capacity has been a topic widely researched by many authors. Some unused capacity is needed to ensure flexibility, but an excess of it unnecessarily weakens the utilization rate of resources.
Some research studies have presented strong evidence that a high quantity of unused capacity exists within companies (Brausch and Taylor, 1997), (Cokins, 1996). Most of this research has focused on measuring production department capacity but overlooked capacity measurement of non-production and service departments, where the costs of unused capacity could seriously impact on profit.
Typical systems concentrating on capacity usually only serve to highlight the quantifying output sacrificed due to low capacity utilization. Conventional capacity measurements do not include the value of equipment in the production system. As a consequence, their application can lead to erroneous operation decisions being made at management level. In such a situation, unused capacity costs gain in significance in terms of decision-making by management. To compound matters further, this problem is followed by another, that being of how to allocate such unused capacity costs. In traditional costing systems that do not tackle capacity problems, all costs are allotted to the products produced, which absorb all the fixed costs. In such cases, the costs relating to products could end up exaggerated, meaning they are unable to compete in the marketplace.
Costs of unused capacity
As mentioned above, capacity is one of the most important measures of resources used in production. Traditional concepts of capacity measurement very often omit the economical aspect that proves so important for informing managerial decisions. One of the areas that could be highly affected by changing capacity is product costing. Traditional absorption costing methods, which are based on proportional allocation of overhead costs according to direct costs consumed by products, are unable to calculate costs relating to capacity changes. The calculation for the rate of overhead is normally based on past data, with no consideration for possible capacity changes (Drury, 2001).
Analyzing the dependence of costs and capacity usually involves the process of classifying costs as variable and fixed. In this approach, costs are attributed according to their reaction to changes in the volume of production. Distinguishing between the variable and fixed parts of company costs is also fundamental to the variable costing method, which is the simplest way of bypassing the shortfalls of absorption costing methods. It can prove most effective when short-term decisions based on capacity utilization are required. Some authors have stated that the variable costing method is a means to providing useful, extra information for decision-making (Drury, 2001).
The variable costing method separates the fixed costs of a company that are not related to its outputs. These costs should not be allocated to products as they can distort the profitability of a product when incorrectly allotted.
Two forms of variable costing exist (Kral, 2006). The first of these is single step variable costing, which gathers all fixed costs in one cost pool and treats these costs as applicable throughout a firm. This form of variable costing only allows for measurement of capacity for a company in its entirety. The other variable costing method is known as the multi-step form, which apportions fixed costs into a company-wide section and another assignable to individual segments of a business. This means of costing enables capacity measurement of distinct parts of a business's.
Using the single step variable costing method, it is possible to calculate unused capacity costs with the following equation (Synek, 2003):
UCC = FC x (1 - [Q.sub.act]/[Q.sub.max]) (1)
Where: UCC--Unused capacity costs
FC--Company fixed costs
[Q.sub.act]--Actual output of a company in units or Euros
[Q.sub.max]--maximum output of a company
This sum, based as it is on maximum output determination, merely calculates a theoretical value of unused capacity costs. The greatest difficulty faced is that it one is usually unable to gauge company-wide capacity by a single measure. Modern enterprises consist of a complex structure of processes, activities and operations, which usually possess separate capacities. A company's products usually consume the capacity of the business's activities in different portions, dramatically complicating capacity measurement. It is possible to identify three aspects to the challenges facing conventional capacity measurement: the absence of both economic content and a quantity based approach, plus an unduly high emphasis placed on technical processes (Sebestyen and Juhasz, 2003). The company-wide capacity measurement described above via single measure becomes, in such conditions, an insufficient basis for informed managerial deliberations.
The appearance of activity-based costing (ABC) permitted the solving of such issues precisely, because its main aim is to analyse and differentiate between the overhead costs associated with capacity maintenance as well as operational and support processes. When using ABC for determining cost data, the results obtained are also appropriate for performing capacity usage calculations.
Measurement of capacity of activities in the ABC system
The basic idea of ABC is to allocate costs to operations through the various activities in place that can be measured by cost drivers. In other words, cost units are allocated to individual activities (e.g. planning, packing, quality control) in an initial phase using a resource cost driver, with the costs of those activities being allocated to the specific products or cost objects that actually caused the incurrence of the overhead costs, using an activity cost driver in the second phase.
Once the individual activities have been defined, the company's costs are then assigned to them and the cost drivers of individual activities are determined, the output measures for which have to be quantified. Output measures are used to quantify the outputs of activities, and provide a firm basis for activity capacity measurement. (Glad and Becker, 1996)
Activity-based costing facilitates the application of a process led approach to a business, identifying individual activities which take place within it. The great advantage of ABC is that the capacity of individual activities can be measured. In a traditional costing and manufacturing system, only the capacity of a total plant or that of individual production departments is measured and priced. ABC also focuses on overhead activities which are performed in an organization. Demand for the outputs of these overhead activities is on the rise in all areas of business, the driving force for this being the cost objects of products and other items. Due to this fact, the capacity usage of these overhead activities could dramatically fluctuate, and capacity limitations or wastage of these activities may potentially create a problem for management. In this situation, measuring the capacity of these overhead activities is desirable.
The costs of unused capacity can be calculated when the fixed costs of the resource, actual resource usage and effective capacity is known. The analysis of the costs of unused capacity is based on the following simple formula (2):
Activity Availability = Activity Usage + Unused Capacity (2)
The cost of unused capacity is the entire expense paid in advance in order to obtain the resource under consideration. This consists of the costs of capacity rightfully used in an operation--also known as 'exploited'--and costs unnecessarily allocated, i.e. unused capacity. Splitting capacity costs under the two headings can be appropriately carried out using linear approximation. Therefore, the costs of unused capacity are calculated by the same equation as general company capacity (1).
Determining overhead activity capacity
The most significant provision governing activity capacity measurement is that of setting the correct activity capacity, this capacity being determined by the level of its denominator. There are four different denominator activity levels that can be used (Drury, 2001). They are:
1. Theoretical maximum capacity
2. Practical capacity
3. Normal, average, long-run activity
4. Budgeted activity
These denominator levels are frequently applied in manufacturing operations where capacity can be technically and very preciously measured. In the case of overhead activity measurement, the setting of appropriate denominator levels could prove more complicated, because overhead activities usually don't have technical parameters that might easily be gauged. The capacity of overhead activities is usually measured by working out the number of output measures within a cost period.
Output measures are, in the ABC system, used to determine the recovery rate of each cost pool/activity. Two alternatives exist for this purpose (Glad and Becker, 1996):
* Actual output
This method uses the actual output of a particular output measure. This results in all costs being fully recovered by the cost object. If capacity utilization rates vary from one period to another, this will result in recovery rates fluctuating, sometimes dramatically so. In addition, the costs of idle capacity that exist in a particular capacity will not be highlighted. The costs of the cost object might also vary considerably, because costs of idle capacity are actually allocated to the products produced.
* Maximum capacity
In order to avoid the deficiencies of the actual capacity approach, it is desirable to set the constant capacity level for each activity. The effect of this is to make recovery rates reasonably consistent from one period to another, plus calculations of costs of unused or idle capacity, which should be specifically reported, are carried out. The costs of a cost object will also not alter dramatically.
Generally, calculating activity recovery rates based on actual output could prove easier to perform, as no maximum capacity determination is necessary. Calculations based on the maximum capacity are more accurate and provide for greater possibilities of utilization, e.g. capacity purposes. The challenge is working out how to set the maximum capacity of overhead activities.
Activity capacity output measures are used for quantifying activity unit costs, the rate for which is calculated as follows:
Activity cost per unit = Activity cost/Output measure capacity (3)
Setting the maximum capacity of activity output measures could prove rather complex in some cases. Some activities are measurable by a technical parameter. These activities may be described as activities with technical parameter. An example of such is warehousing. A suitable cost driver for the warehousing activity would be ground space or land, potentially measured in square meters or by the maximum number of pallets storable. In this case, it is possible to assign maximum capacity as the capacity of a warehouse, as denoted in technical documentation and actual capacity (actual occupation), this being data which is usually found on a company's ERP system. Following this, the capacity utilization rate may be quantified and calculations made on the costs of idle capacity.
Unfortunately, many overhead activities are not measurable by any technical parameters. These activities usually take the form of a register of the number of operations performed by employees. Such activities can be designated activities with continuous performance. An example is invoicing, with the cost driver being the number of invoices. In this activity, the actual output is easily gauged, but setting maximum capacity is challenging due to various factors affecting the performance of individual units of this activity. In practice, it is actually quite tricky to arrive at the maximum number of invoices a department could issue. Therefore, maximum capacity could be defined as being the long-term average of an activity's output, or arrived at by process and activity analysis. The former is simpler but incapable of identifying limitations relating to the true capacity of an activity.
Managing a product portfolio with activity capacity
Activity capacity measurement necessitates radical improvement in capacity measurement in a business. Products and other cost objects usually consume activity outputs disproportionally. This means that individual products consume differing amounts of activity capacity. One situation that is likely to be encountered is when the capacity of any activity is exhausted, even though other activities show large portions of idle capacity. Items consuming an over-proportional amount of any activity capacity are known as 'zombie products' (Nekvapil 2004). Product portfolio management is favorable in such cases so as to avoid the issue of consumption of disproportional activity capacity.
Managing a product portfolio where differences exist in the consumption of activity outputs is gaining in relevance to business today. Reaching the maximum capacity of any activity output usually puts pressure on cost increases, which are caused by additional costs of limited capacity consumed by this activity. At a later date, when demand on capacity is lower, costs like these--e.g. wages for new employees--are not normally reduced to their original levels. This effect, if caused by so-called zombie products, could result in cost increases and wastage.
In situations when the capacity measures of activities are explicitly defined, the linear programming method might be applied for product portfolio optimization models. In first step, the linear profit function has to be defined, [x.sub.1] - [x.sub.n] are the product quantities and [P.sub.1] - [P.sub.n] the product profits. This linear function supposes to be maximized in order to get the maximum profit (4). After that, the constraints are defined (5), which represent the limited activity capacities ([b.sub.1] - [b.sub.3]) for individual activities [A.sub.1] - [A.sub.n]. The company products in fact consume the different portions of the activity outputs. This function is than solved to get the best possible product portfolio, with highest possible profit. This method could be also extended with activity cost measurement.
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4)
[A.sub.1][x.sub.1] + [A.sub.1][x.sub.2] + ... + [A.sub.1][x.sub.n] [less than or equal to] [b.sub.1] [A.sub.2][x.sub.1] + [A.sub.2][x.sub.2] + ... + [A.sub.2][x.sub.n] [less than or equal to] [b.sub.2] [A.sub.3][x.sub.1] + [A.sub.3][x.sub.2] + ... + [A.sub.3][x.sub.n] [less than or equal to] [b.sub.3] (5)
As mentioned above, demand for activity outputs is often higher than the installed capacity of an activity, although activity capacity may not be consumed at all. Circumstances such as these usually lead to cost increases. If activity capacity has to be increased, it is usually necessary to consume more sources. An alternative situation might present itself in which one is confronted with unused capacity and wastage. Here, when demand for an activity's outputs only occasionally exceeds its capacity, it proves ineffective to permanently raise activity capacity, because average unused capacity and wasted costs will go up. One option is for surplus demand to be outsourced, for example by renting additional warehouse space. Another possible scenario involves the incapability of utilizing the installed capacity of an activity, to which capacity cannot be reduced. In such cases insourcing external activities might be beneficial. That means that one could offer the unutilized outputs of an activity to external customers in order to increase the utilization rate. An example of this would be an accounting department offering its services to external subjects. (Kanniannen, Varila and Paranko, 2003)
Allocation procedures for unused capacity costs
The last question managers often ask goes something like this: "Is it worthwhile allocating idle capacity costs to products produced?" Elsewhere in this paper methods are outlined for calculating idle capacity costs. There are two ways of incorporating idle capacity costs in a company's costing system. The first is to allot said costs to the products produced, which can be carried out by using actual output capacity measures within the costing system. The other involves allocating only those costs really consumed to products and quantifying idle capacity costs. Both of these have pros and cons, and it is generally very difficult to say which brings about more benefits. The main priority is to ensure that management's requirements are met. Executives and users of information have to consider whether the full allocation of costs is desired. This issue is normally solved by the sales department, where fully allocated costs could generate information of greater accuracy for decision making over the long term. However, one knock-on effect might be an increase in final price, in circumstances when a company is not utilizing its capacity effectively. This price increase could discourage customers, resulting in continuous underuse of installed capacity.
Traditional costing and manufacturing systems are usually not able to handle capacity utilization problems very effectively. Their disadvantage tends to be an extreme focus on production capacity measurement with a single capacity measure. Companies often perform a large number of individual activities, which also have individual capacity limitations and use various capacity measures. An activity-based approach is able to incorporate the capacity measurement of these activities in a company's costing system.
Complications might arise when implementing effective measures for overhead activities. In practice, it is very difficult to quantify any type of activity or set a maximum capacity, which is essential in order to measure utilization. Limiting the capacity of overhead activities could hamper capacity utilization affecting other activities, as well as the general output of an enterprise. In such situations, managers attempt to increase the volume of these overhead departments, usually resulting in cost increases. Measuring a product's consumption of overhead activity outputs makes it possible to avoid these issues.
In such multi-measure models, the importance of product portfolio measurement gains in importance, due to a risk of disproportionate consumption of activity outputs. Furthermore, there is a heightened chance of management erring in judgment, especially in circumstances of fluctuation in demand. Several procedures could be applied to capacity models to improve the ability of company executives to make informed decisions. Nevertheless, the demand necessary in terms of information and data could limit their practical utilization.
Linear programming methods might effectively be applied in situations when the capacity of overhead departments is defined and consumption of these outputs is measurable in relation to a company's products. The aim of this model is to eliminate those products that consume a high and over-proportional part of the overhead departments' capacities.
BRAUSCH, J. M., TAYLOR, T. C. (1997), Who is Accounting for The Cost of Capacity?, Management Accounting, Vol., No. February, pp. 44-50.
COKINS, G. (1996), Activity-based cost management: Making it work: A manager's guide to implementing and sustaining an effective ABC system, Irwin, Chicago.
COKINS, G. (2001), Activity-Based Cost Management: An Executive's Guide, John Wiley and Sons, ISBN 047144328X
DRURY, C. (2001), Management and Cost Accounting, Fifth Edition, Thomson Learning; ISBN 1-86152-536-2
GLAD, E., BECKER, H. (1996), Activity-Based Costing and Management, John Wiley and Sons, ISBN 0-471-96331-3
JACOBS, F., MARSHALL, R., SMITH, S. (1993), An alternative method for allocating service department costs, Ohio CPA Journal; Apr 1993; 52,2; ABI/INFORM Global pg.20
KANNIAINEN, J., VARILA, M., PARANKO, J. (2002), The Unused Capacity Trap, Pre-Prints of the 12th, International Working Seminar on Production Economics. Innsbruck, Austria. 18-22 February, Vol. 3. pp.229-240.
KAPLAN, R., COOPER, R. (1998), Cost & Effect--Using Integrated Cost Systems to Drive Profitability and Performance, Harvard Business School Press, ISBN978-0-87584-788-7
KRAL, B., (2006) Managerial Accounting, Management Press, ISBN 80-7261-141-0
NEKVAPIL, T., (2004), Netradicne o ABM--Controller a zombie, Controlling 4/2004, ISSN 1801-6251
POPESKO, B., NOVAK, P., Principles of overhead cost allocation, from Issues in Global Business and Management Research--Proceedings of the 2008 International Online Conference on Business and Management (IOCBM 2008), Universal-Publishers USA, ISBN 9781599429441
POPESKO, B., Activity-based costing applications in the plastics industry--Case study, from Issues in Global Research in Business and Economics, FIZJA International, Orlando USA, ISSN 1940-5391
SEBESTYEN, Z., JUHASZ, V., The impact of the costs of unused capacity on production planning of flexible manufacturing systems, Periodica Polytechnica Ser. Soc. Man. Sci. Vol.11, No.2, PP 185-200, 2003, ISSN 1587-380
SYNEK, M., a kol., Manazerska Ekonomika, Grada Publishing a.s., 2003, 466 s., ISBN 80-2470515-X
VOLKAN, I. (2007), ABC & ABM--The couple which prevails cost calculation and modern administration for performance, Journal of Accounting and Management Information Systems, 2nd International conference AMIS 2007, Academy of Economic Studies, Bucharest, ISSN 1583-4387
Department of Enterprise Economics, Tomas Bata University, Zlin, Czech Republic
Boris Popesko can be contacted at: firstname.lastname@example.org
* The article is processed as an output of a research project entitled Methodology of Activity-Based implementation and its influence on the efficiency of manufacturing industries, registered by the under the registration number 402/07/P296.