ACCT 311 Week 7 Individual Research Paper Example

Is Time-Driven Activity-Based Costing More Accurate? Theory and Evidence on Costing the Complexity of Customer Orders

Introduction

A cost system is a theory about what causes costs. Traditional systems assume that overhead is caused by volume, so they spread it across products with a single rate based on direct labor hours or machine hours. Activity-based costing replaced that theory with a richer one: overhead is caused by activities, such as setups, orders and inspections, and products and customers should bear the cost of the activities they demand (Garrison et al., 2018). Time-driven activity-based costing goes one step further, holding that most activities consume resources in proportion to the time they take, so that a cost per minute and an equation for the time each transaction requires can replace the costly interviews and surveys of conventional ABC. This paper asks whether time-driven ABC produces more accurate costs than conventional ABC, and whether its central assumption, that time can be estimated reliably, holds up. The evidence suggests that the method is more accurate where activities vary in complexity, but that its accuracy depends on how the time estimates are gathered, and that no single costing system dominates the others on every criterion.

From Plantwide Rates to Activity-Based Costing

Garrison et al. (2018) explain that a plantwide overhead rate distorts product costs when products consume overhead resources in different proportions than they consume the allocation base. A low-volume custom product that requires many setups and engineering changes is undercosted by a direct labor rate, while high-volume standard products are overcosted. Activity-based costing corrects this in two stages. First, overhead costs are assigned to activity cost pools, such as order processing or machine setups, usually on the basis of interviews in which employees estimate how they divide their time. Second, the activity costs are assigned to products and customers using activity measures, such as the number of orders or setups. The result is a more realistic picture of which products and customers are profitable.

Conventional ABC has well-known weaknesses. The employee interviews are expensive and must be repeated as operations change. Because employees typically report how they divide 100 percent of their time, the system assumes that resources are fully used, hiding unused capacity inside activity rates. And a single activity measure, such as number of orders, assumes that every order consumes the same resources, which is rarely true.

The Time-Driven Approach

Time-driven ABC addresses these weaknesses with two estimates. The first is the capacity cost rate: the cost of the resources a department supplies divided by their practical capacity. The second is a time equation for each activity, which estimates the minutes a transaction requires based on its characteristics. Balakrishnan et al. (2012a) place the approach among four common ways of costing products and illustrate it with the same numerical example used for traditional costing, conventional ABC and resource consumption accounting.

Consider a composite industrial supply distributor whose order-handling department has 12 employees and costs $1,440,000 a year, including salaries, benefits, supervision, technology and space. Each employee is paid for about 2,000 hours a year, but after breaks, training and meetings, practical capacity is about 80 percent, or 1,600 hours, which is 96,000 minutes. The department's practical capacity is therefore 1,152,000 minutes, and the capacity cost rate is $1,440,000 / 1,152,000 = $1.25 a minute. The time equation for an order is 8 minutes for basic entry, plus 2.5 minutes for each line item, plus 15 minutes if the order is expedited, plus 6 minutes if the customer is new and needs a credit check. A standard four-line order takes 8 + 10 = 18 minutes and costs $22.50. A twelve-line expedited order from a new customer takes 8 + 30 + 15 + 6 = 59 minutes and costs $73.75.

Conventional ABC would assign both orders the same cost. If the department processed 64,000 orders, the cost per order would be $1,440,000 / 64,000 = $22.50, whatever the order's complexity. A single cost per order is accurate only for the average order, and most decisions are about orders that are not average. Time-driven ABC also reveals unused capacity. If the year's orders required 1,000,000 minutes in total, the department used 1,000,000 of its 1,152,000 minutes, leaving 152,000 minutes, or $190,000, of capacity that customers did not consume. Conventional ABC would have spread that $190,000 across the orders, making every order look more expensive than it was.

The time equation is also easier to maintain than an interview-based system. Suppose the distributor launches an online ordering portal, and orders entered by customers through the portal skip the 8 minutes of basic entry but still need 1.5 minutes per line for review. Under conventional ABC, the company would need to reinterview the department to learn how employees now divide their time. Under time-driven ABC, it adds one term to the equation: minus 8 minutes and minus 1 minute per line if the order arrives through the portal. A twelve-line portal order would then take 18 minutes instead of 38 before expediting or credit checks, and its cost would fall from $47.50 to $22.50. The equation turns a change in process into a change in cost immediately, which gives managers a reason to encourage customers to use the cheaper channel.

Evidence on Accuracy

Whether these refinements improve accuracy is partly a question about how costing errors behave. Labro and Vanhoucke (2007) simulated two-stage costing systems and found that partial improvements usually increase overall accuracy, but not always, because errors can offset one another, most notably when aggregation error in activity cost pools combines with measurement error in resource drivers. They also found that errors in the second stage, the assignment of activity costs to products, affect accuracy more than errors in the first stage, so refinements should focus there. Time-driven ABC is essentially a refinement of the second stage, since its time equations capture differences in how much of an activity each order consumes. The simulation also found that errors usually leave more products undercosted than overcosted, with large overcosting of a few expensive products and small undercosting of many cheaper ones.

Case evidence supports the claim that time equations improve the second stage. Everaert et al. (2008) studied a Belgian wholesaler that had used conventional ABC and then adopted time-driven ABC. They found that many logistics operations could not be modeled with a single cost driver, and that time equations captured the different complexities by including multiple terms and interactions. Comparing the two systems, they concluded that conventional ABC had oversimplified 64 percent of the activities and misallocated 55 percent of all indirect costs. A single case cannot establish how common such errors are, but the magnitude suggests that the single-driver assumption can be costly in operations with varied transactions, which describes the distributor in the example.

The Weak Point: Time Estimates

Time-driven ABC replaces interviews about how employees divide their time with estimates of how long each task takes, and those estimates can be wrong. Cardinaels and Labro (2008) tested this in an experiment. They found that measurement error decreased when activities were defined at a more aggregated level, and that advance notice that time estimates would be required reduced error, especially for aggregated activities or incoherent tasks. Most striking, participants who gave estimates in minutes showed a strong overestimation bias, which the authors note may be a problem for a method that recommends estimates in minutes.

This finding cuts against the most attractive feature of the method. The detailed time equation in the distributor example is valuable only if 2.5 minutes per line item is close to the truth. If employees overestimate, the equation will charge too much time to each order and understate unused capacity. Practical remedies follow from the experiment: tell employees in advance that times will be measured, observe or sample actual times rather than relying only on estimates, and compare the total minutes the equations predict with the minutes actually paid for. In the example, if the equations predicted more than 1,152,000 minutes, the estimates would clearly be too high.

Evidence on Adoption and Use

Accuracy is not the only reason organizations adopt or abandon a costing system. Gosselin (1997) studied manufacturing business units and found that strategy was associated with the decision to adopt activity-based approaches, while organizational structure, particularly centralization and formalization, was associated with whether units went on to implement full activity-based costing. A method's success therefore depends on whether the organization can sustain it, not only on whether it is accurate.

Health care offers a recent test of time-driven ABC. Keel et al. (2017) systematically reviewed its use in health care and concluded that it is applicable and can cost care processes efficiently, overcoming a key challenge of other cost-accounting methods. They also found that its ability to inform bundled payments and to coordinate care across the continuum had not yet been demonstrated in the published literature, and they recommended incorporating it gradually into existing systems.

The health care setting also shows why time is a natural cost driver in service organizations. In a clinic, the most expensive resources are the hours of physicians, nurses, technicians and rooms, and a patient's visit consumes them in sequence. Mapping the process and timing each step lets an organization see which steps add cost without adding value, such as waiting for a room or repeating a history that was already taken. The same logic applies to the distributor, whose most expensive resource is the time of its order-handling staff. In both settings, the cost system becomes a map of where time goes, and that map is often as valuable to managers as the cost figures themselves, because it shows which processes to redesign. This mix of promise and caution parallels the evidence from logistics: the method captures complexity well, but its benefits depend on how carefully it is built into an organization.

Costing Systems as Decision Aids

Balakrishnan et al. (2012b) rated four product costing approaches, from volume-based rates to resource consumption accounting, on three dimensions: the cost of implementing and maintaining the system, its ability to provide decision-relevant data and the incentives it creates for managing the demand for resources. They concluded that no system clearly dominates the others and suggested that future systems might blend the best features of each. Time-driven ABC is cheaper to maintain than conventional ABC and makes unused capacity visible, which encourages managers to manage the supply of resources. But like all full-cost systems, it can still mislead short-term decisions if managers treat a cost per minute as if it were avoidable. Garrison et al. (2018) make the same point about differential analysis: only costs that differ between alternatives are relevant to a decision, and allocated capacity costs often do not.

For the distributor, this means the $73.75 cost of the complex order is the right figure for pricing and customer profitability, because it reflects the capacity such orders consume over time. It is not the right figure for deciding whether to accept a single extra order next week, since the department has 152,000 unused minutes and an extra order would not change the $1,440,000 spent on the department.

Implications for Cost Accountants

Several implications follow. Cost accountants who adopt time-driven ABC should start with the activities whose transactions vary most in complexity, since that is where the method's accuracy advantage is greatest. They should collect time estimates with advance notice and verify them against observed times and against total paid capacity, to counter the overestimation bias Cardinaels and Labro (2008) found. They should report unused capacity separately, so that managers can decide whether to reduce resources or find new uses for them. And they should present time-driven costs as tools for pricing, product mix and customer profitability decisions, while reminding managers that short-term decisions require differential analysis.

Scripture commands full and fair weights and measures, so that people would deal honestly with one another (English Standard Version Bible, 2001/2016, Deuteronomy 25:15). A cost system is a set of weights and measures for an organization's resources. When it charges simple customers for the complexity of others, or hides idle capacity in the price of every order, it measures unfairly, even if no one intends to deceive. Building a system that measures as accurately as is practical, and saying plainly where it is uncertain, is part of honest stewardship of the information on which others rely.

Conclusion

Is time-driven activity-based costing more accurate than conventional ABC? Where transactions vary in complexity, the evidence suggests that it is: time equations capture differences that a single activity measure cannot, and the method separates the cost of unused capacity from the cost of the work done. Its accuracy, however, rests on time estimates that experiments show are prone to error, especially when stated in minutes, and on an organization's willingness to keep the equations current. The evidence also has limits. Case studies such as the wholesaler examined by Everaert et al. (2008) show large improvements in single companies, while broader studies remain few, and much of the research in health care describes applications rather than measuring their effects. Time-driven ABC is best understood not as a final answer to the question of what causes costs, but as a better and cheaper way to ask it, which is valuable precisely because costing theory, as Balakrishnan et al. (2012b) conclude, has not produced a single system that is best for every purpose.

References

Balakrishnan, R., Labro, E., & Sivaramakrishnan, K. (2012a). Product costs as decision aids: An analysis of alternative approaches (Part 1). Accounting Horizons, 26(1), 1-20. https://doi.org/10.2308/acch-50086

Balakrishnan, R., Labro, E., & Sivaramakrishnan, K. (2012b). Product costs as decision aids: An analysis of alternative approaches (Part 2). Accounting Horizons, 26(1), 21-41. https://doi.org/10.2308/acch-10197

Cardinaels, E., & Labro, E. (2008). On the determinants of measurement error in time-driven costing. The Accounting Review, 83(3), 735-756. https://doi.org/10.2308/accr.2008.83.3.735

English Standard Version Bible. (2016). Crossway. (Original work published 2001)

Everaert, P., Bruggeman, W., Sarens, G., Anderson, S. R., & Levant, Y. (2008). Cost modeling in logistics using time-driven ABC: Experiences from a wholesaler. International Journal of Physical Distribution & Logistics Management, 38(3), 172-191. https://doi.org/10.1108/09600030810866977

Garrison, R. H., Noreen, E. W., & Brewer, P. C. (2018). Managerial accounting (16th ed.). McGraw-Hill Education.

Gosselin, M. (1997). The effect of strategy and organizational structure on the adoption and implementation of activity-based costing. Accounting, Organizations and Society, 22(2), 105-122. https://doi.org/10.1016/S0361-3682(96)00031-1

Keel, G., Savage, C., Rafiq, M., & Mazzocato, P. (2017). Time-driven activity-based costing in health care: A systematic review of the literature. Health Policy, 121(7), 755-763. https://doi.org/10.1016/j.healthpol.2017.04.013

Labro, E., & Vanhoucke, M. (2007). A simulation analysis of interactions among errors in costing systems. The Accounting Review, 82(4), 939-962. https://doi.org/10.2308/accr.2007.82.4.939