If the cost function is a valid representation of the costs behavior, a cost prediction can be interpreted as “what the cost should be for a given volume of activity”. It becomes an expectation, a standard, benchmark or a target.
A benchmark is a point of reference from which comparisons can be made.
A target is a level of performance or rate of improvement required for measure.
Interpreted as such, predictions made with cost functions are very useful tools for managers. First, managers can use them to set reasonable objectives for their subordinates. It is interesting to note here (although it is an issue of management control rather than management accounting) that how the target was set (i.e. which cost estimation technique was used to produce the function producing the target) affects its credibility and achievability. Targets should ideally be S.M.A.R.T.: Specific, Measurable, Ambitious yet Realistic and Time-bounded. The very usage of cost function ensures measurability and sets the time frame. However, which method you use affects specificity, ambition and realism. Account analysis and high-low are not very suitable for target setting, but the engineering approach and the least-square regression are.
Targets based on the engineering approach are highly detailed, but they are not based on historical data, i.e. not based on concrete experience. Therefore they are highly specific and ambitious, but sometimes also unrealistic. They can be seen as “lovely ideals”. To correct for this bias, managers often incorporate allowances for waste, spoilage, rejects, breaks, machine downtime, or variations in skills to transform ideal standards into practical standards.
Targets based on the least-square regression can be highly detailed if there is enough observations to disentangle the respective effects of imperfectly correlated cost driver. But most of the time these requirements are not satisfied: data is scare and cost drivers are highly correlated. Therefore regressions usually yield broad targets lacking specificity. However, since they are based on past observations, these targets are realistic (they are after all the average of what was done before). But for that reason, they may be considered as lacking ambition: managers rarely aim for the average past performance; they want to improve performance.
Since these two estimation techniques have complementary strengths and weaknesses, they greatly benefit from being used in combination. They are also at the core of cost management as in target costing and kaizen costing.
Target costing is a method of costs planning used during the research, development, and engineering stage to reduce manufacturing costs to targeted levels.
Target costing consists first in estimating the price customers will be willing to pay for a product or service. This becomes the target price which is usually set using value engineering (or functional analysis).
The target price is the estimated price for a product or service that potential customers will be willing to pay.
Value engineering is a process of determining how much value consumers received from a product or service based on its features and functionality.
Then, the target cost is estimated as the difference between the target price and the target profit margin.
The target cost is the cost of a product or service which allows the company to achieve its target profit when the product is sold at the target price.
Then the engineering approach is applied to estimate the cost of the product or service as it is currently designed. Usually, this estimated cost is greater than the target cost, i.e. there is a cost gap. The product or service is then resigned until the cost gap is null.
The cost gap is the difference between the estimated cost of a product or service and its target cost.
While target costing is applied in the research and development phase, Kaizen costing is applied in the manufacturing stage.
Kaizen costing is a costing technique which explicitly incorporates continuous improvement when setting standards. It is a costing system that focuses on reducing costs during the manufacturing stage of the total life-cycle of a product.
Kaizen costing builds on statistics about the observed evolution of product costs all along their life. These statistics typically show a stable pattern: start-up costs (costs are usually higher at the beginning) progressively disappear and as the experience with the product increases, the company becomes more efficient, but at a decreasing rate. This pattern is called the learning curve.
The learning curve shows how the unit product cost declines as units of output increase.
Interestingly, this learning curve can be applied to any costs and help setting both realistic (because based on past experience) and ambitious (because of the planned continuous improvement) targets.
Please indicate how clear and understandable this page was for you: