An Activity- Based Costing and Theory of Constraints Model for Product- Mix Decisions

The objective of this thesis is to demonstrate the use of the Activity-Based Costing (ABC) approach together with the Theory of Constraints (TOC) philosophy in determining the optimal product-mix and restrictive bottlenecks of a company. The contribution of this thesis is a new product-mix decision model that uses activity-based cost information. This new model is proposed to be used with the TOC philosophy in order to improve the financial performance of a company.

Four case studies, all of which are based on hypothetical data, are prepared in this research to show the applicability of the proposed model in different manufacturing environments. Specifically, the first case study shows that the conventional product-mix decision model and the model developed in this thesis can give significantly different results regarding the best product-mix and associated bottlenecks of a company. The second case study demonstrates the use of the proposed product-mix decision model in a complex manufacturing environment. Specifically, this case study shows how companies should consider alternatives such as activity flexibility and outsourcing to improve their profitability figures. The third case study is an extension of the second case study, and it is prepared to illustrate that the proposed model can be extended to include more than one time period. The final case study demonstrates the applicability of the proposed model in a lean manufacturing environment.

Using the proposed model developed in this research will give managers more accurate information regarding the optimum product-mix and critical bottlenecks of their companies. By applying the TOC philosophy based on this information, managers will be able to take the right actions that will improve the profitability of their companies. Specifically, they will be able to observe the effects of several alternatives, such as activity flexibility and outsourcing, on the throughput of the whole system. In addition, the proposed model should help managers to prevent making decisions that sub-optimize the system. This may occur, for example, when using only the most efficient methods to produce each product even though the capacities of these methods are limited and some other less efficient methods are currently available in the company. By extending the model to include more than one time period, managers will be able to estimate the potential bottlenecks and the amount of idle capacities of each non-bottleneck activity performed in the company ahead of time. This information is powerful and can give companies a substantial advantage over their competitors because the users of the new model will have enough time to improve the performance of their potential bottlenecks and to search for more profitable usage of excess capacities before the actual production takes place.