We show how a linear programming model can assist strategic decision-making, understanding it either within the neoclassical theory of the firm, the industrial organization theory, the resource-based view, or other approaches of strategic management. The model relays on Activity Based Costing (ABC) for calculating unit product cost, and on dynamic Activity Based Management (ABM) for assessing the feasibility of prospective production plans. It was implemented 4 years ago in a Chilean integrated steel manufacturer, and it is currently being used to optimize its business plan.
In order to survive, manufacturers must strategically plan their product mix, sales prices, volumes, inventory levels, production capacity, and so on. This requires the assessment of two critical issues: the feasibility of production plans and the unit costs of products. If a company lacks a feasible estimation model, it may commit itself to an unreasonably high workload, which will cause the company to default on its obligations and lose the goodwill of its customers (Spearman and Zhang, 1999). Conversely, the company could adopt a more conservative policy, constraining itself to lower production volumes and artificially reducing its profits. By the same token, the company must have a good forecast of total costs as a function of the production plan in order to maximize its revenue. Otherwise, lucrative products may be exchanged for unprofitable ones, affecting the company's competitiveness.
The purpose of this paper is to show how a mathematical programming model can assist in strategic decision-making by forecasting the results of possible actions and providing quantitative feedback to managers. The model is based on Activity Based Management (ABM), an approach that conceptualizes production systems as a network of work centers that add value to a flow-in-process, constrained by the available resources. We applied this methodology at the Chilean integrated steel manufacturer Compañía Siderúrgica Huachipato (Huachipato). The steel industry has received a great deal of attention in the field of strategy and operations research, because of the heavy pressure from worldwide competition ( Denton et al., 2003).
In the steel industry, a number of studies have reported how to minimize cost, maximize profit or maximize capacity utilization, with a linear programming model (Sinha et al., 1995 and Chen and Wang, 1997). However, little effort has been devoted to explicit the connection between the mathematical program and strategic decision-making. Most likely, this is due to a weak understanding of the relationship between operational and financial indices (Melnyk et al., 2004).
Our contribution to linking mathematical programming and strategy research is two-fold. First, in 2 and 3 we propose a dynamic activity-based model for calculating unit cost and for assessing the feasibility of production plans for a general production operation. This accounts for one of the five potential areas for future research in the steel industry proposed by Dutta and Fourer (2001): “Simultaneous optimization of product-mix, inventory, and transportation problems over multiple periods.” In Section 4, we apply this model in a Chilean integrated steel manufacturer. A second contribution, presented in Section 5, is to explain how the model can assist managers in making better strategic decisions. Finally, in Section 6 we present our conclusions.
In this paper we analyze how activity-based management can assist the cost estimation and the feasibility assessment, by describing the production system as a network of activities connected by physical flows. Cost is estimated by prorating the use of resources into activities, and the contribution of activities to final products. Feasibility is modeled using constraints that limit both the flow and the inventory in work stations. This idea was implemented in a Chilean integrated steel manufacturer as a planning system in Excel, which has been used and enhanced from year 2000 until now.
We also explored the connection between the activity-based optimization system and the strategic decision-making of an integrated steel manufacturer. We show that the system can provide valuable feedback to managers, understanding their role within the neoclassical theory of the firm, the industrial organization theory, the Chicago school, the Schumpeter's view and the resource-based view.
