BUS 6600 GCU Staff Scheduling For Improving Risk Management Discussion

Discuss how your organization could use an operations management linear programming application to solve a problem or improve a business process.

, Sir and Class

Linear programming applications can be effectively used in operations management to control costs and allocate resources more efficiently to different areas of operations. The allocation of resources is primarily a key area where linear programming can enable an organization to cut costs and improve efficiency. After setting production objectives, linear programming models can be created that can determine the exact value of resources an organization needs to meet its production objectives while at the same time minimizing costs. Linear programming models can also be used to optimize day-to-day supply chain decisions in a way that reduces total operating costs. Day-to-day supply chain decisions include ensuring there is enough inventory, scheduling specific processes, and identifying the most efficient locations that can be used for certain operations. Linear programming models can be used to solve these problems based on the resource constraints that the organization is subject to. Supply chain costs can, as a result, be significantly reduced, making operations more efficient.

Staff scheduling, which is a critical aspect of operations management, can also be better optimized through the use of linear programming. While it may not always be possible to have enough staff to meet day-to-day needs, it is still possible to identify effective ways of utilizing available staff to improve the efficiency of day-to-day operations. Linear programming models can solve this problem by allocating staff to specific areas more efficiently based on several constraints, such as the number of customers. Linear programming models can also be used to evaluate possible investment decisions that an organization may make. Based on estimates of possible returns, the value gained from making certain operational decisions can be accurately predicted. As a result, more informed decisions can be made, improving the organization’s overall profitability.

Reference

Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., Cochran, J. L., Fry, M. J., & Ohlmann, J. W. (2016). Quantitative methods for business with CengageNOW (13th ed.). Boston, MA: Cengage Learning. ISBN-13: 9781305799257

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