Report Objectives
This report focuses on unit 3 of the module (capacity management, planning and control) with a study approach on the causes and effects of variation in demand for goods and services, the planning processes for effective and efficient delivery, and consistent operations despite the changing market demands (Do Ngoc & Moon 2011). The report is fundamental to those organizations that aim at establishing improved capacity processes for long, medium, and short-term performances, which primarily require instantaneous forecasting. In this area of report, our attention is drawn to the various methods of managing changes in demand, the loading, sequencing, scheduling and control systems, and how the corresponding operational systems assist managers to ensure proper control of inventories (Do Ngoc & Moon 2011). This section of discussion also considers the importance of segmenting the transformation process through production model for the purposes of improving efficiency in planning and control activities.
The topic of capacity management, planning, and control touches on specific areas of improved inventory management with significant attachment to factors like costs and time of deliveries based on the changing needs of customers (Guneri & Gumus 2008). In this line of report, we define capacity management, look at some of the capacity constraints, discuss planning and controlling capacity, forecast demand and capacity, and finally look at the cost and benefits of capacity forecasting in relation to customers’ purchases as a measure of organizational performance.
Definition of Capacity Management
Studies attach higher levels of significance on operational value of an organization within the specified periods of production. Under operational management, capacity is a term used to define the maximum level value of the added activities throughout the engagement period (Herrera, Alberto & Cabrera-Ríos 2005). In other words, capacity management helps organizations to determine the maximum additional valuable activities that can be achieved under normal operational conditions within the specified time of production without straining the available resources. Through capacity management, organizations find it easy to operate within their limits, but still produce goods and services that meet the demands of customers in different market segment (Herrera, Alberto & Cabrera-Ríos 2005). This means that capacity management helps organizations to improve in areas of resource allocation so that the little resources can be viewed as sufficient to fulfil the changing needs of customers.
Constraints to Capacity Management
Organizations at times fail to meet their operational capacity for maximum processing due to inexistence or insufficient demand or due to poor deliberative policies to allow organizations to quickly respond to all the new orders (Coyle 1998). The inability to meet market demands would mean that organizations are operating below their capacity levels, and cannot meet the competitive operational standards.
It is also possible that organizations can be incapacitated by high costs of production or the increasing costs of expanding operations to meet the growing market demands. The changes in consumptions needs means that organizations must put in place strategies to expand their operations. This desire cannot be fulfilled if the company lacks sufficient resources or finances (Herrera, Alberto & Cabrera-Ríos 2005). Other than the cost of operation, capacity management is also affected by changes in management technologies. The changes is management technologies require organizations to regularly update their systems, provide sufficient technical training, design new delivery channels, and gain higher customers’ loyalty through quality products and services. The whole period of updating systems, training workers to gain new skills and insights, and venturing into new designs is a time wasted, which translates to significant revenue losses (Herrera, Alberto & Cabrera-Ríos 2005). In other words, organizations need to provide extra resources to manage both the micro and macro-operations of operations, which include human and physical resources.
Capacity management, planning and control
Planning and controlling capacity include setting an effective capacity for improved operations so that the activities of the company can respond to the customers’ demands for goods and services (Premkumar, Chu & Chou 2001). Capacity planning and controlling entails making stringent decisions about organization operations to counteract the fluctuating market demands. The management process entails comparing medium and short-term organizational capacity as well as analysing the aggregate demand and production capacity to meet the performance objectives of the company without a change on the planning and control systems (Premkumar, Chu & Chou 2001).
Under medium and short term capacity planning and control, the management must involve proper assessment of the forecast demand for a period ranging between 2 and 18 months in relation to the planned output, which can be varied based on the production capacity of the company (Premkumar, Chu & Chou 2001). It is better for the company to have a production capacity higher than the forecast demand than have a lower production capacity for the planned output. In most cases, organizations’ operations surfer from inaccurate forecasts, especially for the changes in demand that occur over within the short period of period of production. The fact that the response is required on a short timescale means that operational managers must be able to make short-term capacity adjustments with an aim of flexing output for the short period following the predicated performance capabilities.
On the side of aggregate demand and production capacity, the management in most cases concentrates on setting capacity levels to meet the medium and short-term aggregate demand, which reflects customer’s ability to purchase the goods and services. With concern for aggregate demand, operation managers make overall decisions affecting product and service deliver without putting pressure on the resources (Premkumar, Chu & Chou 2001). It is therefore convincing enough for the management to buddle together products and services in order to have a wider view of market demand in relation to organizational capabilities (Premkumar, Chu & Chou 2001). Time and cost approximations are some of the basic stages that will allow process managers to determine the best response strategies for the growing market demand since the two factors affect production and delivery.
The relevance of capacity management, control and planning
Other than the mentioned objectives, operations managers take devise capacity plans in a way that affect several aspects of performance. It is important to note that organizational costs are always affected by managers’ inability to create a balance between capacity and customer demand. Where the organization suffers excess levels of demand, it is possible that there is underutilization of performance capacity, and this could lead to higher unit costs compared to unit profits (Herrera, Özdemir & Cabrera-Ríos 2009). The inability to create a balance between capacity and demand could also have negative impact of revues. Efficient capacity management will therefore ensure that the production process equates capacity to the demand or results into slightly higher capacity than the demand so that customers are satisfied without revenue loss on the side of the company (Herrera, Özdemir & Cabrera-Ríos 2009). At the same time, there is need to understand the effect of capacity management on the company’s working capital, particularly when the company decides to heap up their finished goods before determining the level of demand (Zeydan & AIahverdi 2006). Even though the demand will be satisfied under such circumstances, there are higher possibilities that the organization will be forced to finance the inventories from stock of its capital until the inventory of finished goods can be sold. The capacity plan also have impact on the quality of goods and services, and where there is an increase in the number of staff, the organization will face disruption to its normal operations hence an increase in the profitability of production errors (Zeydan & AIahverdi 2006). Capacity management is known to speed up response to the demand of customers through improved inventory management or through a deliberate provision of surplus supplies.
Apart from the stated issues, the closeness between demand and capacity has a influences dependability of supplies. The argument here is that the demand should not get closer to the operations capacity ceiling because getting closer will create unexpected alteration in the delivery system (Chou, Wu, Kao & Hsieh 2001). Making the delivery of goods and services less dependable suggest management inability to meet the expected market demand following the limited operations capacity. The production managers must then allow for process flexibility by creating surplus capacity since the balance between capacity and demand will automatically eliminate market and operation inefficiencies (Chou, Wu, Kao & Hsieh 2001).
It is possible that operations managers will face problems related to forecasting demand given the organizations’ limited capacity, which can wither certain of uncertain. The problem of forecast require managers to have ideas about the company’s ability to meet the increasing demands, and the decision must have backings from quantitative data about the capacity and demand (Herrera, Özdemir & Cabrera-Ríos 2009). As far as capacity management is concerned, the decision-making criteria will follow certain fundamental questions that can only be answered quantitatively. The three most important questions connected to capacity management, planning and control are as stated below:
- What capacity levels will help the company meet the growing aggregate demand for the planning period?
- What alternative capacity plans are relevant to the company’s operations and could help the company to respond to the changes in demand?
- What is the most appropriate capacity plan that could be used to manage the growing demand and manage the risks associated with poor product and service deliveries?
Sample calculation on capacity management, planning and control
The main objective under operations forecast is to determine the level of output at which the company will breakeven given the projected cost of production, the unit costs of output, and the aggregate market demand assuming that the customers have the same opportunity purchase (Aguilar, Rodríguez & Cabrera-Ríos 2006). Assume a case where a company’s fixed cost of production is 15,000 US dollars, with a unit cost of 7.50 dollars for every additional output. Assume that the company faces an aggregate demand of 500,000 units charged at 15 dollars for every unit to meet the market demand (Aguilar, Rodríguez & Cabrera-Ríos 2006). The company must first determine the number of units that it can sell to break even before extending its services to fulfil the market demands.
The solution for the breakeven point would be as illustrated in appendix 1 for the calculated breakeven point and appendix 2 for the graphical representation of the breakeven point (Aguilar, Rodríguez & Cabrera-Ríos 2006). Form the calculations represented in the appendix, it is healthy for the company to produce 2000 units of output in order to meet its operational costs before engaging in production of extra units to meet the market demands. Determining the cost of production, which entails overhead costs, labour costs and costs of acquiring production equipment and balancing such costs with the customer’s demand for the first 2000 units of output fall under the concepts of operations management (Aguilar, Rodríguez & Cabrera-Ríos 2006). By analysing the company’s capacity, it becomes possible to determine the rising costs of operation prior to production so that the company can adjust the unit prices for its supplies with an aim of meeting the initial costs of production. In order to achieve the targeted level of output and revenues, the company must consider certain factors like the time of production, additional costs, amount of inventories available and changes in market demand.
Companies use historic data to improve their performance relationships and expand on the capacity to meet customer demands. For the wide portfolio of services, it is noticeable that the demand changes quite often and so should the capacity requirements (Chen 2007). The case provided discusses the historical capacity and demand data for a particular company in a particular year (Chen 2007). From an initial production capacity of 128 and associated demand as shown in figure 3 of the appendix, the company must schedule its operations to meet its monthly targets.
References
Aguilar, M. A. S., Rodríguez, G. J. M., & Cabrera-Ríos, M., 2006. Statistical characterization and optimization of artificial neural networks in time series forecasting: the one-period forecast case. Computación y Sistemas.
Chen, H., 2007. A Lagrangian relaxation approach for production planning with demand uncertainty. European Journal of Industrial Engineering.
Chou, Y. C., Wu, C. S., Kao, C. E., & Hsieh, S. H., 2001. Integration of capacity planning techniques for tool portfolio planning in semiconductor manufacturing. International Journal of Industrial Engineering: Theory, Applications and Practice.
Coyle, A., 1998. An algorithm for capacity expansion in local access networks. In Proceedings of the 33rd Annual Conference of the Operations Research Society of New Zealand.
Do Ngoc, A. D., & Moon, I. K., 2011. The storage capacity expansion and space leasing for container depots. Flexible services and manufacturing journal.
Guneri, A. F., & Gumus, A. T., 2008. The usage of artificial neural networks for finite capacity planning. International Journal of Industrial Engineering: Theory, Applications and Practice, 15(1).
Herrera, Á., Alberto, C., & Cabrera-Ríos, M., 2005. Un enfoque de inventarios para planear capacidad en redes de telecomunicaciones. Ingenierías.
Herrera, C. A. A., Özdemir, D., & Cabrera-Ríos, M., 2009. Capacity planning in a telecommunications network: a case study. Int J Ind Eng-Theory, Appl Pract.
Premkumar, G., Chu, C., & Chou, H., 2001. Telecommunications network design decision-a genetic algorithm approach. Decision Sciences.
Zeydan, M., & AIahverdi, A., 2006. Economic order quantity with uncertain inflation: A case study. International Journal of Industrial Engineering-Theory Applications and Practice.
Appendix
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| Month |
Demand (in output units) |
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| 1 | 128 | ||
| 2 | 155 | ||
| 3 | 198 | ||
| 4 | 108 | ||
| 5 | 130 | ||
| 6 | 160 | ||
| 7 | 191 | ||
| 8 | 150 | ||
| 9 | 220 | ||
| 10 | 130 | ||
| 11 | 230 | ||
| 12 | 200 |
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