Supply chain management is a broad concept that traverses the limits of a single firm to span associated actions of all the businesses that are in the chain of supply. Any business must apply a harmonized, bi-directional delivery of its commodities plus services, available sale data, anticipated finances and the associated demand trajectories (Benton, 2014). There are four known types of flows which are significant for the successes of any supply chain management in a business unit. Going beyond the boundaries of any organization in fundamental nature implies that the supply chain needs to work in satisfying the final client (Chopra & Meindl, 2007). The chain of supply needs to be effective as this is what drives growth, the realization of profits and customer satisfaction. Toyota is world’s largest car manufacturer that prides itself on being home one of the most efficient supply chains for its products (Heim, 2013). As the company’s supply manager, I strive to ensure great efficiency in the face of changing trends in the field informed by innovations and a shift in customer preferences in relation to the supply method. In my position, I have a huge role to play in the success of the supply chain. Integration is not a sufficient reason for the supply chain's success. Better coordination and integration is required.
The way products move from the companies plants be it the cars or the spare parts to the consumer is of great significance. It remains an important constituent in the management of Toyota’s supply chain (Benton, 2014). Clients anticipate their requested orders are made available in an appropriate, consistent, and consumable condition. The transport medium remains crucial in attaining this result (Christopher, 2011). The flow of products is not unidirectional in today’s setting, a factor attributable to the need for methods of taking back improper goods to the purchaser for the reason that they are spoiled, outdated and tattered (Stadtler & Kilger, 2005). There are many other reasons for this growth in reverse systems, but there are no doubts to a paradigm shift in the handling of supply chains for business entities (Benton, 2014). The schemes for the return of goods usually have to be planned differently from the existing forward techniques. Certain factors such as the location of the clientele, the size of ordered commodities, and arrangement of facilities for such services are typically different from those of supply to the consumer. There should be a prudent utilization of the available medium of transport in a way that the customers find a value for the items ordered. Accordingly, there has been a development of business firms that specialize in returning goods to the manufacturer in case they have not met the agreements that were in the order document from the consumer. Toyota is keen on exploring such alternatives to ensure client satisfaction at all times. The figure below is a simple depiction of the manufacturer’s supply chain.
Another type of flow is the movement of information. Over the years due to the evolving supply chain management systems, the flow of information has become a necessary ingredient for the success of a company. Conventionally, the available sales data belonging to a firm has been going to a direction parallel to the way in which products move. However, in the recent information age, this has long been forgotten; the manufacturers and the consumers share day to day information including client requests (Coyle, Novack, & Gibson, 2015). This information can help the business units in predicting the demand for a particular product because they can directly speak to the consumer and know the specific needs. In the event of lack of information regarding the requirements for goods or a long channel of communication, the logistics personnel will usually have a rough time figuring out the client needs. For the avoidance of such doubts, supply experts have developed communication channels that can handle well the information bit so that they are not far apart from the consumers (Chopra & Meindl, 2007). In the event of lack of such avenues the company will incur a lot of costs while storing products that a consumer may not be interested or not being consumable. The outcome will ultimately be high inventory costs, creating more avenues of being less profitable business (Coyle, Novack, & Gibson, 2015). There ought to be information channels with which supply personnel can get real-time customer related data of what the consumer needs, cutting the costs of storing such goods in warehouses. The chain of supply of a product from the manufacturer to the client can take half the time in a case such methods do not exist. It is even possible to eliminate an inventory because a firm will have a direct control of the products' marketplace. (Chopra & Meindl, 2007). An important effect of supply chain firmness and quicker order cycle periods have been more rapid cash flows. Consumers take delivery of orders immediately, and they are payable sooner, and the companies can receive money earlier (Lebreton, 2007).
For any business to succeed in managing its inventory well, it is necessary that it understands the characteristics of the items it sells (Cox, 2011). The traits can be in the form of the cost incurred, the required time before the items are delivered to the consumer once ordered and the demand characteristics. The nature of the actual demands holds the greatest effect and thus classified into dependent and independent demand. The independent demand is one that is not related to the request for other items. Dependent demands refer to the demand that emanates from an existing demand attributes of a product whose details are in an inventory (Chopra & Meindl, 2007). However, for example, a company such as Toyota, it requires a product structure for which it would make no sense to forecast something like wheel assemblies independently, simply because the wheel assemblies are dependent on and derived from the demand for the automobile product. Aggregate planning identifies the best way to utilize the limited resources of a company to meet the time varying demand (Benton, 2014). This type of planning established the most optimal planning strategy so as to have a so-called monopoly in the marketplace (Gattorna, 2009). The objective of this model’s effectiveness is measured by the ability to allocate system capacity to alternative products over time in the face of demands so as to optimize some features of system performance. A materials requirement planning works best in assisting business entities in developing a demand that is dependent on the inventory and also to estimate the orders expected in a particular period. In specific terms, the latter is a critical technology developed to establish orders that customers would request so that the manufacturer knows how much to produce to avoid the loss result in from stocking many unordered products (Chopra & Meindl, 2007).
Material requirement planning is a systematic method the company is implementing to determine the quantity and the timing of items that heavily rely on demand. Since the introduction of the concept, the development and implementation of MRP have both made substantial progress. However, since it has become evident that MRP alone is not sufficient to cope with balancing capacity with demand adequately; further development has introduced capacity planning requirements (Coyle, Novack, & Gibson, 2015). The output from the aggregate planning is usually optimal workload of the product which can be further broken down into its dependent demand items. Moreover, through better services to the consumers, a company can be successful and reach even a global space. The key thing to ensure that there is better customer service is to ensure that the clients always find the products and should not go out of stock for whatever reasons. The essential tool in controlling the availability of a product in the market is through the use of Master Product Schedule (Coyle, Novack, & Gibson, 2015). The achievement of this may be via the control of initial inventory to create a sure forecast for a particular period. The calculations can be complicated in an environment with multiple products, so it is necessary to avoid errors. The reliability of such results depends on the mistakes and constraints incurred in the process. MPS is a useful tool in establishing the availability of the product in the market with a careful consideration of the costs (Mukerjee, 2008). The MPS is a predictable schedule of demand. The MPS includes a forecasted demand as backlogged customer orders (Chopra & Meindl, 2007). The application of the principles of supply chain management can help to reduce costs, waste and enable the prediction of our product demand. There is the maintenance of a minimum level of inventory that is carried and is maintained at a few crucial points. I intend to apply some of the inventory management theories in ensuring the success of the initiative. Another major objective of the supply chain is applicability in planning for cost reduction. The cost per unit for the end customer reduces (Coyle, Novack, & Gibson, 2015). Now, on the one hand, the firm can predict demand quite accurately, and it also tries to reduce wastage and improve quality and harmony. Supply chain management thus creates benefits to the customers (Gattorna, 2009). Reduction of waste, better prediction of demand, cost reduction all aim at benefits to the customers. The supply chain is primarily meant to enhance performance for a business marketer, through integration, coordination and cooperation between multiple firms (Christopher, 2011).
Forecasting in this context is the technique of being able to predict demands in the future so as to efficiently handle the market forces. Many managers treat forecasting as purely an art form and assume that the best forecasts are a creation of experienced managers using their intuition (Christopher, 2011). However, this does not mean that forecasting is a futile exercise, but it is important to recognize that forecasts will never be perfect and therefore firms should find ways and means of reducing the errors involved in the practice. In certain situations, future demand can be estimated accurately using structured analysis, while in some it may be difficult to forecast demand (Christopher, 2011). Demand forecasting has been the weakest link in most supply chain planning. Forecasting is a management process, and like any other process needs a careful organization with attention to people, processes, and the tools that constitute the forecasting management (Benton, 2014). The quantitative type of forecasting provides a general idea of the historical customer demands for a particular product. Through the use of statistical analysis, it is possible to identify two main categories of consumer patterns. One of the patterns has its basis on the time periods in which certain product demand was high and at certain periods when the demand was low. The process of identifying and predicting these patterns with regard to time is achieved using a time series technique (Coyle, Novack, & Gibson, 2015). Another type is the use of patterns which have a direct influence demand at a particular point in time (Christopher, 2011). Such analysis has been made easier through the use of regression analysis.
Contrary to the above, qualitative forecasting method also known as subjective forecasting entails the steps of reflecting on ideas by experienced who can easily predict the demands they are finally making these reports formal (Greef & Ghoshal, 2004). One can also explain it as the process of analyzing the future sales data, predicting how such data will change to obtain future demands. In some cases, the data obtained from this technique has worked whereas in some cases it has failed. Therefore, the best process is to incorporate the two techniques, and the results can form a basis for better confidence going forward (Greef & Ghoshal, 2004). It is not, however, possible to correctly predict what may happen in future for any business. In such cases, historical demands become the primary source of useful forecast deductions. It is necessary to compare the viability of such projections to ensure that the data is reliable. For an entirely complete estimate, it is necessarily healthy for any business to combine the two techniques. Demand forecasters need to employ qualitative forecasting techniques when they have reason to believe that the future will not necessarily resemble the past. Toyota should do both qualitative and quantitative forecasting so that the forecasted demand is correct beyond any reasonable doubt to eliminate any chances of errors (Gattorna, 2009).
The first process is to guarantee a break-even point. Many businesses have collapsed because they got it wrong when it comes to implementing a working chain for a better place in the market. Toyota has always had a culture of analyzing customers’ needs frequently, and determining the appropriate course of action, a factor has enabled it to drive through turbulent times in the automobile market (Hines, 2008). The supply cycle must ensure that the customers feel valued at the end of the process of delivery. Value addition is possible and can cut costs from both the consumer and manufacturer’s side. This process has to happen so that there is no gap between the producers and the final consumers. It is important to conduct reliable demand forecast for more exact needs of the customer at hand. Firms need to invest heavily in the model of supply and also ensure that the model interacts well with their business model.
Benton, W. C. (2014). Supply chain focused manufacturing planning and control. Stamford, CT: Cengage Learning.
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Christopher, M. (2011). Logistics & supply chain management. Harlow, England: Financial Times Prentice Hall.
Cox, S. S., Desai, H., Desai, K., & Sherman, A. K. (2011). Mswires: Sourcing for a Parts Supplier. Journal Of Critical Incidents, 497-99.
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Coyle, J. J., Novack, R. A., & Gibson, B. J. (2015). Transportation: A global supply chain perspective.
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Hines, P. (2008). Benchmarking Toyota's Supply Chain: Japan vs U.K. Long Range Planning, 31(6), 911-918
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Stadtler, H., & Kilger, C. (2005). Supply chain management and advanced planning: Concepts, models, software and case studies. (Springer e-books.) Berlin: Springer.
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