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Business forecasting

Business Forecasting
MTCA is not a New Concept but New in Practice
According to Chase, many manufacturing firms are aware of the MTCA as a concept that can create positive implementations and changes in the supply chain (13). MTCA helps the ‘ Consumer packaged goods’ manufacturing organizations to weigh the marketing impact on the demand of retailer consumers. In the end, they perform the ‘ what-if’ analysis that is essential for accurate prediction and maximization of future demand. The MTCA is however still a concept, and fewer organizations are ready to engage in it practically. They are not in a position to implement the casual techniques like multiple linear regressions to the model, which they lack the knowledge and expertise to do perfectly. Also, many organizations have failed to link the short-term volumes associated with the sales promotions.
MTCA has only remained a concept with few societies practicing it. It is because the sales forecasting approaches and applications are forever evolving from simple techniques relying on sales history in the past to more sophisticated casual mechanisms such as the application of microeconomics. Many organizations find such concepts very complicated and expensive in terms of training employees and perfecting the ideas (Chase 97)
Seven-Step Process Proposed and used by the Carbonated Soft Drink
All the seven step processes are very essential, and they link well with the three major concerns of the carbonated soft drink industry, which include the sensing demand, shaping demand and the maximization of ROI. The seven procedures touch on the existing marketing mix, business indicators that promote profitability and increased sales volume and the alternative scenarios used in maximizing ROI. Among the seven procedures, the third step is the most complicated. The third step includes testing the predictability of a model while using the ‘ out-of-sample data’, that establishes whether the model can fulfill its duty of predictability. Historical data is essential to predict the future demand. Even though the future data may fit the future data, it is not an assurance that the forecast in the future is accurate. Like in the carbonated soft drink study, the estimate went on for over 153 weeks, with the 13 weeks used as out of sample data. The increased lead times for some specific packaging components is due to the complicated process. Also, the surfacing of more than normal supply and demand issues forces a change in the supply chain after only thirteen weeks of the entire plan (Chase 175).
The scenarios
The scenarios as analyzed in the case study include sensing demand, shaping demand and ways of maximizing Return on Investment. The sensing demand handles the measures the organization undertakes to increase volume in the retail business associated with grocery. The scenario is imperative in demand forecasting because it ensures the production of enough products for existing customers. For the shaping demand, the firm concentrates on major business indicators, to push sales up thus increasing profitability. The third scenario associated with maximization of ROI, the organization researches on other scenarios that can help boost sales and promote productivity. Another fourth scene not mentioned in the case study, but remains important is to understand the consumer in terms of quality and quantity standards. It will ensure that production ultimately meets the needs of the customer (Chase, 178).
Challenges
If the firm is implementing the MTCA for the first time, the major problem includes the cost involved. The organization should invest more funds for promoting the program to meet all the three scenarios and follow the seven steps to the later. Also, it requires highly skilled employees, and it may include soliciting for services from consultations firms, which involves using huge funds. Training of workers is also essential for the program to succeed.
Work Cited
Chase, Charles. Demand-Driven Forecasting: A Structured Approach to Forecasting. New York: Wiley Publishers, 2014. Print.

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