Operations forecasting ops 571

Running Head: Operations Forecasting 1

Forecasting is an essential concept for all organizations. It predicts the coming budgetary conditions of the economy. It is based on analyzing the past and current data to predict a potential foreseeable outcome. Forecasting is never a guarantee of a particular outcome, but it allows organizations to properly prepare for what’s to come. According to John G. Glover, “Business Forecasting is the research procedure to discover those economic, social and financial influences governing business activity, so as to predict or estimate current and future trends or forces which may have a bearing on company policies or future financial, production and marketing operations.” Tesla builds their vehicles made to order from the customers. During this research a comparison and contrast of the three quantitative analytical tools of forecasting Telsa production of the Model S. The forecasting methods are time series analysis, causal relationships and simulations.

Develop Forecasting model Using Excel

The Time Series Methods of forecasting is concepting that organizations use to attempt to manage the unknow future. It renders past data to predict the future. Telsa in the past was known for failing to properly predict the manufacturing of their vehicles in to most present. According to Forbes (2018) “Goldman Sachs' Tesla analyst David Tamberrino reiterated his sell rating and $205 price target. He decreased his Model S and X March quarter delivery projections and believes that the Model 3 production is ramping slower than expected. The company’s stock entered bear territory yesterday, falling 21% from its September 18 intra-day high of $389.61 to a low of $308.76. It has rebounded about $10 from the low to now be down 18% from its high.”

Due to the major shortfall of production during Q2 of 2018, Telsa increased production and making an average 7,000 cars in within three days. The financial analysts implementing the time series analysis to properly hit their targeted productions for the fourth quarter.

Chart 1: Time Series

Another Forecasting tool to analysis Tesla future production is the causal relationship. The purpose of causal forecasting is to implement the most effective statistical analysis relations between one or more independent variables and a dependent variable.

Chart 2: Causal Relationship

Forecast simulation is a forecasting technique where several forecast methods are compared to each other. The method which most closely reflects the actual outcome is then selected to use when calculating the base forecast for the next period. This selection is made each time forecasting is done.

Chart 3: Simulation

Compare and Contrast Forecasting Models

Each Quantitative forecasting model’s Qualitative method of forecasting is often employed where the key trends or developments are hard to capture or where such data is not available. In such a case business analyst used subjective information such as intuition or informed opinion for forecasting the future results. This type of forecast is essential for new products where no historical information is available and primarily used for medium- & long-term planning.

Forecasts is best fitted for Telsa

Based on historical data, the best forecast that best suits Telsa during this current year is the time series forecasting quantitively model. The reason is due to Telsa past shortfall of over predicting the production of manufacturing their vehicles. They have in the past over promised the delivery of their vehicles and have fallen behind on the promises. Customers are expecting a certain promise delivery date, and due to the lack of properly forecasting in the past, Telsa fell behind on the mass promised orders. The failure to properly forecast in the past affected the stock of Telsa during the second quarter of 2018. In most recent the financial Analyst and the CEO of Tesla evaluated the past production rates and applied to the third quarter.

Conclusion

Quantitative Forecasting Models are be used to assist companies in the properly planning of production, ordering of inventory, how many staff they should have on hand and the expected gains of revenue. Without the proper forecasting companies are falling short of producing the gains their investors expect them to make. The lack of properly forecasting will affect the revenue in turn effects the production. Telsa has recently master the proper forecasting by using historical data.

References

Jacobs, F.R., & Chase, R.B. (2014). Operations and supply chain management (14th ed.). New York, NY: McGraw-Hill.

Cheng, B., He, R., Yang, H., & Yang, J. (2005). Quantitative method and model for forecasting R&D expenditures in china. Research Evaluation, 14(1), 51-56. doi:10.3152/147154405781776274

CNBC (2018). Musk says Tesla pushed out 7,000 cars last week. Retrieved from

https://www.cnbc.com/2018/06/29/tesla-q2-production-and-delivery-numbers.html

Forbes (2018). Telsa’s Model S and X Deliveries Could Be Slip-Sliding Away. Retrieved from: https://www.forbes.com/sites/chuckjones/2018/03/21/teslas-model-s-and-x-deliveries-could-be-slip-sliding-away/#4f994c4e5019