Statistical Methods for Forecasting: Alton Bridge Project and Wilkins Plant - Paper Example

Question A. Alton Bridge Project

The Alton Bridge, also known as the Clark Bridge, named after the bridge it replaced is one of the complex projects to ever be taken in the United States. The bridge connects Highways 367 and 67 in Missouri to Alton, Illinois, through the broad River Mississippi. The intent of this discussion is to discuss some of the challenges that faced the construction of this bridge and measures that were taken to solve the drawbacks. Three of the challenges that the project faced include working over water, weather, and the installation of the cable stays on the bridge.

Working over water was one of the toughest challenges faced by the constructors. The bridge which is sometimes referred to as Super Bridge due to its huge size crosses the mighty Mississippi river. The team had to design mechanisms of operations to ensure a balance between the equipment and the materials they were using and the water. To overcome this challenge, the team had to wait for a little while in the mornings before stepping out into the waters to monitor the stability of the water before starting operations. They also had divers for activities underwater. The second challenge was the weather. For instance, when the towers were seventy feet tall, the wind posed a hindrance causing a temporary stop to the construction of the towers. The weather also increased danger and delays later in that year. This was resolved by making support to the towers. There were also the torrential rains that were termed the worst in 500 years, and the construction site was flooded. This was a huge delay since little work could be done until the water subsided. The team utilized crashing technique to recover the lost time to finish the work within the set timeline.

The third challenge that the team faced was with the cable stays which were to be installed in the 112 miles of the bridge two years since the start of the project. The technique they had used for the insulation of the cable stays proved costly since they realized that the coating on the cables was weak. This made the cable stays to cut across the cross section areas as they were pulled against each other. This challenge delayed the project for a month and a half as well as thousands of cables before it was resolved. Fortunately, the team managed to establish a mechanism for passing the cables through a wide pipe in such a way that they did not touch each other to prevent wearing each other.

Question B. Wilkins, A Zurn Company: Demand Forecasting

Bernie Barge, the newly promoted inventory manager at the Wilkins plant, is facing challenges in deciding the best demand forecasting models to use in his presentation for a forecasting meeting. The two product families in line are the Pressure Vacuum Breakers (PVBs), a type of a backflow prevention device, and Fire Valves (FVs), a type of pressure reducing valve for water. Wilkins has been using old forecasting models that lay emphasis only on the past sales over an extended period before new products had been introduced and this poses challenges on the aspect of accuracy. For instance, for the first quarter of 2005, the management had forecasted a sale of 53,560 PVB units but managed to sell 48, 159 units. Forecast for FVs was 559 units but this was exceeded, and sales were at 580 units.

A successful demand estimate is one that considers the three stage procedure forecast on the environment, the industry and finally the sales forecasts (Ali, Sayin, Van and Fransoo, 2009). The environmental forecast will project aspects such as inflation, unemployment rates, consumer spending etcetera. The industry forecast will consider consumers intention and the statistical trends. These two forecasts will assist in projecting demand forecasts for the products in the line and in our case PVBs and FVs. In all these forecasts, a sound judgment based upon facts and without forecaster bias is essential.

As the new inventory manager, my recommendations would be the use of statistical models as they maintain objectivity, are more realistic, and their level of accuracy is high (Abraham and Ledolter, 2009). The updated sales data should be used to create a time series which will show the trend in demand, and this will act as a guide to accurately projecting the demand for the coming periods. As mentioned earlier, the forecast method should be coupled with sound judgment. For the new products, the evolutionary approach should be employed which projects the demand for the new product as an outgrowth and an evolution of an existing old product. The sales demand for old items with almost similar functions as the new item being established in the market should be used to estimate the possible demand rate for the new product. With the adequate creation of awareness of the new product to the consumers, the growth rate will be speedy.

In conclusion, Bernie Barge should incorporate the above models in his presentation and explain the outlined benefits to his superiors, and if implemented, the demand estimates for the company products will be more accurate than before.

References

Abraham, B., & Ledolter, J. (2009). Statistical methods for forecasting (Vol. 234). John Wiley & Sons.Ali, O. G., Sayin, S., Van Woensel, T., & Fransoo, J. (2009). SKU demand forecasting in the presence of promotions. Expert Systems with Applications, 36(10), 12340-12348.

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