Leitax Case Essay

* Forecasting is an impartial strategic ingredient that will ensure apt base for reputable planning. Our forecast is always the first step in developing plans in running the business along with our future plans of growth strategies. With this tool, we are able to anticipate our sales within reason that then can allow for us to control our costs in conjunction with inventory which will then help us to enhance our customer service. Sales forecasting is a vital strategic tactic in our company’s methodology.

In an article published on the Harvard Business Review website we see that “a factory needs to be flexible and respond to customer orders quickly” (Upton 1995). As the global market for products is growing factories need to be able to keep up with the demand of products in many more countries than they had in years past. Managers have to make decisions on whether or not to expand a factory or build a new factory and the decision between the two have large differences in cost. Forecasting can help managers decide if they should expand or not expand. Capacity does not need to be crowded because that can lead to decrease in quality of products and can cause underproduction. Capacity decisions are one of the toughest decisions manager have to

3. Market Share: forecasting will help in identifying the size of the market share and market potential will aid in the manufacturing and distribution process. Will also aid in proper utilization and eliminate waste.

However, from the case study, it is difficult to do so due to two main reasons which are insufficient information and long production’s lead time. Information would slowly become more obvious when it approaches the peak season while the long production’s lead time is a constraint which prevents the company from producing at the point where adequate data are available. Therefore, to improve company’s performance, the first thing is to forecast demand more accurately from the first beginning. Wally now only based his first phase production decision on individual forecasts. However, from the exhibit 5, it shows how demand forecasts improve with increasing information. With the lack of information, Wally might take into account and use past statistical deviation between initial and final forecast, which is the closest to the real demand, when he makes a decision. In textile and fashion industry where things change rapidly, people who have more experience and close to customers are those who are most likely to accurately foresee the future trends. So inviting retailers, especially salesmen or shop managers, to help with the demand forecasting is a good idea (Giordano also used this effective strategy to forecast demand).

Fixing the forecasts allows to build the communication between the different departments of a firm (communication between the operational staff, the financial staff, etc.). It should be also a guide for financial planning and monitoring the activity and the performance. It is a tool to evaluate profitability and productivity, to identify an eventual gap between actuals and OP (operating plan), and to fix it.

Along with better communication, improved forecasting can help a supply chain run better. If you are able to forecast customer demand, you have a better chance on not being “tricked” by signals throughout the chain. A company can improve forecasting by looking at their past history, the history within their industry, or simply by asking their customers; predominantly through surveys or focus groups. Another way to improve you supply chain is to see if there is an opportunity to reduce the number of parties or complexity within the supply chain. The more stations there are the better chance for errors and delays. It is also easier to find and solve issues if your process is less complex. A smaller group also allows for better relationships between

It is recommended that a deep analysis should be performed for the forecast errors in the previous years to identify similarities, patterns and trends that would collect certain items together under one forecast error distribution, instead of grouping all new items together. Distinguishing between forecasting for “never out” (Staples) vs. “new” items. In the case for “new” items, then histories of similar new products introduced by L.L. Bean can serve as historical guidelines to help derive a new product sales forecast. Market Research and Surveys: Finding new ways to get advanced market feedback on new products prior to launching, such as ending a survey to customers to find out their preferences among the products displayed. In return, offer

The current demand forecasting method is based on qualitative techniques more than quantitative ones. If the forecast is not accurate, the company would carry both inventory and stock out costs. It might lose customers due to shortage of supply or carry additional holding costs due to excess production. If the actual demand doesn’t match the forecast ones, and the forecast was too high, this will result in high inventories, obsolescence, asset disposals, and increased carrying costs. When a forecast is too low, the customer resorts to a competitive product or retailer. A supplier could lose both sales and shelf space at that retail location forever if their predictions continue to be inaccurate. The tolerance level of the average consumer

Two Vice Presidents for the company Keene and Ryan come to the conclusion that a task force must be created to make sense of the final forecast and product demand forecast that the four marketing managers created. The task force found many problems some being systematic bias and that it seemed information was being withheld. In the end at the presentation it becomes obvious that the problems were poorly done incorrect forecasting and a collaboration to prevent people from becoming aware of it, by withholding information and

The decision to introduce more sophisticated forecasting techniques to aid the demand planning process would not have worked well for Leitax.   The introduction of the system Fowler and McMillan introduced was a significant change for the staff of this company, thus trusting the system and improving the system for better accuracy would pay off more than confusing things by adding more sophisticated models.   Relying on the most robust model, the statistical model has proven successful in Leitax’s past, but Fowler was concerned the DMS group would seem over bearing. I think DMS had the ability to utilize statistical modeling while also bringing all stakeholders together in a manner that was cooperative versus over

* As stated in the guidelines, we also assume that the mean of the demand is equal to the product of the mean of the forecasting error and the forecast itself, and the same for the standard deviation of demand;

The ecosystems that digital versus physical products have, including their supply chains are vastly different. These differences in their supply chains have a significant impact on the abilities each has to innovate. Digital products manufacturers are highly dependent on their supply chain, often creating shared collaboration

More precise prediction indicates enhanced production assessments, and enhanced trade judgment stand for increasing revenue. A right sales estimation ought to be a forecasting of that will occur independent of what you believe will come about and nearly all, what you feel like to take place. Major expansion has been made in the function of numerical facts study to establish more correct sales predictions of upcoming market pattern. Such trading predictions give a separate, impassive vision of the marketplace. Good-quality sales prediction diminishes the ambiguity about the expectations, and fantastic sales predication exchange this doubts into likelihood.

But even this is not possible in case of a new product or innovation. A forecast of sales, demand, cash, requirements and several such business valuables are extremely essential for a business in order to be able to appropriately plan and conduct its operations in an effective and efficient manner. Yet, forecasts cannot be made accurately as there are several factors and changes in the current environment that leads to variations in forecasts and impacts or causes a manager to make changes in the forecasts.

All organizations that supply goods or services to another business or consumer look at demand forecasting for planning purposes. Young (2010) stated for most organizations, the marketing department will forecast the demand for both the short and long term planning and the operations department will work closely to set a production forecast based on these demands. When forecasting, organizations must take into consideration all the possible factors that will affect the supply/demand. These factors include trends, seasonality, competitive pricing, sudden changes in demand, economic conditions, labor and strikes, and more. In today’s business world, forecasting is not just a necessity, but also a means of survival, which is why predicting the future, is so important for the short and long-term success of an organization. As the northeast vice president of operations for McDonalds, I have the complex and challenging role of ensuring accurate forecast are submitted for the internal and external demand for our products.