What Role Could Dell Use Collaborative Forecasting At Dell

Forecasts are extensively used to support business decisions and direct the work of operations managers. The two major types of forecasts are qualitative and quantitative. Within each of these types are multiple methods and models. Qualitative forecasts are based upon subjective data. Quantitative forecasts are derived from objective data. Both methods are not suitable for all situations and circumstances. Each has inherent strengths and weaknesses. The forecaster must understand the strengths and shortcomings of each method and choose appropriately. One example of forecasting is the United States Marine Corps use of forecasting techniques, both qualitative and quantitative, to predict ammunition requirements.

Dell uses a just in time order fulfillment policy and accurate forecasting of sales to minimize inventories. This allowed Dell to hold inventory of finished products far below levels of their competitors (10-20% compared to 50-70% industry level) and furthermore allowed them to quickly implement changes to their product lines as new technologies became available. This quick inventory turnover also allowed Dell to retain more capital. Finally, this policy enabled Dell to respond immediately to technological progress in components and deliver state of the art new finished products (e.g. Pc’s holding the newest Pentium microprocessors) while competitors

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

Barilla, the leading pasta manufacturer in Italy, faces increasing problems related to demand fluctuation. Their distributors also suffer from high inventory holding costs and low service levels on the other hand. This report explains, why the company and their distributors are troubled with this situation and how Barilla intends to solve it. The problem Barilla experiences is called the “Bullwhip Effect”, i.e. that demand variability increases when moving up the supply chain. Several factors enforce this Bullwhip Effect, e.g. high lead times, poor demand forecasting, and batch ordering. In this report we will point out, that exactly those aspects can be identified as the underlying reasons for Barilla’s problems. In a

* 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.

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.

Manufacturing support performance cycles serve as the logistics of production. These functions maintain orderly and economic flow of materials and work-in-process inventory to support production schedules. The goal is to support manufacturing requirements in the most efficient manner. These are internal cycles to the firm, thus they are rarely affected by behavioral uncertainty. Customer accommodation performance cycles are those associated with processing & delivering customer orders. They link customers through timely & economical product availability. Physical distribution integrates marketing and manufacturing efforts. To improve the effectiveness forecast accuracy must improve to reduce uncertainty.

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

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.

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.

Before, the concept of demand forecast was to serve the key functional groups in achieving their own interest. Facing the new challenges, forecast needed to be more accurate. And therefore it needed a new concept that is to have a consensus forecasting that would accurately reveal market demand and align the needs of key actors in the forecasting process. Leitax implemented two specific changes in forecasting process. The first one is to switch the focus from sell-in to sell-through and second one is to ignore capacity constraints.

As director of Supply Chain Systems, Teri Takai recommends implementing virtual integration strategies from companies like Dell to portions of Ford’s supply chain strategy. Although there are several key differences between the companies, the restructuring plans of Ford 2000 have set a viable foundation to implement Dell’s virtual integration strategy in inventory management, customer service and support and suppliers’ management. The redesign of the process must include design not only of the supply chain but also of fulfillment, forecasting, purchasing, and a variety of other functions that historically been considered independently within the Ford hierarchy. Teri

I will recommend the BOD to approach the Dell model with a prudent attitude, neither too aggressive nor too timid. Emulating the virtual integration should focus on developing the strategic partnerships with technologically advanced suppliers and eliminating the correlation with smaller ones. Ford would make sure that key suppliers have access to forecasting data from customers' purchasing trends and production information to enable a faster order-to-delivery cycle. The difference in the distribution model between Dell and Ford lies in the middle link of using retail shops. Since Ford cannot skip retail as a focal distribution point, it should work on establishing a network of retail shops that it owned. Ford make sure shops are not affecting

What was the critical mission and scope of work of the Forecast Re-Design Team? What supply chain leadership qualities and skills had

Business forecasting is the process of studying historical performance for the purpose of using the information gained to project future business conditions so that decisions can be made today that will assist in the achievement of certain goals. Forecasting involves taking historical date and using it to project future data with a mathematical model. Forecasts are extensively used to support business decisions and direct the work of operations managers. In this paper I will introduce different types of forecasting techniques.