Demand Forecasting Techniques and their use within Dell Corporation

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.

All businesses are confronted with the general problem of having to make decisions under conditions of uncertainty. Management must understand the nature of demand and competition in order to develop realistic business plans, determine a strategic vision for the organization, and determine technology and infrastructure needs. To address these challenges, forecasting is used. According to Makridakis (1989), forecasting future events can be characterized as the search for answers to one or more of the following questions:

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

* 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.

Forecasting is used in all businesses. Forecasting is used to help businesses decide how much they should produce and where to sell a product. Forecasting can aid a company in knowing the lifecycle of a product, which can help them to determine when and if they should discontinue a product. Forecasting can also help managers close the gap between supply and demand. If a forecast is properly predicted the supply of a product can satisfy the demand of the product. Forecasting is not always accurate however, and can lead to either over production of a product or underproduction of a product.

This research paper was developed with the main purpose of presenting an overview that define and explain the importance of demand forecasting aligned with the Sales & Operations Planning. In addition, through the analysis of the content presented in this paper, readers will be able to understand each aspect involved with the topic in discussion as well as its application against the competitive business market faced by companies worldwide. More importantly, by analyzing the content presented in this research paper, readers will also be able to learn and comprehend that when well applied, forecasting methods within the sales & operations planning can be key business tools for companies in their path for success.

Forecasting: It is an important step required to anticipate the future events that might occur with the mentioned changes. There may be a possible need for expansion of services to compete with the technological advances; continued mergers; increased spending on operations as well as research and development.

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).

Factors affecting forecast error and accuracy- Time horizon, Level of detail – product, geography, time.

Guidelines and examples to improve efficiency of other organizations that don’t use these methods by adopting these forecasting practices.

M&L Manufacturing Company is an example of a company that could benefit from forecasting. In the past the company has made an educated guess to determine necessary production for

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.

• Transactional buyers – SMB and Personal,user call centers, and AD’s by DELL to reach out to them

Of the many strategic and tactical uses of forecasting, the most critical from a cost standpoint is to mitigate risk and optimize potential revenue gains over time. The best forecasting frameworks and implementations balance risk mitigation and optimized revenue levels to stabilize the entire value chains of businesses (Hanafizadeh, Moosakhani, Bakhshi, 2009). The forecasting process over time can become an indispensable aspect of any broader strategic and knowledge management process including serving as a highly effective system of record (Kahn, Adams, 2001).

Based on the case, there were two fundamental changes to standardize and improve the accuracy of forecasts. The first area was to "switch the focus of the focus of the forecasting process from sell-in to sell-through". This meant tracking closely what was sold in one region and shipped from another made forecasting market demand a more accurate exercise. The second area centered on ignoring capacity constraints to estimate demand. In the past, "forecasting was affected by perceptions of present and future supply chain capacity".