Case Study

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

NOTE: The project will be done using CONNECT – The student will be provided feedback (once) on cases submitted by the due date. It is the student’s responsibility to send the Instructor an email – shayes@vbgov.com informing them that their chapter cases are ready for review (worth 3 pts.) (All cases in the chapter must be completed before the Instructor will review the cases) are ready for review. No cases will be reviewed past the required submission date.

| |(iii) |Discuss the usefulness of demand elasticity concepts in explaining the strategies adopted by Starbucks to maximise its profit |[8] |

The two main forecasting techniques that can be used to project a sales forecast are quantitative and qualitative. The type of forecast model to be used depends on forecast horizon, available data, accuracy required, forecasting budget, and the individuals forecasting (Jacobs & Chase, 2011). Qualitative methods are more subjective and rely on leadership for the projection so a certain level of experience and knowledge is needed for an accurate forecast. Quantitative methods rely on mathematical calculations using historical data or external data factors that affect the sale of the product.

The major problem of Lancaster-Webb Medical Supply is that they ignored the consumers’ new demand for interact directly communication. They didn’t pay attention to what is the best ways to get close to their customers，they also didn’t open-minded toward new techniques and their influence for consumer’s communicate behavior. Even after they knew the glove girl’s story and influence, the marketing department also didn’t change anything for their new product launches’ strategy, they still only use the CEO’s speech at gathering as their communication way, like what they did 30 years ago.

The focus of Ted Ralley, the Director of marketing research for an auto spare parts company is to calculate future sales for the upcoming business year. His task is to provide the highest levels of forecasting accuracy. To accomplish this, he utilized historic sales data from four years prior, and the most available forecasting method, time series to conduct several forecasts. He was however still apprehensive about results he garnered using the time series method. He is of the view that economic activity and oil prices plays a significant role in auto parts sales, and to substantiate his views he has decided to forecast using econometric variables. It is his intention to base his forecasting decisions and projections for the upcoming year on results derived from analysis surrounding this theory.

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".

Within all I&D branches the customers were monitored closely to see their reactions to the innovations by a variety of means like surveys or statistics on such factors as revenue growth or number of services used by each customer. 1 Shorter turnaround time for feedback would held experimenters learn and prepare modified experiments more rapidly. 2 Despite the great success of the I&D Team, Amy Brady and Warren Butler want to enlarge the learning through experimentation. So in particular, the need for failure so as to generate more learning. 3 But: Butler commented, “(…). If we have too many failures, we just won´t be accepted. Currently, we may have failure within concepts, but not failure in concepts.” 4

Forecast is an important step in the supply chain planning because most of the functional areas of the firm are affected by forecasts. For example, production planning should be done by manufacturing on a day to day basis to meet the customer needs. Forecasts are supposed to be understood by the finance to make a proper level of investment in the plant, equipment, and inventory so that the budgets are constructed for a better management of business. Proper allocation of resources for different product groups and marketing function campaigns are to be known by the marketing function. Forecasts helps the human resources function in hiring and training decisions when the demand is expected to grow, by determining the labour requirements of the firm.

Time series is a very important factor in business today. Organizations always depend on forecasting methods for their management decisions. The methodology itself depends on the availably of the required data and accordingly a judgmental or statistical approach is chosen. Almost every functional area of the organization makes use of the forecasting, for example financial experts use forecasting for cash flow analysis, stock price fluctuations and companies’ valuations. Also personnel departments depend on forecast for their recruitment plans. Logistics and supply chain forecast their inventory levels and their supply and demand. Moreover, there is a huge demand to utilize time series data in

available at the time when the initial forecast is required. Hence, the early forecast must be based largely on subjective considerations (such as the manager's experience and the general demand of a similar or comparable product). As the latest information (actual sales demand) becomes available, the forecasting model is modified with the subjective estimation in the presence of the actual data. This

Often forecasting demand is confused with forecasting sales. But, failing to forecast demand ignores two important phenomena. There is a lot of debate in the demand planning literature as how to measure and

Evaluation of the approach and methods used for sales forecasting as well as monitoring of the actual sale and its comparison with the estimated performance form part of the regular activities of the Sales Manager. As the sales realize for the operating period, they should be monitored at a regular time period. The unfolding of market reality often creates the need to adjust the sales forecasts. Business prudence desires that in the case of annual sales forecasts, the forecasts should be thoroughly reviewed at least on a quarterly basis and if need be, corrected too. A similar review on an annual basis in the case of long-term forecasts is also felt necessary. In the process of carrying out corrections in the sales forecast emphasis should be laid on diagnosing the causes warranting such corrections so that the accuracy level of sales forecasts can be improved. In any case, a strong justification must be made for modifying the sales forecasts so that suitable adjustments in the marketing and sales strategy be also carried out. Many a firms in order to minimise the error factor in sales forecasting, use multiple experts and approaches. At times this results in varying levels of sales forecasts. Under these circumstances, the manager may examine the differing forecasts by:

They also consider demand forecasting through quarterly sales data to forecast future fluctuation and problems.

Question: What kind of forecasting methods do you think a company with the following products would use. For each product take up a company of your choice and justify the use of particular forecasting method for that company.