M&L Manufacturing

M&L Manufacturing specializes in the fabrication of copiers and printer components. The parts are subsequently distributed to major makers of copiers and printers, as well as computer and office supply companies. The company manufactures about 20 distinct goods. Because the company manufactures components for two primary markets (replacement and manufacturing), it is critical to customize production needs to meet the individual needs of each market. Yet, because some things are overproduced, the company’s operations are inefficient. The company’s output is not efficiently planned. Forecasts are not used by the corporation to plan production. Falling profits, as well as competitive pressures, have forced the operation manager to think of formal forecasting to improve inventory management and production planning. Two items have been identified to kick off the forecasting process.

Demand Forecast for Four Weeks

From the data provided by the manager, the following forecasts can be made;

Forecast for Product 1

The demand for product one can be forecasted using the linear trend method. The model takes the form F=a + bt (Egrioglu et al., 2015). Linear model has been chosen for this product because its demand reveals a linear pattern. The need for this week can be considered to be an outlier. The outlier demand can be replaced with an average demand for week 6 and week 8 in the series. Demand for week 7 can be replaced with 71.5 which represent average demand for week 6 and week 7.

From the attached spreadsheet, the following trend model is established;

F= 46.64 + 3.5t, where t for the next four weeks is 15, 16, 17, 18

Replacing the Value of t in the function gives the following results;

Week, 15: 99.14

16: 102.64

17: 106.14

18: 109.64

Forecasts for Product 2

Product 2 does not reveal a particular pattern in its demand. A naïve or intuitive approach has been used for forecasting the demand for this product. This uses a simple model, F= Ft-1+A (Jaipuria & Mahapatra, 2014). The method is chosen for this product for some reasons; first, the time series is fluctuating and seasonal. Secondly, the technique is easy to use and easy to understand. Using the model, the forecasts will be;

Week, 15: 45

16: 46

17: 47

18: 48

Why Different Methods have been used for the two Products

Different methods have been used to forecast the demand for the two products since their demand patterns are very different. Whereas the demand pattern for product 1 forms a linear model, the demand pattern for product 2 is quite complex and non-linear. A similar method cannot be used to forecast the two products.

Benefits of Formal Forecasting

Formal forecasting brings with it a lot of benefits to businesses. For instance, prediction helps firms to predict the future hence reducing the future uncertainties (Jaipuria & Mahapatra, 2014). Through this, businesses can quickly adapt to future changes in demand and thus make them remain competitive. Forecasting also helps companies to reduce costs associated with excess inventories (Babai, Syntetos, & Teunter, 2014). Essentially, forecasting assists businesses in planning production hence allowing firms to produce what will be demanded therefore avoiding cases of having to keep excess stocks. Through forecasting, it becomes easier to accurately and promptly satisfy the demands of all customers. Forecasts also help businesses to focus ahead to meet sales and production targets which in turn positively impacts on revenue generation and profitability.

References

Babai, M. Z., Syntetos, A., & Teunter, R. (2014). Intermittent demand forecasting: An empirical study on accuracy and the risk of obsolescence. International Journal of Production Economics, 157, 212-219.

Egrioglu, E., Khashei, M., Aladag, C. H., Turksen, I. B., & Yolcu, U. (2015). Advanced time series forecasting methods. Mathematical Problems in Engineering, 2015.

Jaipuria, S., & Mahapatra, S. S. (2014). An improved demand forecasting method to reduce bullwhip effect in supply chains. Expert Systems with Applications, 41(5), 2395-2408.

Stevenson, W. J. (2015). Operations management. New York: McGraw-Hill Education.Boston: McGraw-Hill/Irwin.