You are asked to assume the role of the forecaster in each separate scenario, analyze the data, and and prepare the requested forecast(s). When you have completed the assignment, you will have a total of 14 sales volume forecasts. The 5 forecasting problems for this exercise span a range of industry settings and a variety of situations and contexts. Remember, your goal is to develop accurate forecasts. This may require you to apply an exponential smoothing approach, moving average approach, regression analysis, trend line approach, or some combination of these approaches to achieve your goal.

1. Your firm's distribution center (DC) in northeastern France, attached to your Western European manufacturing plant, services customers throughout France, Germany, Belgium, and The Netherlands. On-going DC cross-docking efforts notwithstanding, it appears that the warehouse space used by the DC may not be sufficient for much longer. To gauge future DC space requirements, a forecast of future sales volume (turnover) is needed. Sales data for one of your firm's products are below.

Historical Sales Volume:

First Year 33,343

Second Year 61,983

Third Year 83,995

This product is noteworthy because it's only three years old and sales have increased steadily and dramatically since launch. Indeed, this kind of product volume growth in the Western European marketplace is why the DC is becoming increasingly space-constrained. Perhaps even more importantly, this particular product has a high space-to-turnover ratio. Although it accounts for only about 10% of the total product-line sales volume through the Western European DC, it represents about 40% of warehouse space usage. Develop forecasts of future sales of this product for each of the next three years. Show the method(s) you used, and your rationale the approach(s) used for each problem.

Three separate forecasts are required one each of the fourth year, the fifth year, and the sixth year.

2. The past two years of monthly in-bound call center volumes for one firm are shown in the table below. No major noteworthy competitive market developments have occurred over the last two years, other than general growth in category sales. A forecast of future call center activity would be an important input in planning for facility expansion, leasing of additional capacity, and/or outsourcing of some/all of the firms call center operation.

Year 1 Monthly Usage:

January 12,577 February 12,305 March monthly 13,056 (March Quarterly Usage 37938) April 12,480 May 12,204 June monthly 12,430 (June Quarterly Usage 37114) July 12,656 August 12,775 September monthly 14,349 (Sept Quarterly Usage 39780) October 14,128 November 14,311 December monthly 14,161 (Dec Quarterly Usage 42600)

Year 2 Monthly Usage:

January 14,169 February 14,960 March monthly 14,940 (March quarterly 44,069) April 15,890 May 16,198 June monthly 15,898 (June quarterly 47,986 July 16,721 August 16,929 September monthly 17,128 (Sept quarterly 50,778) October 15,769 November 17,003 December monthly 15,323 (Dec quarterly 48,095 )

Develop forecasts of call center usage (call volume) for each of the first two quarters of Year 3. Only quarterly usage forecasts are required, not monthly forecasts.

Q: Year 3, Quarter 1 Forecast? Year 3, Quarter 2 Forecast?

3. Five years of a well-established brands monthly sales volume data are shown in the table below. As may be noted, there is substantial seasonality in this brand's sales.

Year 1 Year 2 Year 3 Year 4 Year 5

January 5550 4782 5283 3460 4014

February 5398 3897 3544 4665 4954

March 4236 5293 4070 3930 4276

April 2977 3747 2419 3065 3350

May 2345 2235 1863 1946 2074

June 1198 1156 1887 1602 1250

July 1090 1196 1194 1818 1392

August 1530 1889 1759 2190 1642

September 1388 1324 2077 2007 1836

October 1522 1069 1440 1187 993

November 2252 1763 1601 1571 1356

December 3746 2312 3712 2720 2542

Develop a monthly sales volume forecast for the brand for each of the first six months of Year 6. A total of six monthly forecasts are needed one for each of January, Year 6 through to June, Year 6.

	Year 6, January Forecast
	Year 6, February Forecast
	Year 6, March Forecast
	Year 6, April Forecast
	Year 6, May Forecast
	Year 6, June Forecast

4. As the production planner for one of your firms product lines, you receive sales forecasts from your firms regional sales managers about the middle of each month. Based on these sales forecasts for the following month, you need to create production plans for each of the two products in your product line. A comparison of forecasts vs. actual sales data for the past four months for two products for two channels from a new-appointed regional sales manager are shown in the table below. The indirect channel is the retail channel and retailers typically hold some buffer inventory of their own to service varying final-customer demand requirements. The direct channel involves direct-to-final-customer sales via an e-commerce sales channel and associated major account initiatives. These channels do partially overlap, for those customers who view both channels as viable ways of purchasing these products.

Indirect- Channel- Direct- Channel Indirect- Channel- Direct- Channel

Forecast- Actual -Forecast- Actual Forecast- Actual- Forecast- Actual

Product 1 Product 2

Month 1 - 4,500- 13,271- 6,500- 4,519 4,400- 5,863- 3,900- 2,584

Month 2 - 21,000- 9,260- 8,500- 10,850 9,000- 4,895- 4,000- 3,111

Month 3 - 11,000- 3,820- 11,000- 4,684 5,500- 7,502- 3,500- 4,848

Month 4 - 7,000- 16,748- 8,000- 12,126 9,000- 653- 6,000- 2,567

Month 5 - 16,000- 12,000 6,000- 4,500

Based on these data and particularly on the sales managers month-5 forecasts shown in the table, what production volume would you schedule in month 5 for each of these two products? For each product, you must make a total sales volume forecast (the total combined sales volume for the indirect and direct channels). Your production planning goal is to have production volume exactly equal sales. Assume that its equally bad to over- or under forecast and over- or under-produce (i.e., its equally costly to have excess inventory as it is to have unfilled orders), you have no on-hand inventory, and there are no significant setup costs for your regular monthly production run.

Q: Product 1, Month 5 Forecast? Product 2, Month 5 Forecast?

5. As a manufacturer selling directly to final end-users, your sales and inventory transaction systems normally have up-to-date information on sales and inventory from which you create production plans. In selling through intermediaries, a variety of complications arise. Channel members maintain inventory buffer stocks to service their customers. Suppliers may or may not be aware of channel members inventory policies and levels. In addition, channel members may or may not share their generate-demand program plans and/or their customer sales data with upstream suppliers. For upstream suppliers, collaboration and information sharing with downstream channel members has value. Various possibilities for supply chain collaboration exist. Plan sharing, plan coordination, and EDI (electronic data interchange) are three examples of supply chain collaboration. However, downstream channel members arent always willing or able to collaborate in a timely fashion and at the level of information disaggregation of interest and value to upstream suppliers. Alpha-channel historical orders, sales, and promotional activity data are shown in the table below:

Alpha-Channel Activities

Week Orders Sales Inventory Promotion? 1 11,700 9,468 2,232 No

2 15,500 16,585 1,147 Yes

3 12,200 12,030 1,317 Yes

4 8,100 6,953 2,464 No

5 10,900 11,629 1,735 No

6 17,600 17,945 1,390 Yes

7 7,500 No

8 18,400

Regarding these data and this product and channel:

The Alpha channel is one particular distributor of one of your products.

Orders are the orders (in units) from the channel (i.e., your sales) for delivery in the specified week, Sales are the sales (in units) to final customers made by the Alpha channel, and Promotion? describes whether the Alpha channel conducted any special promotion/merchandising program during a particular week.

This product was reconfigured prior to week 1 so the week-1 orders reflect expected sales plus any inventory build-up by the Alpha channel to have a suitable amount of reconfigured product inventory on-hand to service final customers requirements.

There is no known sales seasonality for this particular product.

Q: Alpha Channels Orders, Month 9 Forecast?