Operations Management - Sprintware Case Study - Why Forecasting is Necessary - Management Assignment Help

Assignment Task

Scenario

Sprintware Inc is a retailer of sports shoes. They cater for ages 5 and up and for both genders. Their range of shoes include running shoes for road, trail and cross training. Each of these categories cater for flat-footed (pronation), normal, and high-arched (supination) individuals. The Sprintware group consists of 27 stores across six countries in Africa. Mr Gump, the owner and founder of the company, for a year has been meeting bi- annually with top management and professional athletes to try to determine the next trend in shoe style, as well as the demand for the shoes. This has worked fairly well in the past, but Mr. Gump feels that, with the increase in the number of stores, this process is becoming tedious. At the same time Mr. Gump would like to free himself from the management of demand forecasting and focus more on further expansion of the African continent. You have been appointed as the new Operations Manager with an initial focus on a more rigorous approach to forecasting.

Some of the newer stores do not yet have any sales data to lean on to ascertain the number of shoes to order from head office. Some investigation of other stores
has shown that the prediction of the demand for shoes is correlated with the number of memberships at local gyms. For one of the stores, you have been asked to use a simple linear regression model to work out the number of road shoes to send to the store, based on the fact that the city in which the store is located has an approximate gym membership of 7 500 people.
 

Assignment questions
1. Include an executive summary highlighting the purpose of the assignment and describing what is covered.

2. Discuss why forecasting is necessary.

3. Determine the difference between quantitative and qualitative measures.

4. Discuss examples of quantitateve forecasting methods that could be used for this scenario.

5. Complete the following calculations using the formula and data provided:

• Naive method for the road shoes 
• Moving average for the trail shoes
• Exponential smoothing for the cross-training shoes

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