Decision support tools Lecture 8: New Balance Case Study

Preparation self-study (yesterday) Read the “New Balance” Case Study on pages 457-458 of the DST module handout. Write down your answers to the questions below and bring them to class on Thursday 27 March. We’ll be using that lecture period to discuss your ideas. You may do this as exercise together with a friend – but please bring something concrete to class that we can all discuss.

Question 1 New Balance invested in a decision support system. What was the actual decision that they needed to make?

Question 1 New Balance invested in a decision support system. What was the actual decision that they needed to make? They needed to decide what quantities of shoes to manufacture in different price ranges, styles and shoe sizes in order to be able to fulfil sales orders without holding excess inventory.

Question 2 With reference to the Problem section of the case study: What was New Balance trying to forecast? What factors can you think of that might have led to inaccurate forecasts being generated by individual salespeople? What factors can you think of that might have led to inaccuracies in the overall forecast that was derived from the sales rep’s information? What negative business impacts could result from inaccurate forecasting?

Question 2 (a) With reference to the Problem section of the case study: (a) What was New Balance trying to forecast? They were trying to forecast sales orders that would be placed by retail outlets, in order to manage production.

Question 2 (b) With reference to the Problem section of the case study: (b) What factors can you think of that might have led to inaccurate forecasts being generated by individual salespeople? Only a few sales reps submitted forecasts – they could have been ones with a history of good sales figures that they were proud of, and smaller orders from other reps might not have been taken into account; or reps might have a tendency to put in optimistic forecasts so that they look good; and reps might not be aware of external factors that could affect future sales. Also a retail company that was ordering shoes might have had weak planning systems themselves.

Question 2 (c) With reference to the Problem section of the case study: (c) What factors can you think of that might have led to inaccuracies in the overall forecast that was derived from the sales rep’s information? The overall forecasts could have been affected by errors in the sales rep spreadsheets; by the fact that forecasts weren’t received from all sales reps and different regions might have different ordering patterns; and their lack of awareness of the potential impact of changing trends and economic factors.

Question 2 (d) With reference to the Problem section of the case study: (d) What negative business impacts could result from inaccurate forecasting?

Question 3 The second sentence in the Solution section of the case study states that “The DSS helped New Balance forecasters take into account such predictors of demand as general economic indicators, current orders, and historic sales data.” Do you think that the DSS system used OLAP functionality or data mining tools to provide this data? Why do you think that? A new feature was provided that made it easy for sales reps to revise their forecasts of customer sales orders. Would you classify this feature as a GDSS? Why or why not?

Question 4 With reference to the Results section of the case study: Some representatives are better at predicting orders than others. How could this information be used to improve the overall accuracy of forecasts? Would you classify the use of the DSS as operational and/or tactical and/or strategic? Why? Would you classify the decision to implement a DSS as operational and/or tactical and/or strategic? Why?

And if we have time

One last question Does this DSS provide support for the Intelligence phase of decision-making? For the Design phase? For the Choice phase? Note: we didn’t have time, so this wasn’t discussed in class. You still might want to think about it though.

Tomorrow (Friday) I’ll be going through a set of Excel tasks similar to what you’ll be doing in next week’s prac (DST prac 2)