In: Economics
Jan Northcutt, owner of Northcutt Bikes, started business in 1995. She notices the quality of bikes she purchased for sale in her bike shop declining while the prices went up. She also found it more difficult to obtain the features she wanted on ordered bikes without waiting for months. Her frustration turned to a determination to build her own bikes to her particular customer specifications.
She began by buying all the necessary parts (frames, seats, tires, etc.) and assembling them in a rented garage using two helpers. As the word spread about her shop’s responsiveness to options, delivery, and quality, however, the individual customer base grew to include other bike shops in the area. As her business grew and demanded more of her attention, she soon found it necessary to sell the bike shop itself and concentrate on the production of bikes from a fairly large leased factory space.
As the business continued to grow, she backward integrated more and more processes into her operation, so that now she purchases less than 50% of the component value of the manufactured bikes. This not only improves her control of production quality but also helps her control the costs of production and makes the final product more cost attractive to her customers.
The Current Situation
Jan considers herself a hands-on manager and has typically used her intuition and her knowledge of the market to anticipate production needs. Since one of her founding principles was rapid and reliable delivery to customer specification, she felt she needed to begin production of the basic parts for each particular style of bike well in advance of demand. In that way she could have the basic frame, wheels, and standard accessories started in production prior to the recognition of actual demand, leaving only the optional add-ons to assemble once the order came in. Her turnaround time for an order of less than half the industry average is considered a major strategic advantage, and she feels it is vital for her to maintain or even improve on response time if she is to maintain her successful operation.
As the customer base have grown, however, the number of customers Jan knows personally has shrunk significantly as a percentage of the total customer base for Northcutt Bikes, and many of these new customers are expecting or even demanding very short response times, as that is what attracted them to Northcutt Bikes in the first place. This condition, in addition to the volatility of overall demand, has put a strain on capacity planning. She finds that at times there is a lot of idle time (adding significantly to costs), whereas at other times the demand exceeds capacity and hurts customer response time. The production facility has therefore turned to trying to project demand for certain models, and actually building a finished goods inventory of those models. This has not proven to be too satisfactory, as it has actually hurt costs and some response times. Reasons include the following:
The inventory problem has grown to the point that additional storage space is needed, and that is a cost that Jan would like to avoid if possible.
Another problem that Jan faces is the volatility of demand for bikes. Since she is worried about unproductive idle time and yet does not wish to lay off her workers during times of low demand, she has allowed them to continue to work steadily and build finished goods. This makes the problem of building the “right” finished goods even more important, especially given the tight availability of storage space.
Past Demand
The following shows the monthly demand for one major product line: the standard 26-inch 10-speed street bike. Although it is only one of Jan’s products, it is representative of most of the major product lines currently being produced by Northcutt Bikes. If Jan can find a way to sue this data to more constructively understand her demand, she feels she can probably use the same methodologies to project demand for other major product families. Such knowledge can allow her, she feels, to plan more effectively and continue to be responsive while still controlling costs.
Actual Demand |
||||
Month |
2011 |
2012 |
2013 |
2014 |
January |
437 |
712 |
613 |
701 |
February |
605 |
732 |
984 |
1291 |
March |
722 |
829 |
812 |
1162 |
April |
893 |
992 |
1218 |
1088 |
May |
901 |
1148 |
1187 |
1497 |
June |
1311 |
1552 |
1430 |
1781 |
July |
1055 |
927 |
1392 |
1843 |
August |
975 |
1284 |
1481 |
839 |
September |
822 |
1118 |
940 |
1273 |
October |
893 |
737 |
994 |
912 |
November |
599 |
983 |
807 |
996 |
December |
608 |
872 |
527 |
792 |
Questions and assignment:
The data gives an idea about the sales of bikes in different months of the year. Thus we'll get to know the patern of demand in various, which month has got higher demand and which month has got lower demand. Accordingly the inventory can be kept ready so that there wont be any excessive or shortfall of inventory.
The two methods used are 3 period Moving Average and 4 period Moving Average methods.
3 Period Moving Average for the Month of January : 712 + 613 + 701 / 3 = 675
February : 732 + 984 + 1291 / 3 = 1002
March : 829 + 812 + 1162 / 3 = 934
April : 992 + 1218 + 1088 / 3 =1099
4 Period Moving Average Method for the month of January : 437 + 712 + 613 + 701 /4 = 616
February : 605 + 732 + 984 + 1291 / 4 = 903
March : 722 + 829 + 812 + 1162 / 4 = 881
April : 893 + 992 + 1218 + 1088 / 4 = 1048
4 Period Moving Average Method is better as it has considered more number of past sat sales record and thus the sales smoothens out for more number of months and gives more accurate sales forecast.
Jan's knowledge can be used as she is serving the market for the past so many months and thus knows the market very well. As the sales and demand of bikes varies on monthly basis and thus it is better to forecast on monthly basis.
Jan's could have taken experts and sales force opinion and thus can predict the sales more accurately and finally serves the customers in a much better way.