Home > Free Essays > Business > Decision Making > Forecasting Strategy of Seven Cycles

Forecasting Strategy of Seven Cycles Coursework

Exclusively available on IvyPanda Available only on IvyPanda
Updated: Jun 5th, 2022

Discussion

Most markets do not show sustainable development and demand; therefore, forecasting is a major factor in the successful operation of a company. Ineffective prognostication can lead to excessive or unnecessary use of resources and subsequent waste. The more volatile the demand is, the more important it is for a company to make an accurate forecast. The purpose of this paper is to discuss the way Seven Cycles utilizes its forecasting strategy and the effect it has on its organizational decisions.

Just-in-Time Method

Seven Cycles is a US bicycle brand, which produces and sells craft-made vehicles. This company actively utilizes forecasting methods to ensure it delivers a valuable product for the market (Seven, 2015). In particular, the firm has employed a Just-in-Time (JIT) manufacturing system. The core of this approach lies in the fact that the producer receives the required inventory when they need it and when the client has placed an order. That is, “a rider ordering a bike actually triggers the process of the bike’s component parts beginning to move toward the bike builder’s workspace” (Seven, 2015, para. 2). Seven Cycles benefits from using this type of forecasting in multiple ways. In particular, they do not need to keep excess inventory and spend money on storing it. The organization can streamline its processes and focus on examining sales patterns. As a rule, sales can have peaks and valleys, and the JIT method is helpful in predicting future demand (Javadian Kootanaee, Babu, & Talari, 2013). The company has to forecast not only local but also regional demand, and the chosen strategy ensures they can do it for a defined customer group.

Conclusion

Thus, it can be concluded that the JIT method utilized by Seven Cycles is a wise approach to demand forecasting. It ensures the management of material flows in production is based on the actual need that is created by the current demand for finished products. Therefore, the company offers high-quality custom bicycles without excess waste and inventory by correctly forecasting the demand for their goods.

References

Javadian Kootanaee, A., Babu, K., & Talari, H. (2013). Just-in-time manufacturing system: From introduction to implement. International Journal of Economics, Business and Finance, 1(2), 7-25.

Seven. (2015). The big ideas – just-in-time manufacturing. [Blog post]. Web.

This coursework on Forecasting Strategy of Seven Cycles was written and submitted by your fellow student. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.
Removal Request
If you are the copyright owner of this paper and no longer wish to have your work published on IvyPanda.
Request the removal

Need a custom Coursework sample written from scratch by
professional specifically for you?

801 certified writers online

Cite This paper
Select a referencing style:

Reference

IvyPanda. (2022, June 5). Forecasting Strategy of Seven Cycles. https://ivypanda.com/essays/forecasting-strategy-of-seven-cycles/

Reference

IvyPanda. (2022, June 5). Forecasting Strategy of Seven Cycles. Retrieved from https://ivypanda.com/essays/forecasting-strategy-of-seven-cycles/

Work Cited

"Forecasting Strategy of Seven Cycles." IvyPanda, 5 June 2022, ivypanda.com/essays/forecasting-strategy-of-seven-cycles/.

1. IvyPanda. "Forecasting Strategy of Seven Cycles." June 5, 2022. https://ivypanda.com/essays/forecasting-strategy-of-seven-cycles/.


Bibliography


IvyPanda. "Forecasting Strategy of Seven Cycles." June 5, 2022. https://ivypanda.com/essays/forecasting-strategy-of-seven-cycles/.

References

IvyPanda. 2022. "Forecasting Strategy of Seven Cycles." June 5, 2022. https://ivypanda.com/essays/forecasting-strategy-of-seven-cycles/.

References

IvyPanda. (2022) 'Forecasting Strategy of Seven Cycles'. 5 June.

Powered by CiteTotal, the best bibliography maker
More related papers