BUSINESS OPERATIONS
Business Operations: Follow-Up Response
Peer Discussion 3
Time series analysis is a useful tool for making strategic predictions and decisions for a companys future with statistically-based models. It should be understood that exact predictions cannot be through this model; however, keeping the future directions clear with the number analysis and processing through time-series data is a beneficial tool for better decision making rather appearing strayed only (Gerunov, 2016). The underlying cause of a certain notable pattern that has occurred over the past and whether it would be sustained in the future are some of the key deciding factors for a business provided with this statistical analysis tool.
A human judgment could be a useful technique for making forecasts for a business, which could be in focus groups. Group methods, such as focus groups, are among the fastest ways to obtain and share information about...
The opinions and attitudes of the people involved in these groups can disseminate some crucial points that could help forecast the firms for their future profits and value creation.Peer Discussion
The importance of time series analysis cannot be overstated in this case;...
…stage of its growth, like concept testing, pre-test markets, early sales, etc. (Mas-Machucha, Sainz & Martinez-Costa, 2014). It is an easy method for its usage, and the data could be conveniently extracted from the responses. It could be either conducted online or physically/ face-to-face. Its applicability for the firm is apt as the existing preferences are assessed along with identifying any gaps where changes could be made to bring new products, by even sometimes changing the preferences, as Apple did when they replaced the traditional Walkman with their IPods and Apple music library from where people could download hundreds of songs…
References
Gerunov, A.A. (2016). Automating analytics: Forecasting time series in economics and business. Journal of Economics and Political Economy, 3(2), 340-349.
Mas-Machucha, M., Sainz, M. & Martinez-Costa, C. (2014). A review of forecasting models for new products. Intangible Capital. http://dx.doi.org/10.3926/ic.482
Zellner, M., Abbas, A. E., Budescu, D. V., & Galstyan, A. (2021). A survey of human judgment and quantitative forecasting methods. Royal Society Open Science, 8(2), 201187. https://doi.org/10.1098/rsos.201187
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