Management

CO6: “Utilize quantitative forecasting methods with time series data”

Forum Prompt:

After carefully reading Chapter 5 in your textbook and reviewing the additional resources in the Lessons area of the Sakai classroom, think about forecasting using Time-series Data in your organization. Address the three subjects below:

1) What are the various ways a forecast can go wrong using historic data to predict future requirements, resources, or customer demands?

2) What statistical methods are used to “sense demand signals, shape demand, and forecast demand” (Chase, p. 126).

3) What time-series data is used to forecast future demand for products, services, or activities in your organization? From your experience, how accurate is the time-series data that is used to forecast and how accurate are the forecasts?

PS: I ATTACHED THE EBOOK on file FOR THIS CHAPTER. (page 126).
“(250-300 words)”ANSWER

Business Forecasting

Forecasting is important for all-size businesses to thrive. The primary component that forecasters use is historical data. However, a forecast based on historical data can go wrong in various ways, as discussed below.

When someone initiates a business, it is not easy to predict its performance accurately. Past indicators are used to estimate income and losses for all other enterprises using historical records. Clearly, the data is not available at the beginning of a business (Gilliland et al., 2016, p. 67).

Secondly, confident entrepreneurs typically project growth sequentially, with sustained steady growth. It produces what appears like a graph of the hockey stick, predicting that the venture will have impressive growth that will continue to expand and increase steadily. Investors can approach illustrations of hockey sticks immediately with cynicism, realizing that the prediction is exaggerated.

Lastly and related to expecting rapid and steady growth right from the beginning, business people prefer to cherry-pick data and leave out other vital pieces of information. The demand for one’s product, market volume, pricing, and marketing costs is only a few of the components of a well-developed forecast that a large number of investors ignore (Gilliland et al., 2016, p. 67).

Statistical methods such as trend projection and barometric techniques are used to sense demand signals, shape demand, and forecast demand. According to Gilliland et al. (2016, p. 88) trend projection is used when it is necessary to make a detailed assessment. In this method, time plays a significant role. For estimating demand, this approach uses historical and cross-sectional data. This strategy assumes that whatever the market trend has been in the past will remain stable in the future. The time series reflects the historical pattern of strong demand for particular goods and is used to predict the time series trend. The barometric technique is the use of economic. This approach is centered on the premise that all present-day activities can be used to forecast the future.

In my company, we use demand forecasting. This projection gives estimation of how many goods and services the company’s consumers will be consuming in the near future (Gilliland et al., 2016, p. 102). Critical market projections such as sales, profit margins, cash flow, capital spending, risk evaluation, and mitigation plans, capacity planning rely on this forecast to improve their productivity in meeting demand while minimizing overall operating costs.

References

Gilliland, M., Sglavo, U., & Tashman, L. (2016). Business forecasting: Practical problems and solutions. John Wiley & Sons.