Define the purpose of the forecast
Demands and trends are the main factors that call for business forecast in any given business field. Forecasting is an important activity in determining appropriate positioning of a given business in its future perspective (Mason, 2013). For this case, the following are some of the reasons for business forecast;
What are the available opportunities for pursuing Television products?
How have other television products similar to our products prospered in the market?
Is the business worth investing in; and if so, what business segments?
How should the business allocate research and development efforts and funds?
How successful will different products concepts be?
How will our television products fit into the market in the next five or ten years from now?
Forecasts that can be used to attend to the above questions should develop a long horizon. Similarly, it is important to carry out a testing and introduction study in order to fully leverage on the market potential of the product (Rapach & Wohar, 2008). Establishing real-time answers is the pathway to achieving significant profits, it is important to appropriate amount of money and effort in order to achieve great forecasts.
Establish a time horizon
The usual time horizon for a business forecast is 4-5 years, for this specific forecast, seven years will be the appropriate time horizon. Given that this is a new business that is kicking off its operations in the business market, there are no relevant past data that can be used to develop an analytical forecast. Therefore, for this specific forecast, it is appropriate to use a time horizon of seven years.
Select a forecasting technique
Market research is the most appropriate forecasting technique that is suitable for this specific forecasting. Market research is both a quantitative and qualitative forecasting technique that sought to explicitly identify a market niche for the viability of a new product (Lawrence & Klimberg, 2011). It is within the limits of the research and development department to develop survey segments that will be used to source real-time information from the field. Data projection of a 7-year time horizon is appropriate for use in this forecasting.
Gather and analyze relevant data
The data that will be used in this specific forecasting are those that are based pure market assumptions. Therefore, data with a 7-year time horizon will be generated and analyzed appropriately. The following are set of data for the 7-year time horizon;
(1) Consumer goods
(2) Household appliances
(3) Radio, TV, and others
(4) Total columns of 3 & 4 (5) Column 5 divide col. 2(6) % column 4 divide col. 2 (7) %
2008 110.9 3.18 1.43 4.61 4.16 1.29
2009 118.9 3.47 1.48 4.95 4.16 1.23
2010 119.1 3.13 1.70 4.83 4.06 1.43
2011 128.6 3.94 2.46 6.40 4.98 1.91
2012 138.4 3.87 2.26 6.13 4.43 1.63
2013 143.3 3.82 2.37 6.19 4.32 1.65
2014 150.0 3.99 2.61 6.60 4.40 1.74
2015 151.1 4.02 2.74 6.77 4.48 1.81
Table 1.1; expenditures on appliances versus all consumer goods (in billion $)
In analyzing these data, it is important to consider that there is a common increasing trend in all the columns. In the year 2008, households that bought radio and TV did spend approximately $1.43 billion, in the year 2015 a total of $2.74 billion were spent on purchasing the same items, this is an increase by almost double the amount. In analyzing the consumer goods versus home appliances (radio and TV), column 5, 6 and 7 shows an increase in expenditures over time.
Perform the forecasting process
In executing a forecasting process, a 7-year time horizon will be considered. The data that will be included in the forecast are based on the past data that were generated. The following is the forecast process for a 7-year time horizon;
(1) Consumer goods (2) Household appliances (3) Radio and TV (4) Total of column 3 & 4 (5) Col. 5 divide by col. 2 (6) Col. 4 divide by col. 2 (7)
2016 162.9 4.69 2.79 7.48 4.59 1.71
2017 168.2 4.89 2.87 7.76 4.61 1.71
2018 176.4 4.63 3.00 7.63 4.33 1.70
2019 178.1 4.44 3.07 7.51 4.22 1.72
2020 190.9 4.86 3.42 8.28 4.34 1.79
2021 196.6 4.74 3.62 8.36 4.25 1.84
2022 200.1 4.77 3.76 8.53 4.26 1.88
Table 1.2: expenditures on appliances versus all consumer goods (billion dollars)
Evaluate the results
From the forecasting process, it is evident that investing in TV retail is a viable business. The data projected within the 7-year time horizon shows clearly that more and more consumers are spending a lot of money in purchasing these goods. The data from this forecast also shows that, in 2016, it is expected that $2.76 billion will be spent on purchasing radio and TV, in 2022, $3.76 billion will be spent in purchasing the same; this is an increase by $1 billion in terms of revenue. Similarly, consumers are willing to willing to spend more money on purchasing TV more than purchasing normal consumer goods, this evident from column (7).
Brook Lapping Productions. (2009). Starting out in business: Priya Lakhani. London: Teachers TV/UK Dept. of Education.
Lawrence, K. D., & Klimberg, R. K. (2011). Advances in business and management forecasting: Vol. 8. Bingley, U.K: Emerald.
Mason, R. (2013). Successful budgeting and forecasting in a week. London: Hodder Education.
Rapach, D. E., & Wohar, M. E. (2008). Forecasting in the presence of structural breaks and model uncertainty. Bingley: Emerald.
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