Trend Forecasting Steps
Fashion forecasting is generally a career that involves focusing on upcoming trends in the fashion industry. Fashion and trend forecasting is the future determination of mood, behavior and purchasing habits of consumer at a given time of season. It does not only involve determination of markets, consumers in terms of age, their locations and income but also inquire deeply to get to know what they purchase depending on their culture, beliefs, moods as well as geographical location. Fashion and trend forecasting is more reliant on fashion cycle and plays a significant role in introductory stage of consistent fashion cycles.
Fashion and trend forecasting involves a series of activities in each of the area it is dealing with. For example it looks at the; season, target market, consumer, colors, fabrics, silhouette, texture and usage. Therefore, comprehending fashion and trend forecast is not only crucial in determining the success of the ultimate object of the designer but also enhances the continuous repetition of sales in future seasons as well as promoting the fashion cycles.
Unlike in the past when trend forecasting was done manually, current trend forecasting is done using technological forecasting methods although they have been criticized for reducing creativity by most designers. Most trend forecasting are determined by the forecasting method applied by the ultimate user and it is therefore crucial to determine the most appropriate method of trend forecasting in any individuals business model. Generally, any trend forecasting methods involve the following steps (Hines, 2007);
The first step is Problem definition. Although this is the hardest section of forecasting, it is the most important. This step requires keen analysis of how the forecasts will be used, who needs the forecasts as well as how the forecasting technique suits within the firm needs the forecasts. A forecaster should therefore use enough time to every individual who will take part in data collection, keeping the data as well as applying the forecast for future planning. Then gathering of information follows whereby in most cases, statistical or quantitative data and qualitative data are the ones required. Therefore, the collectors of the data should be expertise who can be able to receive the qualitative information from the respondents who are usually the customers if there is no adequate quantitative information (Wong, 2010).
The third step is preliminary analysis, also called exploratory analysis. In this step, the forecaster should consider whether or not there are consistent pattern that lead to significant trend, whether or not there is evidence of business cycles, the presence of outliers in the information that need explanation as well as the extent of relationship between variables present for analysis.
The fourth step is choosing and fitting models. The best method of trend forecasting should depend on the historical data present, the application of the forecasts as well as the extent relationship between the forecasts available and explanatory variables. Some of the methods that can be arrived at includes; exponential smoothing model, ARIMA model, vector autogression, neural networks among others (Wong, 2010).
The last step involves the use and evaluation of the forecasting model. The success of the model can only be determined after the data for the forecast time has been present after which various methods are applied to assess the success of the model.
As earlier stated, the main data required in trend forecasting is qualitative, quantitative and mostly commonly, a combination of the two.
The quantitative research methodology start right from the bottom, where agencies and even the manufacturers either inquires directly from the customers on their purchasing preferences or the organization may record the consumers buying habit in a duration of a given time. The consumer’s response is recorded and used to determine preference for some specific garments, accessories or any other product on research, colors, and sizes among other factors of a product. Surveys through mail, customer response or phones are carried through publication as well as contracting market research organizations for manufacturers and as well as retailers.
The survey questions usually relate to life style, income, shopping habits as well as fashion preference. The customers who participate in these surveys are selected by the research company although they should suit with manufacturers or retailers requirements. Informal discussion with consumer enable researchers get information through asking questions to customers about what they would prefer to purchase, the types they prefer to purchase which is currently present as well as the change in products they require and are not available or they cannot reach. Most researchers use small scale retailers because of their contact and conversation with the customers.
The quantitative methodology entails the use of statistical data or information to determine the trend in customer demands and hence forecast on producing what the consumers purchase the most. Statistical data for fashion sector is easily obtainable without necessarily going to the field because it is available in manufacturers or retailers sales records (Hines, 2007).
From such records, the manufacturers can determine which garments, color of the product, size as well as the fashion preference of the consumer. After that, the manufacturer should be able to determine which fashion product should be produced more depending on sales experienced at each season of the year. It is valuable noting that a well-balanced combination of the qualitative and quantitative research methodologies is bound to boost the success of the model selected for trend forecasting.
This paper has attempted to show that the fashion industry has one main purpose; to offer desirable as well as appealing product to not only satisfy the customer needs, demands and aspire to have them but to also keep the product selling in the subsequent business cycles with a similar season. Every successful trend forecast must commence with the consumer through determination of the consumer’s needs to the market as well as the ability to make the consumer adjust the marketplace to his preferences and lifestyles. The paper has also expounded on the two critical methodologies used in forecast research i.e. the qualitative and quantitative methodologies. It has also emphasized on the need to combine the two methods in order to attain the best results of the model of forecast selected.
Hines, T., & Bruce, M. (Eds.). (2007). Fashion marketing: contemporary issues. Routledge.
Wong, W. K., & Guo, Z. X. (2010). A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm. International Journal of Production Economics, 128(2), 614-624.
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