Fashion Trend and Forecasting – SFDA1302

SCHOOL OF SCIENCE AND HUMANITIES DEPARTMENT OF FASHION DESIGN UNIT – I – Fashion Trend and Forecasting – SFDA1302 UNIT I (9Hrs) Trend forecasting- Introduction, Objectives. Importance of forecasting, Elements of forecasting, Principles of forecasting, Theories explaining forecasting, Steps in forecasting, Major areas of forecasting, Advantages and limitations in forecasting. Trend forecasting Introduction Trend Forecasting is the process of researching and formulating predictions on consumers future buying habits. By identifying the source, tracing the evolution, and recognising patterns of trends, forecasters are able to provide designers and brands with a ‘vision’ of the future. Forecasters research and identify social, cultural, ethical or environmental shifts, and how they are likely to affect future consumer behaviour. Through this process, they can identify products and services that consumers will be looking to buy. Objectives Trend forecasting is an overall process that focuses on other industries such as automobiles, medicine, food and beverages, literature, and home furnishings. Fashion forecasters are responsible for attracting consumers and helping retail businesses and designers sell their brands. Importance of forecasting Forecasting is used in almost every area of business today. Accurate analysis of consumer trends is vital in forming brand direction and development, in the creation of relevant products and services and ultimately in ensuring their success. Some important practices involved in fashion forecasting are: Understanding the seasons, whether the trends are being worked upon for Spring/ Summer or Fall/ Winter Studying trends as per the selected season and a closer look on the markets that are being catered Understanding the demography of that particular area Very importantly, deciding on the product category. Elements of forecasting Forecasting, therefore, helps to know the expected profits or losses and just by going through certain reports and records of the company, enables the forecaster to take necessary decisions. Decision- making becomes better and easier when forecasting is undertaken on scientific basis. 1. Developing the ground work: It carries out an orderly investigation of products, company and industry. 2. Estimating future business: This follows a clear-cut plan for working out future expectancies in the form of natural undertaking with key executives. 3. Comparing actual with estimated results: Checking the attained with anticipated results of the business periodically and tracking down reasons for major differences. 4. Refining the Forecast Process: Once familiarity with estimating the future of the business is gained through practice, sharpening the approach and refining the procedure becomes quite easy. Principles of forecasting There are many types of forecasting models. They differ in their degree of complexity, the amount of data they use, and the way they generate the forecast. However, some features are common to all forecasting models. They include the following: 1. Forecasts are rarely perfect. Forecasting the future involves uncertainty. Therefore, it is almost impossible to make a perfect prediction. Forecasters know that they have to live with a certain amount of error, which is the difference between what is forecast and what actually happens. The goal of forecasting is to generate good forecasts on the average over time and to keep forecast errors as low as possible. 2. Forecasts are more accurate for groups or families of items rather than for individual items. When items are grouped together, their individual high and low values can cancel each other out. The data for a group of items can be stable even when individual items in the group are very unstable. Consequently, one can obtain a higher degree of accuracy when forecasting for a group of items rather than for individual items. For example, you cannot expect the same degree of accuracy if you are forecasting sales of long-sleeved hunter green polo shirts that you can expect when forecasting sales of all polo shirts. 3. Forecasts are more accurate for shorter than longer time horizons. The shorter the time horizon of the forecast, the lower the degree of uncertainty. Data do not change very much in the short run. Theories explaining forecasting Theories of Business Forecasting: Theory of Economic Rhythm Action and Reaction Approach Sequence Method or Time Lag Method Specific Historical Analogy Cross-Cut Analysis Model Building Approach Business Forecasting: Theory # 1. Theory of Economic Rhythm: This theory propounds that the economic phenomena behave in a rhythmic manner and cycles of nearly the same intensity and duration tend to recur. According to this theory, the available historical data have to be analysed into their components, i.e. trend, seasonal, cyclical and irregular variations. The secular trend obtained from the historical data is projected a number of years into the future on a graph or with the help of mathematical trend equations. If the phenomena is cyclical in behaviour, the trend should be adjusted for cyclical movements. When the forecast for a year is to be split into months or quarters then the forecaster should adjust the projected figures for seasonal variations also with the help of seasonal indices. It becomes difficult to predict irregular variations and hence, rhythm method should be used along with other methods to avoid inaccuracy in forecasts. However, it must be remembered that business cycles may not be strictly periodic and the very assumptions of this theory may not be true as history may not repeat. Business Forecasting: Theory # 2. Action and Reaction Approach: This theory is based on the Newton’s ‘Third Law of Motion’, i.e., for every action there is an equal and opposite reaction. When we apply this law to business, it implies that it there if depression in a particular field of business, there is bound to be boom in it sooner or later. It reminds us of the business, cycle which has four phases, i.e., prosperity, decline, depression and prosperity. This theory regards a certain level of business activity as normal and the forecaster has to estimate the normal level carefully. According to this theory, if the price of commodity goes beyond the normal level, it must come down also below the normal level because of the increased production and supply of that commodity. Business Forecasting: Theory # 3. Sequence Method or Time Lag Method: This theory is based on the behaviour of different businesses which show similar movements occurring successively but not simultaneously. As such, this method takes into account time lag based on the theory of lead-lag relationship which holds good in most cases. The series that usually change earlier serve as forecast for other related series. However, the accuracy of forecasts under this method depends upon the accuracy with which time lag is estimated. Business Forecasting: Theory # 4. Specific Historical Analogy: This theory is based on the assumption that history repeats itself. It simply implies that whatever happened in the past under a set of circumstances is likely to happen in future under the same set of conditions. Thus, a forecaster has to analyse the past data to select such period whose conditions are similar to the period of forecasting. Further, while predicting for the future, some adjustments may be made for the special circumstances which prevail at the time of making the forecasts. Business Forecasting: Theory # 5. Cross-Cut Analysis: In this method of business forecasting, the combined effect of various factors is not studied, but the effect of each factor, that has a bearing on the forecast, is studied independently. This theory is similar to the Analysis of Time Series under the statistical methods. Business Forecasting: Theory # 6. Model Building Approach: This approach makes use of mathematical equations for drawing economic models. These models depict the inter-relationships amongst the various factors affecting the economy or business. The expected values for dependent variables are then ascertained by putting the values of known variables in the model. This approach is highly mechanical and this can be rarely employed in business conditions. Steps in forecasting The 6 Steps in Business Forecasting Forecasting is sometimes an overlooked part of business management. Other aspects, like small business inventory management, are already so time-consuming that there is little energy left to dedicate to it. However, predicting future events can greatly help leaders make the best possible decisions. In order to boost your small business inventory management efficiency and leave some time for forecasting, you can start using a mobile inventory app. You already took this step? Great. Then let’s take a look at how the business forecasting process usually occurs. 1. Identify the Problem Defining the problem can seem simple at first because it looks like you are simply asking how will the market react to a new product, or how the company’s sales will look like in a few months. Even more so if you have a good forecasting tool for small business. However, this step is quite tricky because there aren’t actually any tools that can help here. It requires you to know who the forecast is directed too, how the market works, and what your customer base and competition are. You should spend some time evaluating these issues together with the people who will be responsible for maintaining databases and gathering the data. 2. Collect Information We say information here, and not data, because data may not be available yet if for example the forecast is aimed at a new product. Having said this, the information comes essentially in two ways: the knowledge gathered by experts and actual data. If no data is yet available, the information must come from the judgments made by experts in the area. If the forecast is based solely on judgment and no actual data, we are in the field of qualitative forecasting. If data is available on the subject, a model is used to analyze the data and predict future values.

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