The use of trend forecasting in the product development process

Twine, Christine (2015) The use of trend forecasting in the product development process. Doctoral thesis (PhD), Manchester Metropolitan University.

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Abstract

Fashion trend forecasting is often personnel and company dependant and is more likely to be influenced by intuition and personal inspiration. Trend forecasting had been regarded as a driving force of the fashion industry in determining the new fashion trends in fabric, colour and style. There is a dearth of information on the utilisation and application of trend forecasting. There was a need to explore the application of trend forecasting within contemporary design and retail environments. Hence, the rationale of this investigation was to identify how and where trend forecasting is incorporated in the product development process. Soft Systems Methodology (SSM) provided the framework to the primary research. The process focussed on the trend forecasting agencies and how trend forecasting was used by the fashion industry. The concept of fast fashion and its role in changing the model of fashion trend forecasting was critically analysed working through the stages of SSM. Interview data and process mapping were used to establish theoretical models which were tested, refined and validated for the timescales and process used in seasonal and fast fashion contexts. The research was addressed within the context of the UK clothing sector. From an initial analysis of the issues, shortcomings were identified in the seasonal process. These were linked to the buyers and designers having limited communication and fragmented decision making during the range planning process. The ‘open to buy’ process conducted at the end of the range planning season to address ‘close to season’ fashion relies upon repeated orders and unplanned inputs, copied from their competitors. This is because it is difficult to design completely new garments for the required timeframe. In the fast fashion process, it was found the designers had no input into the ‘bought-in’ fashion range resulting in a lack of continuity of how the total range would appear. Fast fashion relies upon ‘bought-in’ fashion and the ‘open to buy’ process relies upon trends based on ‘current influences’ and repeat orders because it is quicker than producing completely new garments within a reduced timescale. The final phase of this research contributes to a new synthesis of information relating to trend forecasting in contemporary design, marketing and retailing environments. A critique of the theoretical models was carried out for areas not discussed before with trend forecasters, buyers and designers. These industry personnel explained how trend forecasting was used in the model stages, alternatives to trend forecasting, the process, timeline and how ‘bought-in’ fashion is used as a solution to fast fashion. This research has resulted in revised models where trend forecasting is successfully located within the seasonal and fast fashion product development. The crux of this research identified the consultation meetings and communication channels which were accurately located in the new models. The models document how key personnel interact, specifically the trend forecaster, the product line manager, the designer and the buyer. In the fast fashion model the ‘bought-in’ range is clearly distinguished from the seasonal range. The new models quantify the timeline for seasonal fashion, fast fashion and ‘open to buy’. The current fashion forecasting system is derived from seasonal fashion and therefore reliant on long lead times. The rise of fast fashion provided the opportunity to identify a taxonomy of models with a shortened time frame. The original contribution to knowledge lies in the seasonal and fast fashion models directly arising from this research, that would facilitate the key personnel involved in the fashion industry to incorporate in their new product development. This results in greater involvement of personnel leading to efficient utilisation of time, resources and expertise in the trend forecasting process.