Towards an Orchestration of Forecasting Methods to Devise Strategies for Design
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Social, technological, political and environmental paradigms are changing globally at a pace never seen before, giving way to rapid changes in social patterns, culture, and human behavior. Designers and creative industries are constantly trying to develop solutions, which are relevant for the end user and in tune with the current times. Since design itself, is a process of synthesis it cannot be carried out in seclusion. It needs to take into account changes happening in the surroundings and changing consumer preferences. Designing solutions without considering the overarching changes underway and their future impact run the risk of losing large monetary investments going into the process. Hence, it becomes extremely important that the design process is informed by relevant forecasts to address the changes emerging in the overall landscape of society and lifestyle. Forecasters have grappled with ambiguity when devising forecasts for the design of consumer goods, durables, services and other lifestyle products. Multiple factors and distinct needs are involved with design projects. With the plethora of forecasting research methods available, selecting the right forecasting strategy is crucial to designing meaningful and successful products. Forecasting literature provides multiple ways for categorizing forecasting methods, including qualitative, quantitative, normative, exploratory methods. Yet, any classification into such categories would focus on the methods rather than target the need and context for forecasting. This dissertation emphasizes the importance of the strategic forecasting approach to holistically inform the design processes. In particular, this dissertation, aims to facilitate a modular orchestration of methods from the ecology of forecasting approaches through a ‘Composite Framework of Forecasting Methods and Applications’. The composite forecasting framework illustrated in this dissertation gleans from three distinct contexts or needs (predict, prefer, and paradigm-shift) for forecasting and utilizes operational caveats (availability of data, lead time, nature of forecast and forecasting range) to guide the selection of forecasting methods. The strategic selection of methods thus obtained enables achieving relevant and accurate future insights, constructively informing design processes geared towards specific forecasting needs and contexts. Applying the composite forecasting framework to real world scenarios opens future conversations for an interdisciplinary perspective on design processes and a richer amalgamation of forecasting techniques.