A real options-based approach to designing for changing user populations of long-lifetime products
In addition to robustness-related considerations, designers of long-lifetime products (e.g., freight trucks and commercial aircraft) must also account for possible secular and demographic trends and their impacts on the ranges of anthropometry, capability, and preference of user populations. However, the uncertainty associated with forecasts of these trends complicates the decision-making process of the designer. One of the decisions to be made is whether to efficiently allocate adjustability to accommodate the required percentage of only the current user population or to allocate additional amounts of adjustability to allow for more uniformly high accommodation levels throughout the product’s lifetime. Postponing this decision until later in the life of the product could be a valuable option. This paper proposes a Black Scholes model-based real options methodology for the valuation of such decision-postponement in the design process. A simplified truck cab designed in 1977 and with a lifetime of 30 years is used as a demonstrative case study. The three population change scenarios considered are: no change, changes due to a secular trend (gradually increasing obesity), and changes due to a demographic trend (gradually changing gender split). Anthropometry synthesized for the user population in these three scenarios is utilized to study the impact of certain adjustability-allocation decisions on the accommodation levels of these populations. The secular trends scenario indicates the need to embed greater-than-optimal truck cab space which in future may be used for a seat designed for the more obese user population. This decision is treated as a real option and is evaluated for different levels of uncertainty associated with secular trend forecasts and for different required rates of return. Despite the limitations of the approach due to certain simplifying assumptions, it is shown to be a good basis for future research into designing for changing user populations of long-lifetime products.